Saeed Khodaygan

"R3T*-MOSafeRL: path planning of mobile robots in unknown dynamic environments"

Homayoun Honari, Saeed Khodaygan

Journal Paper Intelligent Service Robotics (2024): 1-17

Abstract

Path planning has a wide range of applications in many fields of engineering. One of the widely used approaches to solve this problem is sampling-based algorithms. However, a significant limitation of these algorithms is their inability to function effectively in the presence of unknown obstacles within the environment. A feasible way of addressing this issue is by using reinforcement learning to interact with the environment. In the context of path planning, safety means choosing safe and non-optimal paths over the optimal ones and having as few collisions as possible during both the training phase and the test phase. In this paper, a novel two-stage algorithm called R3T*-MOSafeRL( ) is proposed capable of path planning safely in an environment with unknown dynamic obstacles. In the first stage, the Roadmap Multi-Tree RRT* (R3T*) algorithm is presented which uses an initial map of the environment and an expert’s information regarding the important regions of the environment to generate a roadmap. The roadmap acts as discretization of the continuous environment to practically deploy tabular reinforcement learning algorithms on top of it. In the next stage, the algorithm uses a novel eligibility trace-based multi-objective safe reinforcement learning (MOSafeRL( )) to perform safe path planning on the roadmap generated by R3T*. Moreover, a heatmap algorithm based on the roadmap and the weights learned by MOSafeRL( ) is presented which provides an interpretable method to gain information about the regions of the map with high activity of the unknown dynamic obstacles. Hence, the proposed algorithm provides a powerful method for path planning in unknown dynamic environments. Finally, to illustrate the efficiency of the proposed algorithm and to verify it, some case studies are considered and the computational results are compared and discussed..

"Design for additive manufacturing of topology-optimized structures based on deep learning and transfer learning"

Maede Mohseni, Saeed Khodaygan

Journal Paper Rapid Prototyping Journal (2024): 1-17

Abstract

Purpose This paper aims to improve the manufacturability of additive manufacturing (AM) for topology-optimized (TO) structures. Enhancement of manufacturability focuses on modifying geometric constraints and classifying the building orientation (BO) of AM parts to reduce stresses and support structures (SSs). To this end, artificial intelligence (AI) networks are being developed to automate design for additive manufacturing (DfAM). Design/methodology/approach This study considers three geometric constraints for their correction by convolutional autoencoders (CAEs) and transfer learning (TL). Furthermore, BOs of AM parts are classified using generative adversarial (GAN) and classification networks to reduce the SS. To verify the results, finite element analysis (FEA) is performed to compare the stresses of modified components with the original ones. Moreover, one sample is produced by the laser-based powder bed fusion (LB-PBF) in the BO predicted by the AI to observe its SSs. Findings CAE and TL resulted in promoting the manufacturability of TO components. FEA demonstrated that enhancing manufacturability leads to a 50% reduction in stresses. Additionally, training GAN and pre-training the ResNet-18 resulted in 80%, 95% and 96% accuracy for training, validation and testing. The production of a sample with LB-PBF demonstrated that the predicted BO by ResNet-18 does not require SSs. Originality/value This paper provides an automatic platform for DfAM of TO parts. Consequently, complex TO parts can be designed most feasibly and manufactured by AM technologies with minimal material usage, residual stresses and distortions..

"An interface tool for finite element–based optimal design"

Parinaz Ranjbaran, Saeed Khodaygan

Journal Paper International Journal on Interactive Design and Manufacturing (IJIDeM)(2024): 1-17

Abstract

Optimal design of engineering systems with complex geometry under multiple loadings is always a challenging procedure. This paper introduces a computational interface tool between ABAQUS® and MATLAB® that can be used for carrying out the parametric optimal design of complex mechanical components. The software is developed entirely in MATLAB® environment which can handle constrained optimization problems without the need for the user to explicitly define the constraints using mathematical equations or functions. In this software, the design variables are proposed for selection through a user-friendly environment and the objective function can be iteratively evaluated by the finite-element analysis in ABAQUS®. The finite-element model is modified and updated according to the post-processing results in the ABAQUS® environment. The optimizing tool can cover metaheuristic optimization algorithms such as Genetic Algorithm in MATLAB®. Finally, the capability of the proposed tool is illustrated by investigating the optimal design of some engineering case studies..

"Deep reinforcement learning-based framework for constrained any-objective optimization"

Homayoun Honari, Saeed Khodaygan

Journal Paper Journal of Ambient Intelligence and Humanized Computing (2023): 1-17

Abstract

Optimization problems are widely used in many real-world applications. These problems are rarely unconstrained and are usually considered constrained optimization problems. Regarding the number of objectives, the optimization problems can be categorized into single- (for one), multi- (usually for two and three), and many- (more than three) objective optimization problems. In this paper, an Any-Objective Optimization (AOO) framework is introduced based on Deep Reinforcement Learning (DRL) models. The term any-objective optimization is coined to indicate the generalized structure of the proposed algorithm that regardless of the number of objectives, can solve the constrained optimization problems with any number of objectives. To trade off the multiple conflicting objectives, RL algorithms can be extended to a framework called Multi-Objective Reinforcement Learning (MORL). By converting a constrained optimization problem into an environment that can be explored by the MORL and deep learning algorithms, any constrained optimization problem can be tackled. In this research, to solve a constrained optimization problem with any number of objective functions, a novel reward function is introduced, and the algorithm begins a heuristic search in the environment to find the optimal solution(s) and generates an archive of the optimal Pareto front solution. The corresponding environment is constructed modular, such that any RL algorithm with arbitrary reward function types (scalar or vector) can be utilized. To evaluate the proposed algorithm, some popular test function-defined constrained optimization problems with continuous variable and objective spaces as illustrative examples are considered, and five of the widely used DRL algorithms are implemented to test the case studies. To demonstrate the capabilities of the proposed algorithm, the obtained results are compared with structurally similar GA-based well-known existing single-, multi-, and many-objective optimization algorithms, respectively. The results show that the proposed framework can be a well-performing baseline for a new type of DRL-based optimization algorithm. This paper presents a local failure analysis of the ultralight shell-based lattices and explores the effects of the aforementioned factors on their strength and failure mechanism under compression. The main finding of this research is that unlike the high-relative density lattices, which are not sensitive to geometric deviations, in the design of ultralight shell-based lattices (with relative densities lower than 26%), beside the loading conditions, the constituent material and relative density should be considered, as well. For example, for a 10% relative density lattice designed for a triaxial compressive macroscopic state of stress, if the base material is stainless steel, the minimal surface is the optimal unit-cells, while if it is made of pyrolytic carbon, a constant mean curvature surface with a certain value of mean curvature other than zero is optimal. However, for shell-based lattices with relative densities higher than 26%, the geometric deviation does not influence the lattice strength and thus the optimal geometry can be designed without regard to the base material and relative density..

"Effect of geometric deviations on the strength of additively manufactured ultralight periodic shell-based lattices"

Kia Dastani, Mohammad R. Movahhedy, Hongyu Yu, Saeed Khodaygan , Lei Zhang, Michael Yu Wang

Journal Paper Engineering Failure Analysis (2023), https://doi.org/10.1016/j.engfailanal.2023.107328

Abstract

Lightweight shell-based lattice structures with various multifunctional applications can be fabricated with limited manufacturing constraints, thanks to the advancements of additive manufacturing technologies. However, there is always a geometric deviation between the 3D digital model and the additively manufactured lattice structure. In some cases, the geometric deviations may be as small as the machine accuracy, but they would cause a significant decrease in the strength of the lattice. In other cases, the lattice may not be so sensitive to geometric deviations. The sensitivity of lattice structures to the geometric deviations depends on their constituent material, loading condition, relative density, and the geometry of the unit-cell. To understand this, buckling failure should be considered beside yielding. This paper presents a local failure analysis of the ultralight shell-based lattices and explores the effects of the aforementioned factors on their strength and failure mechanism under compression. The main finding of this research is that unlike the high-relative density lattices, which are not sensitive to geometric deviations, in the design of ultralight shell-based lattices (with relative densities lower than 26%), beside the loading conditions, the constituent material and relative density should be considered, as well. For example, for a 10% relative density lattice designed for a triaxial compressive macroscopic state of stress, if the base material is stainless steel, the minimal surface is the optimal unit-cells, while if it is made of pyrolytic carbon, a constant mean curvature surface with a certain value of mean curvature other than zero is optimal. However, for shell-based lattices with relative densities higher than 26%, the geometric deviation does not influence the lattice strength and thus the optimal geometry can be designed without regard to the base material and relative density..

"Concurrent optimization of surface roughness, build time, and mechanical properties of additively manufactured product in terms of part build orientation"

Irana Darvishi, Saeed Khodaygan , Kaivan Mohammadi, Amirhossein Golmohammadi

Journal Paper Progress in Additive Manufacturing (2023), https://doi.org/10.1016/j.engfailanal.2023.107328

Abstract

With the increasing tendency to use the Additive manufacturing (AM) process and especially the Selective laser melting (SLM), improving the properties of the AM part becomes essential. Among the governing parameters for producing an AM part, part build orientation (PBO) is the most important one that can improve the properties by an appropriate adjusting. In this study, the surface roughness, build time, and mechanical properties of AM part are optimized and the results will be selected based on each objective function (OF) importance. To achieve this purpose, the OF for each property is derived from the literature. Then the OFs meta-modeled through the Kriging method and sample points of the Latin hypercube sampling (LHS) method to solve the original OFs problem of being time-consuming. Both original and estimated OFs are optimized by the multi-objective optimization of the non-dominant genetic algorithm (NSGAII) method. The results are ranked according to their importance by the Technique for order of preference by similarity to the ideal solution (TOPSIS) method. First, to illustrate the capability of the analytical original OFs, a comparison is made between the results of experimental tests and analytical original OFs optimum orientations. Finally, to evaluate the efficiency of the surrogate model, the results of the original OFs compared to the estimated ones by the Analysis of variance (ANOVA). Finally, a solution is proposed for the original OFs being computationally expensive by deriving surrogate models from the original OFs. <--! href="">.

"A continuous RRT*-based path planning method for non-holonomic mobile robots using B-spline curves"

S.A. Eshtehardian, S. Khodaygan

Journal Paper Journal of Ambient Intelligence and Humanized Computing (2022): 1-10

Abstract

Rapidly exploring random trees (RRT) are sampling-based approaches being widely applied for path planning of mobile robots. Since the output of these algorithms usually is a stream of discrete lines involving discontinuity at the linking points, kinematic constraints restrict the robot's movements. Consequently, robots may not pass discrete points in the path correctly. Hence, the using CAGD (Computer-Aided Geometry Design) curves can run simultaneously alongside those algorithms or may run after that to make a smooth path and that's the way in which non-holonomic constraints can be considered perfect and robots can be droved autonomously across them about the collision detection method which executed by the main sampling-based algorithm like RRT*. In this paper, an approach based on the combination of RRT* and B-spline is proposed for smoothing the path which is generated by RRT*-based algorithms, which are one of the most famous groups of algorithms in artificial intelligence. Some new functions are added to the outcome of the RRT* algorithm. To avoid collision in the generated path, some corrections are also provided. Finally, for illustrating the efficiency of the proposed method, the algorithm is implemented in the simulation environment of Webots ® and for verification, the obtained results are compared and discussed..

"Reliability-based optimal tolerance design of mechanical systems including epistemic uncertainty"

H. Hassani, S. Khodaygan

Journal Paper International Journal of Mechanics and Materials in Design (2022): 1-18‏

Abstract

As an essential step of product design, tolerance design plays a critical role in reducing manufacturing costs while ensuring mechanical assemblies’ quality and reliability. However, existing tolerance allocation approaches only are concentrated on design specification constraints during the design stage, although component degradation caused by environmental and operating conditions increases the probability of product failure during the service life. To deal with the degradation effect arising over the service life of mechanical assemblies, this paper proposes a reliability-based tolerance design approach to allocate optimal, reliable tolerances to mechanical systems. The proposed approach rewrites the tolerance allocation problem as a two-objective optimization problem with probabilistic constraints, where time-dependent reliability is incorporated to ensure the product’s reliable and consistent operation during the specified service life. Then, the proposed approach applies the non-dominated sorting genetic algorithm II and an entropy-based TOPSIS method to obtain the non-dominated optimal tolerances and the best solution, respectively. In addition, unlike previous methods, epistemic uncertainty effects are considered in this work. A modified linear degradation model is developed to include the epistemic uncertainty in the degradation model’s parameters and investigate the effects of uncertainties on reliability.Accordingly, the proposed approach employs a single-loop sampling procedure to incorporate the effects of epistemic uncertainty on the obtained optimal tolerances. Finally, to illustrate the capability of the proposed method, an industrial case study is considered, and the obtained results and performances are compared and discussed..

"Tolerance analysis of a compliant assembly using random Non-Uniform Rational B-Spline curves and isogeometric method"

Mostafa Aghabeigi, Saeed Khodaygan, Mohammad Reza Movahhedy

Journal Paper Journal of Computational Design and Engineering, Volume 9, Issue 6, December 2022, Pages 2170–2195, https://doi.org/10.1093/jcde/qwac093‏

Abstract

Non-Uniform Rational B-Spline (NURBS) is one of the most versatile tools of computer-aided design. The concept of random NURBS curves is introduced for modeling the geometrical errors in mechanical parts and assemblies. The proposed idea is utilized to solve an example problem involving deformable components. For this purpose, profile tolerances of the parts are transformed into covariance matrices of NURBS control polygon parameters. Then, the control polygons are used as vector chains to calculate geometrical error propagation. Afterwards, isogeometric analysis (IGA) is invoked to express deformations of the parts during the assembly process as changes in the shape of the underlying control polygons. Finally, the result of the calculations is translated back into the tolerance zone of the assembly. Numerical examples are employed to examine the effect of NURBS structure (degree, knot vector, and control points) on convergence and stability of results. Outcomes of the theory are compared with direct measurements of actual assemblies and results of a Monte Carlo finite element simulation to illustrate the validity of the results. Furthermore, the developed model is used to obtain practical guidelines regarding the reduction of geometrical errors by the optimum design of the assembly..

"Prognostic of rolling element bearings based on early-stage developing faults."

Yazdi, M. Hosseini, M. Behzad, S. Khodaygan

Book Chapter Advances in Condition Monitoring and Structural Health Monitoring. Springer, Singapore, 2021. 333-342.‏

Abstract

Rolling element bearing (REB) failure is one of the general damages in rotating machinery. In this manner, the correct prediction of remaining useful life (RUL) of REB is a crucial challenge to move forward the unwavering quality of the machines. One of the main difficulties in implementing data-driven methods for RUL prediction is to choose proper features that represent real damage progression. In this article, by using the outcomes of frequency analysis through the envelope method, the initiated/existed defects on the ball bearings are identified. Also, new features based on developing faults of ball bearings are recommended to estimate RUL. Early-stage faults in ball bearings usually include inner race, outer race, ball and cage failing. These features represent the sharing of each failure mode in failure. By calculating the severity of any failure mode, the contribution of each mode can be considered as the input to an artificial neural network. Also, the wavelet transform is used to choose an appropriate frequency band for filtering the vibration signal. The laboratory data of the ball bearing accelerated life (PROGNOSTIA) are used to confirm the method. To random changes reduction in recorded vibration data, which is primary in real-life experiments, a preprocessing calculation is connected to the raw data. The results obtained by using new features show a more accurate estimation of the bearings’ RUL and enhanced prediction capability of the proposed method. Also, results indicate that if the contribution of each failure mode is considered as the input of the neural network, then RUL is predicted more precisely.

"Direct tolerance analysis of mechanical assemblies with normal and non-normal tolerances for predicting product quality"

H. Hassani, S. Khodaygan

Journal Paper International Journal of Computer Integrated Manufacturing (2022): 1-18‏

Abstract

Tolerance analysis, as an effective tool for predicting the effects of geometrical and dimensional deviations on the key characteristics, plays an essential role in increasing the functionality and quality of mechanical products. The conventional methods in the literature have been developed based on this main assumption that the assembly function is available in an explicit form. However, in most industrial applications, deriving an assembly function in an explicit form may be difficult if not impossible. On the other hand, one of the major weaknesses of the conventional tolerance analysis methods in the literature is that all effective dimensions should be varied under the normality assumption. To overcome these weaknesses, in this paper, a new tolerance analysis approach is developed based on the univariate DRM and Pearson system concepts. The proposed method can analyze directly without the need to define any assembly function and also the rejected product rate can be easily predicted using evaluations of the assembly dimension at the limited number of special points. Finally, for verification of the proposed method, some illustrative case studies are considered and results are compared to obtained results of the Monte-Carlo Simulations and the improved Hassofer-Lind and Rack-Fizzler reliability index methods..

"A Bayesian-reliability based multi-objective optimization for tolerance design of mechanical assemblies."

Ghaderi, A., H. Hassani, S. Khodaygan

Journal Paper Reliability Engineering & System Safety 213 (2021): 107748

Abstract

Tolerances significantly affect the assemblability of components, the product's performance, and manufacturing cost in mechanical assemblies. Despite the importance of product reliability assessment, the reliability-based tolerance design of mechanical assemblies has not been previously considered in the literature. In this paper, a novel method based on Bayesian modeling is proposed for the tolerance-reliability analysis and allocation of complex assemblies where the explicit assembly functions are difficult or impossible to extract. To reach this aim, a Bayesian model is developed for tolerance-reliability analysis. Then, a multi-objective optimization formulation is proposed for obtaining the optimum tolerances of components to minimize cost and maximize product performance. Subsequently, Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed for solving multi-objective optimization. Then, the enhanced TOPSIS is used to find the best optimum tolerances from the optimum Pareto solutions. Using the importance vector concept, a sensitivity analysis approach is used to determine the effects of design variables on the product reliability level and improve assembly reliability to the desired level. Finally, to exhibit the applicability of the proposed method, a transmission planetary gear system is considered, and the obtained results are compared and discussed for verification. .

"Colloidal particle reaction and aggregation control in the Electrohydrodynamic 3D printing technology"

Mohammadi, Kaivan, Mohammad R. Movahhedy, Saeed Khodaygan

Journal Paper International Journal of Mechanical Sciences 195 (2021): 106222.‏

Abstract

The electrohydrodynamic (EHD) 3D printing technology is an Additive Manufacturing (AM) method that can be used in the manufacture of submicron-size structures. In this process, which is based on the formation of Taylor jet from a metallic ink, the investigation of particles reaction and aggregate formation in ink during printing is of great importance. In this paper, a new Finite Element model based on particle tracing in fluids is presented that couples the different physics that govern an EHD phenomenon. Vortex flow caused by boundary shear stress was observed in the ink jet; which was more like the Marangoni phenomenon in a stationary drop. By experimentally validating the presented model with the help of PIV technique, the effects of important parameters (volume fraction, number and size of particles, zeta potential, viscosity, voltage application rate) on aggregate formation were studied based on the DLVO theory. In general, any change of parameters that leads to the increase of volume fraction also boosts the amount of formed aggregates. No interaction effect was observed between the parameters of volume fraction, particle radius and number of particles. It was demonstrated that the DLVO theory by itself is not sufficient for determining colloidal ink stability, and that the parameters of volume fraction, radius and number of particles should also be investigated for this purpose. Considering the conditions of EHD printers, the amount of zeta potential needed for colloid stability increases significantly; and a minimum zeta potential of 110 mV is required for colloid stability. A too-low or too-high value of viscosity (μ > 500 mPa.s, μ < 3 mPa.s) and a low rate of applied voltage also lead to reduced aggregation..

"Minimization of Non-repeatable Runout (NRRO) in High-Speed Spindle Bearings"

Farahani, M. R., S. Khodaygan

Journal Paper No. 2021-01-5023. SAE Technical Paper, 2021.‏‏

Abstract

The production with high quality at the lowest production time can be a key means to success in the competitive environment of manufacturing companies. Therefore, in recent years, the need for extra precise and high-speed machine tools has been impressively increased in manufacturing applications. One of the main sources of errors in the motion of high-speed spindles is the occurrence of non-repetitive runouts (NRRO) in the bearing. The NRRO can be caused by some factors such as the form of balls, the waviness of rings, the number of balls, and the permutation of one or two balls in the ball bearing. In this paper, a Taguchi-based approach is proposed for the optimal design of high-speed spindle bearings by minimizing the NRRO in the machine tools compatible with corresponding standards. First, the optimal design of the high-speed spindle bearings to minimize the NRRO is formulated. To reach this aim, a two-dimensional (2D) model for formulating the NRRO in the ball bearings of the spindle is presented based on the Hertzian contact theory. Subsequently, the objective function and the constraints are formulated in terms of the design parameters for the simulations and the optimization processes. To find the effective parameters with significant impact, above 95% confidence level, the sensitivity analysis is carried out based on the Plackett-Burman design. The optimal robust design of high-speed spindle bearings for minimizing the NRRO is carried out through the Taguchi optimization method. For numerical optimization, the optimal design is formulated in two scenarios based on the Response Surface Method (RSM), and then it is solved by Genetic Algorithm (GA). For verification, the obtained results are compared and discussed.

"An algorithm for numerical nonlinear optimization: Fertile Field Algorithm (FFA)."

Mohammadi, M., S. Khodaygan

Journal Paper Journal of Ambient Intelligence and Humanized Computing 11.2 (2020): 865-878 ‏

Abstract

Nature, as a rich source of solutions, can be an inspirational guide to answer scientific expectations. Seed dispersal mechanism as one of the most common reproduction method among the plants is a unique technique with millions of years of evolutionary history. In this paper, inspired by plants survival, a novel method of optimization is presented, which is called Fertile Field Algorithm. One of the main challenges of stochastic optimization methods is related to the efficiency of the searching process for finding the global optimal solution. Seeding procedure is the most common reproduction method among all the plants. In the proposed method, the searching process is carried out through a new algorithm based on the seed dispersal mechanisms by the wind and the animals in the field. The proposed algorithm is appropriate for continuous nonlinear optimization problems. The efficiency of the proposed method is examined in details through some of the standard benchmark functions and demonstrated its capability in comparison to other nature-inspired algorithms. Obtained results show that the proposed algorithm is efficient and accurate to find optimal solutions for multimodal optimization problems with few optimal points. To evaluate the effects of the key parameters of the proposed algorithm on the results, a sensitivity analysis is carried out. Finally, to illustrate the applicability of FFA, a continuous constrained single-objective optimization problem as an optimal engineering design is considered and discussed.

"Multi-objective optimal design of stiffened laminated composite cylindrical shell with piezoelectric actuators."

Saeed Khodaygan, Mehdi Bohlooly

Journal Paper International Journal on Interactive Design and Manufacturing (IJIDeM) (2020): 1-17.‏

Abstract

The stiffeners and piezoelectric actuators are used in many aerospace structures as an auxiliary layer with laminated composites. A question then arises as to whether we can estimate the percentage of these materials in an efficient design. Due to the high computational cost, it is not easy to answer through numerical solutions. The objective of this paper is concurrently to maximize the buckling load and minimize the weight of the cylindrical shell. To reach this aim, a multi-objective optimization problem is developed based on the closed-form solutions of thermal/mechanical buckling and weight of the piezolaminated shell with eccentric/concentric stiffener. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used for solving multi-criteria optimization. Shannon’s entropy-based TOPSIS decision-making algorithm is employed to select the best design from Pareto fronts. To illustrate the potential of lightweight optimal design in structural stability, the obtained optimal and conventional designs are compared.

"Optimal path-planning for mobile robots to find a hidden target in an unknown environment based on machine learning."

Sombolestan, S. M., A. Rasooli, S. Khodaygan

Journal Paper Journal of Ambient Intelligence and Humanized Computing 10.5 (2019): 1841-1850‏

Abstract

Using mobile robots in disaster areas can reduce risks and the search time in urban search and rescue operations. Optimal path-planning for mobile robotics can play a key role in the reduction of the search time for rescuing victims. In order to minimize the search time, the shortest path to the target should be determined. In this paper, a new integrated Reinforcement Learning—based method is proposed to search and find a hidden target in an unknown environment in the minimum time. The proposed algorithm is developed in two main phases. Depending on whether or not the mobile robot receives the signal from the hidden target, phases I or II of the proposed algorithm can be carried out. Then, the proposed algorithm is implemented on an e-puck robot in an urban environment which is simulated within Webots software. Finally, to demonstrate the efficiency of the proposed method and to verify it, the computational results from the proposed method are compared with three conventional methods from the literature.

"Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions."

Afshar Mehrnoosh, Saeed Khodaygan

Journal Paper Structural Control and Health Monitoring 26.7 (2019): e2369

Abstract

Operational modal analysis based on power spectral density transmissibility (PSDT) functions is a useful tool to identify the modal parameters with low sensitivity to excitations. For pole extraction from the PSDT function, a proper parametric identification method such as the polyreference least squares complex frequency-domain method or poly-Max method can be used. Then, the poles are selected from a stabilization diagram (SD) with overestimating the system model order. Therefore, spurious modes can be identified that must be distinguished and removed from the system poles. To reach this aim, many techniques have been proposed and applied. In this paper, a new algorithm is proposed to enhance the performance of the SD for automated modal parameter identification based on the PSDT. The algorithm is composed of two main phases. In the first phase, the spurious modes are discriminated from the system poles on the basis of the conventional and supplementary stability criteria. On spurious mode omission, two new criteria named “pole criterion” and “coherence criterion” are introduced and applied as the supplementary stability criteria to make a more clear SD. Then, the extracted poles are categorized in the distinct clusters through a new strategy for comparing modes. In the second phase, a novel multiscreening algorithm is implemented for the automated identification of the system poles. Accordingly, the searching and averaging processes are followed between clusters, and the poles are screened to automatically identify the system poles on the basis of the numbers of their repetition in the SD via k-means clustering algorithms. Also, to improve the accuracy of the identification, the Hilbert transform is used in the construction of the PSDT functions. Finally, to validate and demonstrate the efficiency of the proposed method, a computer simulation and an experiential case study are considered.

"Modal Parameter Identification of Rotary Systems Based on Power Spectral Density Transmissibility Functions."

S. Khodaygan

Journal Paper No. 2019-01-5007. SAE Technical Paper, 2019.‏

Abstract

Operational modal analysis based on power spectral density transmissibility functions (PSDT) is a powerful tool to identify the modal parameters with low sensitivity to excitations. The rotor systems may have the asymmetric damping or stiffness matrices which can lead to increase the difficulties of the identification procedure. In this paper, a new method is proposed to identify the modal parameters of the asymmetric rotary systems by the operational modal analysis based on the power spectral density transmissibility functions. For pole extraction from the PSDT function, a proper parametric identification method such as the Poly-reference Least Squares Complex Frequency-domain method (PLSCF) or poly-Max method can be used. Then, the rotary system poles can be identified from a Stabilization Diagram (SD) with overestimating the system model order. The proposed algorithm is validated by a computer simulation.

"A multiple objective framework for optimal asymmetric tolerance synthesis of mechanical assemblies with degrading components."

S. Khodaygan

Journal Paper The International Journal of Advanced Manufacturing Technology 100.9 (2019): 2177-2205.‏

Abstract

In order to produce the mechanical assemblies with the high quality, the finest functionality, and the low cost, the optimal tolerance synthesis can be a useful tool in the design stage. The degradation of components due to some operational or environmental factors (such as the thermal cycling, the mechanical deformation, and the wear) can lead to dimensional variations in components and fall-off of the functionality of the product. In addition, different manners of the degradation on the internal and external dimensions can cause asymmetric deviations in the dimensions. On the other hand, the effect of degradation on the product quality has not been considered in most researches. In this paper, a new multi-objective framework is proposed for optimal asymmetric tolerance synthesis of mechanical assemblies with degrading components. In this method, the optimal tolerances are allocated based on ensuring the fulfillment of the product’s functional requirements, maximizing the product quality, and minimizing the total cost over the lifetime of the product. To incorporate the degradation effect into the loss function concept, the present worth of the expected quality loss (PWL) is formulated in terms of asymmetric tolerances. Accordingly, the functional process capability and manufacturing cost are developed based on asymmetric tolerances and the degradation effects. In order to extract Pareto fronts of optimal solutions, the elitist Non-dominated Sorting Genetic Algorithm II as an evolutionary generating methodology is utilized. In solving multi-criteria tolerance synthesis problem by a generating method, selecting the best tolerances from the obtained optimal Pareto solutions is a significant challenge. In this paper, to find the best asymmetric tolerances from Pareto solutions, a combined Shannon’s entropy-based TOPSIS algorithm is used. Finally, a bi-directional non-back drivable roller clutch assembly as an industrial case study is considered to illustrate the efficiency of the proposed method, and the obtained results are compared and discussed for verification.

"A framework for multi-objective optimisation of 3D part-build orientation with a desired angular resolution in additive manufacturing processes."

Golmohammadi A.H., S. Khodaygan

Journal Paper Virtual and Physical Prototyping 14.1 (2019): 19-36.‏‏

Abstract

In additive manufacturing processes, the part build orientation (PBO) is one of the most important factors that can affect the characteristics of the quality product such as the amount of support structure and the surface roughness. In most previous methods, the optimal PBO cannot be determined with high precision and accuracy in 3D space. In this paper, to find the precise and accurate optimal PBO with a desired angular accuracy, a new Taguchi-based method, called the Zooming-Taguchi method, is proposed. The proposed simulation-based method can precisely find the optimal PBO in absence of the noise effects. In order to find the optimal PBO with the desired angular resolution, the zooming procedure is iteratively carried out on factor levels through a clustering strategy. Finally, to validate the proposed method, two case studies are considered and the obtained results are compared with conventional methods in the literature and the experimental results.

"An efficient scanning algorithm for improving accuracy based on minimising part warping in selected laser sintering process."

Manshoori Yeganeh, A., M. R. Movahhedy, S. Khodaygan

Journal Paper Virtual and Physical Prototyping 14.1 (2019): 59-78.‏‏

Abstract

In the selective laser sintering (SLS) method, layers of powder are scanned by a laser beam and sintered. The thermal gradients created by laser heating and the subsequent cooling of the sintered sections results in thermal stresses and part warping in the final part. Thermal gradients are dependent on the scanning algorithm, in particular, the scan vector length. In this work, an efficient scanning algorithm for the SLS process is presented with the aim to minimise the part warping in the final part due to thermally induced residual stresses, while maintaining the production time at a minimum. The proposed algorithm is implemented in a finite element simulation and scanning parameters including the number of offsets and scanning length are optimised at constant laser parameters and chamber conditions. The FE model is verified by testing a few samples on SLS machine and comparing the parts made by the proposed algorithm with those made using conventional scan algorithm is the same as parallel-line scan algorithm. It is shown that part warping in the parts made by the proposed algorithm is reduced by up to 35% while the production time, part accuracy and surface properties are improved.

"Meta-model based multi-objective optimisation method for computer-aided tolerance design of compliant assemblies."

S. Khodaygan

Journal Paper International Journal of Computer Integrated Manufacturing 32.1 (2019): 27-42.‏‏

Abstract

Optimal tolerance design is a time-consuming and multi-disciplinary procedure and involves several aspects of design, manufacturing, quality and cost problems. In addition, the quality of assemblies can be significantly affected by the flexibility of components which has not been considered in most of the previous research. In this paper, a new method is proposed for multi-objective optimal tolerance design of compliant assemblies based on an integrated Kriging meta-modelling – NSGA-II – Shannon’s Entropy TOPSIS algorithm. The tolerance propagation of flexible components in the assembly process is modelled through the enhanced Method of Influence Coefficients (MIC). Geometrical variations of key characteristics are estimated through a Kriging model on the data generated from the enhanced MIC based on the finite element method. The overall manufacturing cost is minimised, while the geometric capability ratio (GCR), as a quality criterion, is maximised. To find the Pareto optimal front (POF), NSGA-II is applied. For ranking best alternatives of the POF based on multiple criteria, an improved Shannon’s Entropy-based TOPSIS is used. Finally, to verify and demonstrate the efficiency of the proposed method, a case study is considered with the results compared with Monte Carlo simulations and a conventional tolerance allocation method from the literature.

"An interactive method for computer-aided optimal process tolerance design based on automated decision making."

S. Khodaygan

Journal Paper International Journal on Interactive Design and Manufacturing (IJIDeM) 13.1 (2019): 349-364.‏

Abstract

Interactive and integrated design and manufacturing can be a useful strategy for designers to reach the efficient design through the cognitive or physical interactions. Process tolerance design is a key tool in the integrated design and manufacturing to reach a product with high quality and low cost. Since the optimal tolerance allocation involves several aspects of the design, manufacturing and quality issues, it is always a time consuming and difficult procedure, especially for complex products. Therefore, to overcome these difficulties, a computer-aided approach for optimal tolerance design of manufacturing process is needed in the design stage. In this paper, a novel interactive framework is introduced for computer-aided multi-objective optimal process tolerance design established upon entropy-based decision making. According to the proposed method, the optimal process tolerances of components are allocated through a multi-objective optimization problem where the process capability function and the overall manufacturing cost should be simultaneously optimized. To model the proper objective functions, the new formulations of process capability and manufacturing cost functions are proposed based on the design and customer’s requirements on the virtual model in CAD software, and the experimental observations, respectively. The non-dominated sorting genetic algorithm II is used for solving the multi-criteria optimization. For automated decision making to find the best process tolerances from the optimal Pareto solutions without objective weighting, an improved entropy-based TOPSIS is used. Based on the obtained optimal process tolerances and specifications, the process planning procedure can be carried out. Finally, to illustrate the capability of the proposed method and to validate it, a windmill transmission assembly as a case study is considered and the computational results are compared and discussed.

"Modal Parameter Identification of Rotary Systems Based on Power Spectral Density Transmissibility Functions."

S. Khodaygan

Journal Paper No. 2018-01-1107. SAE Technical Paper, 2018.‏

Abstract

Operational modal analysis based on power spectral density transmissibility functions (PSDT) is a powerful tool to identify the modal parameters with low sensitivity to excitations. The rotor systems may have the asymmetric damping or stiffness matrices which can lead to increase the difficulties of the identification procedure. In this paper, a new method is proposed to identify the modal parameters of the asymmetric rotary systems by the operational modal analysis based on the power spectral density transmissibility functions. For pole extraction from the PSDT function, a proper parametric identification method such as the Poly-reference Least Squares Complex Frequency-domain method (PLSCF) or poly-Max method can be used. Then, the rotary system poles can be identified from a Stabilization Diagram (SD) with overestimating the system model order. The proposed algorithm is validated by a computer simulation.

"A framework for tolerance design considering systematic and random uncertainties due to operating conditions."

S. Khodaygan

Journal Paper Assembly Automation, 39.5 (2018): 854-871. https://doi.org/10.1108/AA-10-2018-0160

Abstract

Purpose – The main aim of this paper is to present a novel Kriging meta‐model assisted method for multiobjective optimal tolerance design of the mechanical assemblies based on the operating conditions under both systematic and random uncertainties. Design/methodology/approach – In the proposed method, the performance, the quality loss, and the manufacturing cost issues are formulated as the main criteria in terms of systematic and random uncertainties. In order to investigate the mechanical assembly under the operating conditions, the behavior of the assembly can be simulated based on the finite element analysis (FEA). The objective functions in terms of uncertainties at the operating conditions can be modeled through the Kriging-based metamodeling based on the obtained results from the FEA simulations. Then, the optimal tolerance allocation procedure is formulated as a multi-objective optimization framework. For solving the multi conflicting objectives optimization problem, the Multi-Objective Particle Swarm Optimization (MOPSO) method is used. Then, a Shannon‘s Entropy-based TOPSIS is utilized for selection of the best tolerances from the optimal Pareto solutions. Findings – The proposed method can be used for optimal tolerance design of mechanical assemblies in the operating conditions with including both random and systematic uncertainties. In order to reach an accurate model of the design function at the operating conditions, the Kriging meta-modeling is utilized. The efficiency of the proposed method by considering a case study is illustrated and the method is verified by comparison to a conventional tolerance allocation method. The obtained results show that using the proposed method can lead to the product with a more robust efficiency in the performance and a higher quality in comparing to the conventional results. Research limitations/implications – The proposed method is limited to the dimensional tolerances of components with the normal distribution. Practical implications – The proposed method is practically easy to be automated for computer-aided tolerance design in industrial applications. Originality/value – In conventional approaches, regardless of systematic and random uncertainties due to operating conditions, tolerances are allocated based on the assembly conditions. Since uncertainties can significantly affect the system’s performance at operating conditions, tolerance allocation without including these effects may be inefficient. This paper aims to fill this gap in the literature by considering both systematic and random uncertainties for multi-objective optimal tolerance design of mechanical assemblies under operating conditions.

"A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process."

S. Khodaygan

Journal Paper The International Journal of Advanced Manufacturing Technology 94.9 (2018): 3963-3978

Abstract

Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations.

"Multi-criteria optimization of the part build orientation (PBO) through a combined meta-modeling/NSGAII/TOPSIS method for additive manufacturing processes."

Khodaygan S., A.H. Golmohammadi

Journal Paper International Journal on Interactive Design and Manufacturing (IJIDeM) 12.3 (2018): 1071-1085.‏‏‏

Abstract

Additive manufacturing (AM), is a new technology for the manufacturing of the physical parts through an additive manner. In the AM process, the orientation pattern of the part is an important variable that significantly influences the product properties such as the build time, the surface roughness, the mechanical strength, the wrinkling, and the amount of support material. The build time and the surface roughness are the more important criteria than others that can be considered to find the optimum orientation of parts. The designers and manufacturing engineers usually attempt to find an optimum solution to reach the product with high quality at the minimum time. Determining the optimum build orientation of the virtual model in the design stage for the additive manufacturing to reach a real production with higher quality at the lower time can be an effective strategy to success in the competitive environment of manufacturing firms. In this paper, a new combined meta-modeling/NSGA II/TOPSIS approach is introduced to search the accurate optimum PBO in the AM based on the multi-criteria optimization formulation. In order to reach this aim, first, a new formulation is proposed to model the build time with respect to the PBO in AM processes. Then, a proper formulation is developed to estimate the mean surface roughness based on the part orientations. By utilizing Kriging method as a powerful meta-modeling approach, the build time and the surface roughness as the objective functions are modeled in the explicit form in terms of the part orientation. Then, the non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-criteria optimization problem with the build time and the surface roughness as the objective functions. Consequently, Pareto-optimum solutions are obtained from the optimization problem-solving. The TOPSIS method is employed to rank all obtained optimum solutions for selecting the best solution. The proposed approach aims to precisely find the optimum PBO for the several AM processes under the low computational time. Finally, to illustrate and validate the efficiency and accuracy of the proposed approach two case studies are considered and the obtained results are compared and discussed.

"Prediction of machining chatter in milling based on dynamic FEM simulations of chip formation."

S. Khodaygan

Journal Paper Advances in Manufacturing 6.3 (2018): 334-344.‏

Abstract

Chatter vibration is a major obstacle in achieveing increased machining performance. In this research, a finite element model of chip formation in a 2D milling process is used to predict the occurrence of chatter vibrations, and to investigate the effects of various machining parameters on this phenomenon. The dynamic properties of the machine tool at the tool tip are obtained based on experimental modal analysis, and are used in the model as the cutter dynamics. The model allows for the natural development of vibration as the result of the chip-tool engagement, and accounts for various phenomena that occur at the chip-tool interface ultimately leading to stable or unstable cutting. The model was used to demonstrate the effects of the machining parameters, such as the axial depth of cut, radial immersion, and feed rate, on the occurrence of chatter. Additionally, the phenomenon of jumping out of the cut region could be observed in this model and its effect on the chatter process is demonstrated. The numerical model is verified based on comparisons with experimental results.

"Optimized thermal gradient by changing temperature parameters for laser-assisted additive manufacturing process based on polyamide-12 powder using numerical model."

Manshoori Yeganeh Ahmad, Mohammad Reza Movahhedy, Saeed Khodaygan

Journal Paper Iranian Journal of Manufacturing Engineering 5.4 (2019): 26-36.‏‏‏

Abstract

The laser-assisted additive manufacturing based on the powder is an efficient layer manufacturing process that uses a high-energy laser for the fabrication of polymeric components. The thermal stresses of the laser arise from the thermal gradients generated by the laser and other parameters of the device. Reducing thermal gradients decreases the deformations in the part and increases the fabrication accuracy. The main aim of this paper is to determine the temperature parameters including the preheating temperature or the powder bed temperature, the ambient temperature, scanning power and spot diameter in such a way that the temperature gradient is minimized. The finite element modeling is performed for the selective laser sintering process for polyamide-12 powder. In this paper, thermal gradient by changing temperature parameters based on the temperature model of the finite element and Taguchi experimental design is optimized. In order to reach this aim, the finite element simulation of the selective laser sintering process is first carried out for polyamide-12 powder. In order to verify the simulations, the experimental test is performed by a selective laser sintering device and the obtained results are compared with the finite element model. Then, using the Taguchi method, experiments are designed at the different levels and optimal temperature parameters are obtained. According to obtained results, optimal parameters were obtained to minimize thermal gradients at 451K preheat temperatures, 359K ambient temperature, 10W laser power, and 0.5mm spot diameter.

"A new approach for the reliability-based robust design optimization of mechanical systems under the uncertain conditions."

S. Khodaygan, M. H. Sharafi

Journal Paper No. 2018-01-0615. SAE Technical Paper, 2018.‏

Abstract

A mechanical system inherently affected by the conditions, factors, and parameters of uncertainties. Without including the uncertainty effects in the design procedure, the designs may not be robust and reliable. Robust design optimization (RDO) method is a procedure to find the insensitive design with respect to the variations. On the other hand, reliability is measured by the probability of satisfying a specific design criterion. Therefore, a reliable design is a design that satisfies the specified criteria even with some uncertainties in variables and parameters. Reliability-based design optimization (RBDO) is an optimization procedure that incorporates reliability requirements to find the proper design. Since RDO and RBDO are usually the expensive computational approaches, the Reliability-Based Robust Design Optimization (RBRDO) may be difficult to apply. In this paper, a new model for the reliability based robust design optimization is introduced. First, two new factors that are called “chance - penalty function” and “reliability multiplier” are introduced. Based on these new factors, the optimality, the robustness, and the reliability functions as three objective functions are modeled. Then, a combined model for the RBRDO of the mechanical systems under the uncertain conditions is proposed. Finally, the application of the proposed method is demonstrated through the design of two case studies under uncertain conditions, and the computational results are compared to the obtained results from classical methods.

"A new method for reconstructing the inner profile of the pipe for inspection with the laser-based measuring pig."

Hadavand Majid, Khodaygan Saeed , Mohammad Sobhan Esfandiar

Journal Paper Modares Mechanical Engineering 18.6 (2018): 132-138.‏‏‏‏

Abstract

Along with improvement of technology and need for access to energy resources, existence of pipelines such as gas, oil and water pipes is vital for our lives. These pipes will be eroded and damaged over time. With the prediction of the defects and tracking of pipeline paths, the probability of sudden damages is greatly reduced. In this paper, at first various non-destructive methods of monitoring the pipelines are investigated and it is shown that the laser method is the most comprehensive and non-destructive inspection method and then the background of the chosen method is examined. Also, the hardware aspect of the system and the proper layout of the laser sensors are determined on the system. After that a complete mathematical model and an algorithm is proposed for it which can be used to analyze the data obtained from the simulation of laser sampling creates image of the pipe internal surface and using this method identifies the defects found at the pipe surface. In the fourth section, a pipe with specific geometric deflection is examined based on the proposed method and algorithm and its results show the correctness of the proposed method.

"Multi-Objective Optimal Tolerance Allocation of the Mechanical Systems under the Thermal Gradients"

Khodaygan S., J. Hemati-Nik

Journal Paper No. 2018-01-1031. SAE Technical Paper, 2018.‏‏‏‏‏

Abstract

Tolerance allocation is a key tool to reach a product with the minimum cost and the maximum performance. Since the thermal effects can cause the dimensional and geometrical variations in the components of mechanical assemblies, the tolerance allocation may be inefficient in the optimal tolerance design at the nominal conditions without including the thermal impacts. In this paper, a new optimal tolerance design of mechanical assemblies with the thermal effects is proposed. According to the proposed method, the tolerance allocation procedure is modeled as a multi-objective optimization problem. The functional objective, the manufacturing cost, and the quality loss function are considered as the corresponding objectives multi-objective optimal tolerance design problem. Using the computational results from the finite element simulations and based on the Artificial Neural Network (ANN) method, the design function as functional objective can be modeled. The optimal tolerance design problem in a multi-objective optimization form can be solved using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The Pareto optimal front (POF) of the proposed multi-objective optimization problem can be obtained. Finally, to illustrate the efficiency of the proposed method and to verify it, a case study under various temperature conditions is considered and computational results are compared and discussed.

"Comparison of analytical and experiment design-based optimization methods to determine the optimum part build orientation in rapid prototyping processes."

Khodaygan S., J. Hemati-Nik

Journal Paper Modares Mechanical Engineering 18.3 (2018): 115-125.‏‏‏‏‏‏

Abstract

In the rapid prototyping process, the orientation pattern of the part is one of the most important factors that significantly affect the product properties such as the build time, the surface roughness, the mechanical strength, and the amount of support material. The build time and the surface roughness are the more imperative criteria than others that can be considered to find the optimum orientation of parts. In this paper, two algorithms based on analytical and empirical optimization methods are presented to determine optimum part build orientation in order to minimize build time and surface roughness. To implement this method, the user's part is received in standard triangle language (STL) format. Then, using the geometric characteristics and type of part orientation, the build time and the average of surface roughness is calculated. In order to determine the optimum part build orientation, two analytical (NSGA-II method) and experimental (new and developed Taguchi method) optimization methods have been used. After introducing the steps of these two methods, in order to determine optimum part build orientation, the steps of these two proposed algorithms are implemented on a part as a case study and obtained results are compared and discussed. The results for the proposed part show that optimal orientation from both optimization algorithms is acceptable. also the computational cost of the experimental optimization method is far less than the analytical method.

"A new method for reconstructing the inner profile of the pipe for inspection with the laser-based measuring pig."

Hadavand Majid, Khodaygan Saeed , Mohammad Sobhan Esfandiar

Journal Paper Modares Mechanical Engineering 18.6 (2018): 132-138.‏‏‏‏

Abstract

Along with improvement of technology and need for access to energy resources, existence of pipelines such as gas, oil and water pipes is vital for our lives. These pipes will be eroded and damaged over time. With the prediction of the defects and tracking of pipeline paths, the probability of sudden damages is greatly reduced. In this paper, at first various non-destructive methods of monitoring the pipelines are investigated and it is shown that the laser method is the most comprehensive and non-destructive inspection method and then the background of the chosen method is examined. Also, the hardware aspect of the system and the proper layout of the laser sensors are determined on the system. After that a complete mathematical model and an algorithm is proposed for it which can be used to analyze the data obtained from the simulation of laser sampling creates image of the pipe internal surface and using this method identifies the defects found at the pipe surface. In the fourth section, a pipe with specific geometric deflection is examined based on the proposed method and algorithm and its results show the correctness of the proposed method.

"Determination of optimal parameters in selective laser sintering for minimizing the part warping based on Taguchi method."

Manshoori Yeganeh Ahmad, Saeed Khodaygan , Mohammad Reza Movahedy

Journal Paper Modares Mechanical Engineering 17.12 (2018): 157-166.‏

Abstract

Additive Manufacturing (AM) or 3D printing is a method to build parts by adding layer-upon-layer of material. The selective laser sintering (SLS) method is one of the most important methods of additive manufacturing processes. The low time and the variety of materials used to build the parts are major advantages of SLS method. The high quality of the product is one of the main goals in the additive manufacturing processes. The part warping is one of the factors that reduce the quality of the products which are built by the SLS process. The hatching patterns and scan algorithms in the SLS process are important factors that affect the product quality. In this paper, the effective parameters of the SLS processes such as the scan vector length and the number of offsets or contours, the laser power, the laser speed, and the hitching spacing are optimally determined to minimize the part warping of the product based on the finite element simulations and Taguchi method. For this reason, SLS process has been modeled on the SLS process. Then, to illustrate and validate the accuracy and efficiency of the proposed method, and the computational results are compared to the obtained results from the experimental tests Using SLS containing CO2 laser. Finally, using the Taguchi design of Experiments, the process parameters have been changed at different levels and optimal parameters have been obtained.

"An uncertainty analysis method for error reduction in end-effector of spatial robots with joint clearances and link dimension deviations."

Hafezipour M., S. Khodaygan

Journal Paper International Journal of Computer Integrated Manufacturing 30.6 (2017): 653-663.‏‏

Abstract

The position accuracy of the robot end-effector is inherently affected by uncertainties. In order to design and manufacture robots with high accuracy, it is essential to know the effects of these uncertainties on the motion of robots. Uncertainty analysis is a useful method which can estimate deviations from desired path in robots caused by uncertainties. This paper presents an applied formulation for 3D statistical error analysis of open-loop mechanisms and robotic manipulators. In order to have an accurate analysis, uncertainty effects of both the link dimension deviation and the joint clearance in performance of the spatial open-loop mechanisms and the robots are considered. The maximum normal and parallel components of the position error on the end-effector path are introduced as error bands for all over range of motion. Furthermore, the percent contributions of manufacturing variables are estimated and the corresponding tolerance that has the most significant effects on the uncertainty zone of the end-effector position is determined. The proposed method is illustrated using a spatial manipulator with three revolute joints and verified with a Monte Carlo simulation method. The results of applying this method demonstrate that estimating the position error and its reduction in mechanisms and robots can be done efficiently and precisely.

"Static and dynamic tolerance analysis of flexible rotary systems based on the tolerance zone method."

Khodaygan Saeed, Hamed Fallahzadeh

Journal Paper Modares Mechanical Engineering 17.8 (2017): 143-152.‏ ‏‏

Abstract

Because of increasing demands for using of rotating systems in high accuracy and high speed applications, in addition of specific condition of rotating systems, it is necessary to analyze these rotating systems characteristics. Tolerance analysis is a useful tool for estimating effects of dimensional and geometrical errors of effective parameters on functional characteristics in a mechanical system. Unlike other mechanical systems, in addition to the dimensional and geometrical errors, the accuracy of the rotary systems performance directly depend on the flexibility of parts and Non Repetitive Run-Out (NRRO) errors. In this paper, a new method is proposed for static and dynamic tolerance analysis of the rotary systems with the dimensional and geometrical errors, the flexibility effects, and the NRRO errors based on the tolerance zone model. First, using the small degrees of freedom concept, the dimensional and geometrical errors and the NRRO error are modeled in the tolerance zone. Then, based on a new strategy, the performance -assembly functions of the system for modeling the error propagation of the rotary system in the static and dynamic conditions are extracted. Then, using the proposed equations, sensitivities of the requirements such as the end of shaft position and the main natural frequency to tolerances are computed. To illustrate applicability of the proposed method, a rotary system is considered as a case study. Monte Carlo simulations are used for validation of the computational results from proposed method.

"Build time estimation in additive manufacturing processes based on part orientations."

Golmohammadi Amir Hossein, Saeed Khodaygan

Journal Paper Modares Mechanical Engineering 17.8 (2017): 9-16.‏ ‏‏

Abstract

The orientation of part in the additive manufacturing process is one of the most important factors should be considered in the additive manufacturing process. In the additive manufacturing process, the part orientation factor can significantly affect the part properties such as the surface roughness, strength, the manufacturing time and amount of support materials. The manufacturing time is a key factor that can influence the total production cost. Therefore, to minimize the manufacturing time, the optimum orientation of parts should be determined. In this paper, a new method is introduced to estimate the built time of the parts through the additive manufacturing process. According to the proposed method, a practical equation is extracted to estimate the built time of the parts with related to the number of layers and amount of the support materials. The method is capable to estimate the built time of a part associated to the part orientations. The efficiency of the proposed method is demonstrated through a case study in two different type of orientation, and the computational results are compared with the obtained results from the simulations in MankatiUM V5.3 and Repetier-Host software. The average of proposed method relative error in the first type of orientation in comparison with MankatiUM and Repetier-Host software results are, respectively, 5 and 10 percent and for the second type of orientation are 7 and 8 percent. Moreover, calculation cost of proposed method is 140 and 100 times faster than MankatiUM and Repetier-Host software, respectively.

"A comprehensive fuzzy feature-based method for worst case and statistical tolerance analysis."

Khodaygan S., M. R. Movahhedy

Journal Paper International Journal of Computer Integrated Manufacturing 29.1 (2016): 42-63 ‏‏

Abstract

Tolerance analysis is an analytical tool for the estimation of accumulating effects of the individual part tolerances on the functional requirements of a mechanical assembly. This article presents a comprehensive feature-based method for tolerance analysis of mechanical assemblies with both dimensional and geometric tolerances. In this method, dimensional and geometric tolerance zones are described by the combination of fuzzy modelling and small degrees of freedom (SDOF) concept. In this model, the uncertainty in dimensions and geometric form of features is mathematically described using fuzzy modelling, and the kinematic effects of tolerances in assemblies are expressed by SDOF concept. In the proposed method, complicated GD&T concepts such as various material modifiers (maximum material condition, least material condition and regardless of feature size), envelope requirement, bonus tolerances and Rule No. 1 (Taylor principle) in several conditions are accurately modelled. Compatible with the proposed model, a procedure for modified worst case and statistical tolerance accumulation analysis is introduced. An algorithm is laid out that describes the steps and the procedure of tolerance analysis. The application of this method is demonstrated through an example, and the results are compared with experimental results.

"Capability Prediction of Machining Processes Based on Uncertainty Analysis."

Afrasiab, Hamed, Saeed Khodaygan

Journal Paper International Journal of Mechanical and Mechatronics Engineering 10.7 (2016): 1262-1269

Abstract

Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

"An Efficient Method for Workpiece Locating Error Prediction in Machining Process."

Khodaygan S.

Journal Paper No. 2016-01-1347. SAE Technical Paper, 2016.‏

Abstract

Fixtures play a key role in locating workpieces to manufacture high quality products within many processes of the product lifecycle. Inaccuracies in workpiece location lead to errors in position and orientation of machined features on the workpiece, and strongly affect the assemblability and the final quality of the product. The accurate positioning of workpiece on a fixture is influenced by rigid body displacements and rotations of the workpiece. In this paper, a systematic approach is introduced to investigate the located workpiece position errors. A new mathematical formulation of fixture locators modeling is proposed to establish the relationship between the workpiece position error and its sources. Based on the proposed method, the final locating errors of the workpiece can be accurately estimated by relating them to the specific dimensional and geometric errors or tolerances of the workpiece and the related locators. The proposed method is developed for error analysis based on worst case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the results of simulation of the case study in a CAD/CAM system.

"Statistical Tolerance Analysis of Flexible Assemblies with Contact Effects."

Khodaygan Saeed, Amir Ghasemali, Hamed Afrasiab

Journal Paper No. 2016-01-1380. SAE Technical Paper, 2016.‏

Abstract

One of the most important characteristics of industrial products, especially mechanical set-ups, is considering the tolerances of production and assembly of these set-ups, which directly influences the products’ operations. In sheet metal structures, due to the high flexibility of the sheets, the errors appeared while assembly will be as highly influential as the errors due to the production tolerance of the sheets. As a result, having a comprehensive model which could analyze the assembly process of these structures and also clarifies the relation between the tolerance of the parts and the ultimate changes of the set-up will be of considerable importance. During the assembly process, the contact effect between the components is inevitable. If such effect is not considered, the contact surfaces will permeate. The purpose of this paper is to present a method to analyze the tolerance of flexible sheet structures, considering the contact effect between surfaces. It is performed by the Method of Modified Influence Coefficients (MMIC) for calculating the outcome error appeared in the assembly set-up. To do so, the method has also been applicable for nonlinear contact problems by modifying the sensitivity matrix and proposing a statistical solution for the errors of the assembly setup. Finally the capabilities of the presented method have been investigated through analyzing an example of assembling two panels of an automobile body and the authenticity of the results has been validated by comparing with Monte Carlo simulation results.

"Tolerance analysis of flexible assemblies with contact effects based on modified influence coefficients method."

Khodaygan Saeed, Amir Ghasemali, Hamed Afrasiab

Journal Paper Modares Mechanical Engineering 15.13 (2016): 144-149.‏

Abstract

In sheet metal structures, due to high flexibility of the sheets, the dimensional and geometrical errors do considerably influence the assembly tolerances. On one hand, various stages of design, manufacturing and assembly of mechanical sets are involved in various factors such as dimensional, geometrical and material uncertainties. As a result, presenting a comprehensive model based on which propagation of the changes resulted from the uncertainties of the manufacturing processes and their relations with assembly tolerances could be approximated with a high accuracy seems necessary. In normal influence coefficients method, neglecting the contact effects between the components not only causes the diffusion of contact surfaces, but also leads to errors in predicting assembly tolerances. In this paper, an applicative method for tolerance analysis of flexible sheet structures and precise prediction of abundant errors in assembly characteristics is presented by modifying the influence coefficients method and by considering the effects of components’ contacts using finite element method (FEM). To do so, a proper strategy based on modeling and the analysis of effective uncertainties in the process of the assembly of the sets with flexible components has been proposed. At the end, the capabilities of the proposed method are investigated by presenting an example and the accuracy of the obtained results has been compared with Monte Carlo and experimental results.

"Error reduction in spatial robots based on the statistical uncertainty analysis."

Khodaygan S., M. Hafezipour

Journal Paper SAE International Journal of Materials and Manufacturing 8.2 (2015): 263-270.‏

Abstract

Kinematic accuracy of the robot end-effector is decreased by many uncertainties. In order to design and manufacture robots with high accuracy, it is essential to know the effects of these uncertainties on the motion of robots. Uncertainty analysis is a useful method which can estimate deviations from desired path in robots caused by uncertainties. This paper presents an applied formulation based on Direct Linearization Method (DLM), for 3D statistical uncertainty analysis of open- loop mechanisms and robots. The maximum normal and parallel components of the position error on the end-effector path are introduced. In this paper, uncertainty effects of both linear and angular variations in performance of spatial open-loop mechanisms and robots are considered. Based on the relations for the percent contributions of manufacturing variables, for the position error reduction, the tolerances that have the most significant effects on the commutated uncertainty zone of the end-effector position can be modified. The proposed method is illustrated using a spatial manipulator with three-revolute joints and verified with a Monte Carlo simulation method. Finally, normal and parallel distances to end-effector path are determined as error bands for all over range of motion. The results of applying this method demonstrate that estimating the position error in mechanisms and robots can be done efficiently and precisely.

"Manufacturing error compensation based on cutting tool location correction in machining processes."

Khodaygan Saeed

Journal Paper International Journal of Computer Integrated Manufacturing 27.11 (2014): 969-978.‏

Abstract

Inaccuracies in workpiece location lead to errors in position and orientation of machined features on the workpiece, and strongly affect the assemblability and the quality of the product. The accurate positioning of workpiece on a fixture is influenced by rigid body displacements and rotations of the workpiece due to several errors (e.g. geometric radial and position errors in locators and manufacturing tolerances of the workpiece). In this paper, an efficient approach is introduced for analysis and compensation errors in the workpiece–fixture–cutting tool system. A new mathematical formulation of workpiece–fixture modelling is proposed to establish the relationship between the locating errors and their sources. Based on the proposed method, the locating errors of the workpiece can be accurately estimated by relating them to the specific geometric errors or tolerances of the workpiece and the related locators. Then, to eliminate the effects of the locating errors and the cutting tool wear on the machined features, the location and orientation of the cutting tool in the cutter location data are corrected. The proposed method is proper for error analysis and compensation based on worst case analysis approach. The application of the presented method is illustrated through presenting an example and the computational results are compared to the results of simulation of the case study in a computer aided design and manufacturing (CAD/CAM) system.

"Robust Tolerance Design of Mechanical Assemblies Using a Multi-Objective Optimization Formulation."

Khodaygan S., M.R. Movahhedy.

Journal Paper No. 2014-01-0378. SAE Technical Paper, 2014.‏‏

Abstract

The design process always has some known or unknown uncertainties in the design variables and parameters. The aim of robust design is minimization of performance sensitivity to uncertainties. Tolerance allocation process can significantly affect quality and robustness of the product. In this paper, a methodology to minimize a product's sensitivity to uncertainties by allocating manufacturing tolerances is presented. The robust tolerance design problem is formulated as a multi-objective optimization based on the combined function-uncertainty-cost model. Genetic algorithm is utilized to solve the multi-objective optimization and a case study is presented to illustrate the methodology.

"A method for locator errors compensation in the fixture-workpiece system."

Khodaygan S., M.R. Movahhedy.

Journal Paper SAE International Journal of Materials and Manufacturing 6.3 (2013): 494-501.‏

Abstract

Inaccuracies in workpiece location lead to errors in position and orientation of machined features on the workpiece, and strongly affect the assemblability and the final quality of the product. The accurate positioning of workpiece on a fixture is influenced by rigid body displacements and rotations of the workpiece due to locator errors. In this paper, a new mathematical modeling of a fixture - workpiece system is proposed to establish the relationship between the workpiece location error and its sources. For the purpose of eliminating the locator errors of the fixtured workpiece, the resultant errors due to several sources are modeled in the locator error. Then the displacement and rotation errors of the located workpiece can be compensated by adjusting the length of locators. The proposed method is proper for error analysis based on both worst case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the simulation results of the case study in a CAD system.

"Fuzzy-based analysis of process capability for assembly quality assessment in mechanical assemblies."

Khodaygan S., M.R. Movahhedy.

Journal Paper International journal of production research 50.12 (2012): 3395-3415.‏

Abstract

Process capability indices are useful tools for evaluating the ability of a process to produce products that meet certain specifications. The assembly quality is dependent on the distribution of variations of assembly dimensions, which is in turn dependent on mating conditions in the mechanical assembly. Since it is often difficult to measure the assembly dimensions in the production stages, they are not considered as a direct inspection objective. Rather, the inspection and evaluation of quality is carried out by specifying whether the assembly requirements satisfy the specified limits. Therefore, we can basethe process capability indices on the assembly dimensions. In most real life cases, the observations are fuzzy. In this paper, a novel method based on fuzzy concepts for process capability analysis of assembly dimensions in mechanical assemblies is presented. According to this scheme, sample observations of manufactured variables are described as fuzzy numbers. The proposed method is able to estimate the ability of the manufacturing process in satisfying the assembly quality in the mechanical assemblies with asymmetric tolerances which have non-normal distributions. In this paper, a proper criterion based on the probability of fuzzy set to interpret the computed fuzzy results is proposed, so these results are converted to the interpretable results for making a decision to evaluate the assembly quality. Furthermore, a new fuzzy-based quantity factor for expressing the percent contributions of effective manufacturing variables on the assembly quality is presented. The application of the presented method is demonstrated through an example and its results are discussed.

"Fuzzy-small degrees of freedom representation of linear and angular variations in mechanical assemblies for tolerance analysis and allocation."

Khodaygan S., M. R. Movahhedy, M. Saadat Foumani

Journal Paper Mechanism and Machine Theory 46.4 (2011): 558-573.‏

Abstract

Tolerances naturally generate an uncertain environment for design and manufacturing. In this paper, a novel fuzzy based tolerance representation approach for modeling the variations of geometric features due to dimensional tolerances is presented. The two concepts of fuzzy theory and small degrees of freedom are combined to introduce the fuzzy-small degrees of freedom model (F-SDOF). This model is suitable for tolerance analysis of mechanical assemblies with linear and angular tolerances. Based on the fuzzy concept, a new index (called the assemblability index) is introduced which signifies the fitting quality of parts in the assembly. Graphical and numerical representations of tolerance allocation by this method are presented. The goal of tolerance allocation is to adjust the tolerances assigned at the design stage so as to meet a functional requirement at the assembly stage. The presented method is compatible with the current dimensioning and tolerancing standards. The application of the proposed methodology is illustrated through presenting an example problem.

"Tolerance analysis of assemblies with asymmetric tolerances by unified uncertainty–accumulation model based on fuzzy logic."

Khodaygan S., M.R. Movahhedy.

Journal Paper The International Journal of Advanced Manufacturing Technology 53.5-8 (2011): 777-788.‏‏

Abstract

In mechanical assemblies, individual components are placed together to deliver a certain function. The performance, quality, and cost of the mechanical assembly are significantly affected by its tolerances. Toleranced dimensions inherently generate an uncertain environment in a mechanical assembly. This paper presents a proper method for tolerance analysis of mechanical assemblies with asymmetric tolerances based on an uncertainty model. This mathematical approach is based on fuzzy logic and tolerance accumulation models such as worst-case and root-sum-square methods. A fuzzy-based tolerance representation is developed to model uncertainty of tolerance components in the mechanical assemblies. According to this scheme, toleranced components are described as fuzzy numbers with their membership functions constructed using the statistical distributions of manufactured variables. In this way, the uncertainty of assembly requirements and accumulation of tolerances are represented in the form of fuzzy number. In this paper, a new factor, the fuzzy factor, is introduced that helps converting the membership functions into fuzzy intervals that can be used for modal interval analysis. Equations for estimation of percent contributions of individual tolerances are introduced in terms of uncertainty parameter. These equations yield percent contributions of upper and lower bounds of independent variables (manufactured dimensions) on the upper and lower bounds of dependent variables (assembly dimensions). The proposed method is applied to an example, and its results are discussed.

"Predicting Fitting Quality of Mechanical Assemblies Through Statistical-Based Process Capability Analysis."

Khodaygan S., M.R. Movahhedy.

Journal Paper No. 2011-01-0466. SAE Technical Paper, 2011.‏

Abstract

The process capability indices are widely used to measure the capability of the process to manufacture objects within the required tolerance. Fit quality is mainly dominated by the distribution of fit dimensions, i.e., a gap dimension. As the fit dimensions are very difficult to be measured in mass production, they are not to be considered as a direct inspection objective. The quality inspection and evaluation relative to fit quality are focused on whether the processes of assembly requirements are conformed with their specification limits respectively. Fit quality specification can be indicated by the process capability indices of mating parts. In this paper, the statistical-based process capability analysis method is presented to estimate ability of manufacturing process for considering of assembly requirements and fit quality in a mechanical assembly with asymmetric tolerances. According to this scheme, toleranced components are described as the statistical distributions of manufactured variables. In this paper a quantity factor to consider the contribution effects of variables that reduce the assembly process capability is introduced. The application of this method is demonstrated through an example and its results are discussed.

"Tolerance analysis of mechanical assemblies based on modal interval and small degrees of freedom (MI-SDOF) concepts."

Khodaygan S., M.R. Movahhedy, M. Saadat Fomani

Journal Paper The International Journal of Advanced Manufacturing Technology 50.9-12 (2010): 1041-1061.‏

Abstract

Tolerance analysis is a key analytical tool for estimation of accumulating effects of the individual part tolerances on the design specifications of a mechanical assembly. This paper presents a new feature-based approach to tolerance analysis for mechanical assemblies with geometrical and dimensional tolerances. In this approach, geometrical and dimensional tolerances are expressed by small degrees of freedom (SDOF) of geometric entities (faces, feature axes, edges, and features of size) that are described by tolerance zones. The uncertainty of dimensions and geometrical form of features due to tolerances is mathematically described using modal interval arithmetic. The two concepts of modal interval analysis and SDOF are combined to describe the tolerance specifications. The algorithm is presented which explains the steps and the procedure of tolerance analysis. The proposed method is compatible with the current GD&T standards and can incorporate GD&T concepts such as various material modifiers (maximum material condition, least material condition, and regardless of feature size), envelope requirement, and bonus tolerances. This method can take into account multidimensional effects due to geometrical tolerances in tolerance analysis. The application of the proposed method is illustrated through presenting an example problem and comparing results with tolerance charting method.

"Tolerance analysis of mechanical assemblies based on modal interval and small degrees of freedom (MI-SDOF) concepts."

Movahhedy Mohammad R.,Saeed Khodaygan

Journal Paper SAE Transactions (2007): 44-52.‏

Abstract

This paper presents modified relations for worst-case and root-sum-square (RSS) tolerance accumulation models for tolerance analysis of mechanical assemblies with asymmetric tolerances. The common models do not consider the sign of the sensitivity factors and thus are applicable to symmetric tolerances only. Using the new models, the accumulation of asymmetric tolerances results in asymmetric assembly tolerances. New relationships for estimation of percent contributions of individual tolerances are also introduced which yield percent contributions of upper and lower bounds of independent variables (manufacturing dimensions) on the upper and lower bounds of dependent variables (assembly dimensions). The modified methods and new relations are applied to linear and nonlinear examples and their results are discussed.

"Comparison of PCA and t-SNE in order to efficiency of clustering Polymer additive manufacturing processes through K-Means"

Mosavi, S. Morteza, , S. Khodaygan

Conference Paper The 19th National Conference and 8th International Conference on Manufacturing Engineering, Ferdowsi University of Mashhad on March 9-10, 2023.

Abstract

Comparison of PCA and t-SNE in order to efficiency of clustering Polymer additive manufacturing processes through K-Means compared and discussed.

A Framework for Learning Dynamic Movement Primitives with Deep Reinforcement Learning,

Noohian Amir Hossein, Raeisi Mehran, Khodaygan Saeed

Conference Paper Proceedings of the 10th RSI International Conference on Robotics and Mechatronics (ICRoM 2022), Nov. 15-18, 2022, Tehran, Iran.

Abstract

Dynamic movement primitives (DMPs) are a learning from demonstration (LfD) method that imitates movement primitives. Recently, reinforcement learning (RL) has been used to modify DMPs. In this regard, most methods have concentrated on improving DMPs with RL after DMPs are learned with supervised learning. In this way, there is no guarantee that the DMPs stay close to demonstrations while modified. To address this problem, in this study, a framework is proposed for learning DMPs with deep RL, which can be further used to modify DMPs. To do so, first, DMPs are modeled in the framework of deep RL. Then, after the reward function for learning is defined, they are learned with deep RL. The deep RL algorithm used in the present study is the twin-delayed deep deterministic policy gradient (TD3) algorithm. Our proposed algorithm is evaluated with various demonstrations, and a case study of a pick-and place task is done. The results show that our method can learn all demonstrations with high accuracy.

Autonomous robotic assembly process based on hierarchical reinforcement learning,

Mehran Raisi ,Amir Hossein Noohian ,Saeed Khodaygan

Conference Paper The 30th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2022), May 10th to May 12th 2022, Islamic Azad University of Tehran, Tehran, Iran.

Abstract

Mehran Raisi, Amir Hossein Noohian, Saeed Khodaygan Tolerance analysis of mechanical assemblies using univariate dimensional reduction method, The 30th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2022), May 10th to May 12th 2022, Islamic Azad University of Tehran, Tehran, Iran.

Tolerance analysis of mechanical assemblies using univariate dimensional reduction method,

Hassani H., Khodaygan S.

Conference Paper The 30th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2022), May 10th to May 12th 2022, Islamic Azad University of Tehran, Tehran, Iran.

Abstract

Hassani H., Khodaygan S. Tolerance analysis of mechanical assemblies using univariate dimensional reduction method, The 30th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2022), May 10th to May 12th 2022, Islamic Azad University of Tehran, Tehran, Iran.

Moving an object between two points on the ground using learning from demonstration dynamics based on dynamic movement primitives,

Salehdehgani Tafti M., Khodaygan S.

Conference Paper The 29th Annual International Conference of the Iranian Association of Mechanical Engineers, K. N. Toosi University of Technology, Tehran, Iran, 22-25 May, 2021.

Abstract

Noohian A.H., Khodaygan S. Moving an object between two points on the ground using learning from demonstration dynamics based on dynamic movement primitives, The 29th Annual International Conference of the Iranian Association of Mechanical Engineers, K. N. Toosi University of Technology, Tehran, Iran, 22-25 May, 2021.

Developing a method for optimal automatic assembly of products with many number of components

Daliri A., Khodaygan S.

Conference Paper 29th Annual International Conference of the Iranian Association of Mechanical Engineers, K. N. Toosi University of Technology, Tehran, Iran, 22-25 May, 2021.

Abstract

Daliri A., S. Khodaygan, Developing a method for optimal automatic assembly of products with many number of components, 29th Annual International Conference of the Iranian Association of Mechanical Engineers, K. N. Toosi University of Technology, Tehran, Iran, 22-25 May, 2021.

Tolerance design of cam-follower mechanism taking into account the effects of wear and quality loss during construction and operating conditions,

Salehdehgani Tafti M., Khodaygan S.

Conference Paper 28th Annual International Conference of the Iranian Association of Mechanical Engineers, Amirkabir University of Technology, Tehran, Iran, 27-29 May, 2020.

Abstract

Salehdehgani Tafti M., S. Khodaygan Tolerance design of cam-follower mechanism taking into account the effects of wear and quality loss during construction and operating conditions, 28th Annual International Conference of the Iranian Association of Mechanical Engineers, Amirkabir University of Technology, Tehran, Iran, 27-29 May, 2020.

Optimal and robust design based on reliability with lack of data conditions using Bayesian inference

Hassani H., Khodaygan S.

Conference Paper 27th Annual International Conference of the Iranian Association of Mechanical Engineers, University of Tehran & Tarbiat Modares University, Tehran, Iran, 30 April-2 May, 2019.

Abstract

Hassani H., S. Khodaygan, Optimal and robust design based on reliability with lack of data conditions using Bayesian inference, 27th Annual International Conference of the Iranian Association of Mechanical Engineers, University of Tehran & Tarbiat Modares University, Tehran, Iran, 30 April-2 May, 2019.

Multi-physical modeling and sensitivity analysis of effective parameters of electrohydrodynamic 3D printer

Mohammadi K., M.R Movahhedy, Khodaygan S.

Conference Paper 27th Annual International Conference of the Iranian Association of Mechanical Engineers, University of Tehran & Tarbiat Modares University, Tehran, Iran, 30 April-2 May, 2019.

Abstract

Mohammadi K., M.R Movahhedy, S. Khodaygan, Multi-physical modeling and sensitivity analysis of effective parameters of electrohydrodynamic 3D printer, 27th Annual International Conference of the Iranian Association of Mechanical Engineers, University of Tehran & Tarbiat Modares University, Tehran, Iran, 30 April-2 May, 2019.

Multiphysical-multiphase modeling of electrohydrodynamic 3D printers

Mohammadi K., M.R Movahhedy, Khodaygan S.

Conference Paper 2th National comprehensive Symposium on 3D printing; Iran 3D Show 2018, Dec 6-8, 2018.

Abstract

Mohammadi K., M.R Movahhedy, S. Khodaygan, Multiphysical-multiphase modeling of electrohydrodynamic 3D printers, 2th National comprehensive Symposium on 3D printing; Iran 3D Show 2018, Dec 6-8, 2018.

Optimal design of high-speed spindle bearings for reducing non-repeatable run out

Farahani M.R., Khodaygan S.

Conference Paper The 26th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2018), April 24-26, 2018, Semnan University, Semnan, Iran.

Abstract

Farahani M.R., Khodaygan S. (2018). Optimal design of high-speed spindle bearings for reducing non-repeatable run out, The 26th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2018), April 24-26, 2018, Semnan University, Semnan, Iran.

Optimal design of high-speed spindle bearings for reducing non-repeatable run out

Farahani M.R., Khodaygan S.

Conference Paper The 26th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2018), April 24-26, 2018, Semnan University, Semnan, Iran.

Abstract

Farahani M.R., Khodaygan S. (2018). Optimal design of high-speed spindle bearings for reducing non-repeatable run out, The 26th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2018), April 24-26, 2018, Semnan University, Semnan, Iran.

Tolerance analysis for quality control of products based on Bayesian-reliability model

Khodaygan S. , Ghaderi A.

Conference Paper The 26th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2018), April 24-26, 2018, Semnan University, Semnan, Iran.

Abstract

Khodaygan S., Ghaderi A., (2018) Tolerance analysis for quality control of products based on Bayesian-reliability model The 26th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2018), April 24-26, 2018, Semnan University, Semnan, Iran.

An algorithm for identifying dynamic characteristics of asymmetric rotary mechanical systems based on operational modal analysis,

Khodaygan S. , Talebi M.

Conference Paper 7th International Conference on Acoustics and Vibration, November 27-28, 2017, Sharif university of technology, Tehran, Iran.

Abstract

Khodaygan S., Talebi M., (2017) An algorithm for identifying dynamic characteristics of asymmetric rotary mechanical systems based on operational modal analysis, 7th International Conference on Acoustics and Vibration, November 27-28, 2017, Sharif university of technology, Tehran, Iran.

A new method for robust design of the inactive suspension system with uncertain parameters,

Khodaygan S. , Sharafi M.H.

Conference Paper 7th International Conference on Acoustics and Vibration, November 27-28, 2017, Sharif university of technology, Tehran, Iran.

Abstract

Khodaygan S., Sharafi M.H., (2017) A new method for robust design of the inactive suspension system with uncertain parameters, 7th International Conference on Acoustics and Vibration, November 27-28, 2017, Sharif university of technology, Tehran, Iran.

Analysis of the Effects of dimensional and geometric tolerances on the natural frequencies of flexible rotary systems based on tolerance zone model,

Khodaygan S. , H. Fallahzadeh

Conference Paper The 25th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2017),May 2-4, 2017, Tarbiat Modares University, Tehran, Iran.

Abstract

Khodaygan S. , H. Fallahzadeh, Analysis of the Effects of dimensional and geometric tolerances on the natural frequencies of flexible rotary systems based on tolerance zone model, The 25th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2017),May 2-4, 2017, Tarbiat Modares University, Tehran, Iran.

Analysis of the Effects of dimensional and geometric tolerances on the natural frequencies of flexible rotary systems based on tolerance zone model,

Manshoori Yeganeh A., M. R. Movahhedy,S. Khodaygan ,

Conference Paper The 25th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2017),May 2-4, 2017, Tarbiat Modares University, Tehran, Iran.

Abstract

Manshoori Yeganeh A. , Movahhedy M. R., Khodaygan S., (2017) Investigation of scanning parameters' effect on warpage of manufactured parts by SLS process based on finite element modeling. The 25th International Annual Conference of the Iranian Society of Mechanical Engineers (ISME 2017),May 2-4, 2017, Tarbiat Modares University, Tehran, Iran.

Tolerance allocation of mechanical assemblages under thermal impact

Khodaygan S. , J. Hemati-Nik

Conference Paper 24th Annual International Conference on Mechanical Engineering ISME 2016; April 26-28, 2016; Yazd, Iran.

Abstract

Khodaygan S., Hemati-Nik J., (2016) Tolerance allocation of mechanical assemblages under thermal impact, 24th Annual International Conference on Mechanical Engineering ISME 2016; April 26-28, 2016; Yazd, Iran.

Multi-objective optimization of parameters affecting machining in the stability limit by providing a novel innovative algorithm

Jafarzadeh E., Sohani A., Khodaygan S.

Conference Paper 24th Annual International Conference on Mechanical Engineering ISME 2016; April 26-28, 2016; Yazd, Iran.

Abstract

Jafarzadeh E., Sohani A., Khodaygan S., Multi-objective optimization of parameters affecting machining in the stability limit by providing a novel innovative algorithm, 24th Annual International Conference on Mechanical Engineering (ISME 2016); April 26-28, 2016; Yazd, Iran.

Fuzzy analysis of production process capability for evaluating assembly quality in mechanical assemblies

Khodaygan S. , Movahhedy M.R.

Conference Paper 24th Annual International Conference on Mechanical Engineering ISME 2016; April 26-28, 2016; Yazd, Iran.

Abstract

Khodaygan S., Movahhedy M.R., (2013) Tolerance analysis of mechanical assemblies based on fuzzy-small degrees of freedom (f-sdof) model, 21th Annual International Conference on Mechanical Engineering (ISME 2013);K.N. Toosi University of Technology, Tehran, Iran.

Fuzzy analysis of production process capability for evaluating assembly quality in mechanical assemblies

Khodaygan S. , Movahhedy M.R.

Conference Paper ASME International Mechanical Engineering Congress and Exposition. Vol. 44274. 2010

Abstract

Tolerances naturally generate an uncertain environment for design and manufacturing. In this paper, a novel fuzzy based tolerance representation approach for modeling the variations of geometric features due to dimensional tolerances is presented. The two concepts of fuzzy theory and small degrees of freedom are combined to introduce the fuzzy-small degrees of freedom model (F-SDOF). This model is suitable for tolerance analysis of mechanical assemblies with linear and angular tolerances. The presented method is compatible with the current dimensioning and tolerancing standards. The application of the proposed methodology is illustrated through presenting an example problem.

FStatistical Error Analysis for Dimensional Control in Automotive Body Assembly Process."

Khodaygan S. , M. R. Movahhedy, A. Mirabolghasemi, M. Zendehbad, H. Moradi

Conference Paper ASME International Mechanical Engineering Congress and Exposition. Vol. 44274. 2010

Abstract

In mechanical assemblies, the performance, quality, cost and assemblability of the product are significantly affected by the geometric errors of the parts. This paper develops the statistical error analysis approach for dimensional control in automotive body multi-station assembly process. In this method, the homogeneous transformation matrices are used to describe the location and orientation of part and assembly features and the small homogeneous transformation matrices are used to model the errors. In this approach, the effective errors in automotive body assembly process are classified in three categories: manufacturing errors (dimensional and geometric tolerances), locating errors (fixture errors) and process errors (joining errors). In a mechanical assembly, small variations due the errors propagate according to a complex mechanism that in this approach it formulated in error analysis procedure. The propagation chain of geometric errors is described based on CAD models. The estimation of the error accumulation and the percent contributions of individual errors are based on the statistical model (root-sum-square method). The application of the proposed method is illustrated through presenting an example problem.

"Tolerance analysis of mechanical assemblies based on fuzzy-small degrees of freedom (F-SDOF) model"

Khodaygan S., M. R. Movahhedy

Conference Paper ASME International Mechanical Engineering Congress and Exposition. Vol. 44274. 2010

Abstract

Tolerances naturally generate an uncertain environment for design and manufacturing. In this paper, a novel fuzzy based tolerance representation approach for modeling the variations of geometric features due to dimensional tolerances is presented. The two concepts of fuzzy theory and small degrees of freedom are combined to introduce the fuzzy-small degrees of freedom model (F-SDOF). This model is suitable for tolerance analysis of mechanical assemblies with linear and angular tolerances. The presented method is compatible with the current dimensioning and tolerancing standards. The application of the proposed methodology is illustrated through presenting an example problem.

"Tolerance analysis of mechanical assemblies with asymmetric tolerances using uncertainty model based on fuzzy logic"

Movahhedy M.R.,Khodaygan S.

Conference Paper 18th Annual International Conference of the Iranian Society of Mechanical Engineers (ISME 2010), Sharif University of Technology, Tehran, Iran.

Abstract

Movahhedy M.R., Khodaygan S., (2010). Tolerance analysis of mechanical assemblies with asymmetric tolerances using uncertainty model based on fuzzy logic, 18th Annual International Conference of the Iranian Society of Mechanical Engineers (ISME 2010), Sharif University of Technology, Tehran, Iran.

"Tolerance analysis of mechanical assemblies with asymmetric tolerances using uncertainty model based on fuzzy logic"

Khodaygan S., M.R. Movahhedy

Conference Paper 10th Iranian Conference on Manufacturing Engineering

Abstract

Khodaygan S., Movahhedy M.R., (2010). Tolerance analysis of mechanical assemblies based on modal interval - small degrees of freedom model, 10th Iranian Conference on Manufacturing Engineering.

"Tolerance analysis of tilted-pad journal using parametric method"

Salehvesal, A.,M.R. Movahhedy ,S. Khodaygan

Conference Paper 10th Iranian Conference on Manufacturing Engineering

Abstract

Salehvesal, A., Movahhedy M.R., Khodaygan S., (2010). Tolerance analysis of tilted-pad journal using parametric method, 10th Iranian Conference on Manufacturing Engineering.

"3D Tolerance analysis of welding fixture based on Fuzzy - Direct Linearization Method, "

,Khodaygan S. ,M.R. Movahhedy

Conference Paper 10th Iranian Conference on Manufacturing Engineering

Abstract

Khodaygan S., Movahhedy M.R., (2010). 3D Tolerance analysis of welding fixture based on Fuzzy - Direct Linearization Method, 10th Iranian Conference on Manufacturing Engineering.

Saeed Khodaygan

Sharif University of Technology

SAEED KHODAYGAN

Associate ProfessorMechanical Engineering DepartmentSharif University of Technology

Education

Contact Information

Executive Activities

Vice-Chairman: Student Affairs

Editor-in-Chief

Head of PEM Lab

Manager of IT Center

Director of Public Relations

Research Interests

Dissertations and Thesis

"Numerical Modelling and Experimental Validation of Nano Colloid Droplet Formation in the Electrohydrodynamic 3D Printer"

"Optimal Process Planning for Automated Robotic Assembly of Mechanical Assembles based on Reinforcement Learning Method"

"Robust Orientation Estimation Using IMU and Online Machine Learning - based Calibration in the Presence of Distortions"

"A Path Planning Method Based on Basic RRT* Algorithm and Cagd-Based Curves for Non-Holonomic Wheeled Mobile Robots"

"Automatic System Identification Algorithm Including Uncertainty Estimation based on Operational Modal Analysis"

"Laser-Based Inspection of Internal Geometry of Industrial Pipes in Pigging Procedure"

"Selection of the Optimal Orientation of Parts in Rapid Prototyping Processes"

"Optimization of Resonator’s Acoustic Performance in the Muffler System"

"Robust Design Optimization for Fatigue Life with Geometric and Material Uncertainties of Mechanical Parts Under Random Loading Based on Maximizing Fatigue Life and Minimizing Uncertainty in Fatigue Life Prediction"

"Reliability Based Robust Design Optimization of Mechanical Systems with Uncertain Parameters Using Bayesian Inference"

" Finite Element Simulation of Machining Chatter in Turning and Milling with Orthogonal Geometry, Taking into Account of Two-Dimensional Machine Tool Dynamics "

"Optimization of Scan Algorithms in Selective Laser Sintering"

"Tolerance Design of Mechanical Parts Considering Degradation and Quality Loss in Manufacturing Process and Operating Conditions "

"A new Approach in Reliability Based Robust Optimization"

"Optimal Design of Tolerances in the Non-rigid Assemblies under the Thermal Impact"

"Optimal Design of the High Speed Spindle Bearings to Reduce Non Repeatable Run Out "

"Tolerance Analysis of Rotating Mechanical Systems in Presence of Dimensional and Geometrical Errors"

"Tolerance Design of Mechanical Systems based on Reliability Modeling under Bayesian Inference"

"Effect of Superhydrophobic Materials Application on the Car Body to Reduce Drag"

"Device on a Chip, in Order to Control and Separation of Circulating Tumor Cells"

Interest Areas

Applied Artificial Intelligence

- Machine Learning- Deep Reinforcement Learning- Digital Twin Modeling- Computational Intelligence- Fuzzy Systems- Evolutionary Algorithms

Design for X (DfX)

- Multidisciplinary Design Optimization- Robust and Reliability-based Design- Robust and Reliability-based Design- Experimental Design- Design for 3D Printing - Design for Manufacturing/Assembly/Testing- Nature-Inspired Design

Precision Engineering

- Tolerance Design- Imprecision and Uncertainty Analysis- Measurement Systems & Metrology

Publications

"R3T*-MOSafeRL: path planning of mobile robots in unknown dynamic environments"

Abstract

"Design for additive manufacturing of topology-optimized structures based on deep learning and transfer learning"

Abstract

"An interface tool for finite element–based optimal design"

Abstract

"Deep reinforcement learning-based framework for constrained any-objective optimization"

Abstract

"Effect of geometric deviations on the strength of additively manufactured ultralight periodic shell-based lattices"

Abstract

"Concurrent optimization of surface roughness, build time, and mechanical properties of additively manufactured product in terms of part build orientation"

Abstract

"A continuous RRT*-based path planning method for non-holonomic mobile robots using B-spline curves"

Abstract

"Reliability-based optimal tolerance design of mechanical systems including epistemic uncertainty"

Abstract

"Tolerance analysis of a compliant assembly using random Non-Uniform Rational B-Spline curves and isogeometric method"

Abstract

"Prognostic of rolling element bearings based on early-stage developing faults."

Abstract

"Direct tolerance analysis of mechanical assemblies with normal and non-normal tolerances for predicting product quality"

Abstract

"A Bayesian-reliability based multi-objective optimization for tolerance design of mechanical assemblies."

Abstract

"Colloidal particle reaction and aggregation control in the Electrohydrodynamic 3D printing technology"

Abstract

"Minimization of Non-repeatable Runout (NRRO) in High-Speed Spindle Bearings"

Abstract

"An algorithm for numerical nonlinear optimization: Fertile Field Algorithm (FFA)."

Abstract

"Multi-objective optimal design of stiffened laminated composite cylindrical shell with piezoelectric actuators."

Abstract

"Optimal path-planning for mobile robots to find a hidden target in an unknown environment based on machine learning."

Abstract

"Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions."

Abstract

"Modal Parameter Identification of Rotary Systems Based on Power Spectral Density Transmissibility Functions."

Abstract

SAEED
KHODAYGAN

Associate Professor
Mechanical Engineering Department
Sharif University of Technology

- Machine Learning
- Deep Reinforcement Learning
- Digital Twin Modeling
- Computational Intelligence
- Fuzzy Systems
- Evolutionary Algorithms

- Multidisciplinary Design Optimization
- Robust and Reliability-based Design
- Robust and Reliability-based Design
- Experimental Design
- Design for 3D Printing
- Design for Manufacturing/Assembly/Testing
- Nature-Inspired Design

- Tolerance Design
- Imprecision and Uncertainty Analysis
- Measurement Systems & Metrology