Application of Mathematical Modelling to Virtual Manufacturing
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To analyze and modify manufacturing process in virtual environments, mathematical modelling can be used. Effects and behavior of the system are simulated by mathematical concepts in order to be analyzed and modified. So, different parameters of the process can be analyzed in order to be optimized. Thus, efficiency of part production can be increased by applying optimization methods to the simulated manufacturing process in virtual environments. Modification can also be presented to the simulated system in virtual environments by analyzing and decreasing errors of manufacturing process. Therefore, accuracy of produced parts can be increased in order to improve efficiency of part production. Overall, mathematical modelling can develop manufacturing process by providing analysis abilities in virtual environments.
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![Title:
Application of Mathematical Modelling to Virtual
Manufacturing
By:
Mohsen Soori
Department of Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic),
Tehran, Iran
Date:
10 November 2018
Abstract: To analyze and modify manufacturing process in virtual environments,
mathematical modelling can be used. Effects and behavior of the system are simulated by
mathematical concepts in order to be analyzed and modified. So, different parameters of the
process can be analyzed in order to be optimized. Thus, efficiency of part production can be
increased by applying optimization methods to the simulated manufacturing process in virtual
environments. Modification can also be presented to the simulated system in virtual
environments by analyzing and decreasing errors of manufacturing process. Therefore,
accuracy of produced parts can be increased in order to improve efficiency of part production.
Overall, mathematical modelling can develop manufacturing process by providing analysis
abilities in virtual environments.
Keywords: Mathematical modelling, Virtual manufacturing, Production optimization,
Efficiency of part production, Accuracy of produced parts
References
[1] Soori, M., Arezoo, B. and Habibi, M., 2013. Dimensional and geometrical errors of three-axis
CNC milling machines in a virtual machining system. Computer-Aided Design, 45(11), pp.1306-
1313.
[2] Soori, M., Arezoo, B. and Habibi, M., 2014. Virtual machining considering dimensional,
geometrical and tool deflection errors in three-axis CNC milling machines. Journal of
Manufacturing Systems, 33(4), pp.498-507.
[3] Nourazar, S.S., Soori, M. and Nazari-Golshan, A., 2015. On the exact solution of Newell-
Whitehead-Segel equation using the homotopy perturbation method. Australian Journal of
Basic and Applied Sciences 5 (8), pp.1400-1411.
[4] Soori, M., Arezoo, B. and Habibi, M., 2016. Tool Deflection Error of Three-Axis Computer
Numerical Control Milling Machines, Monitoring and Minimizing by a Virtual Machining System.
Journal of Manufacturing Science and Engineering, 138(8), pp. 081005.](https://image.slidesharecdn.com/applmathmodel-181120180850/85/Application-of-Mathematical-Modelling-to-Virtual-Manufacturing-1-320.jpg)
![[5] Soori, M., Arezoo, B. and Habibi, M., 2017. Accuracy analysis of tool deflection error
modeling in prediction of milled surfaces by a virtual machining system. International Journal of
Computer Applications in Technology, 55(4), pp. 308-321.
[6] Soori, M., Nourazar, S.S. and Nazari-Golshan, A., 2015. Application of the Variational
Iteration Method and the Homotopy Perturbation Method to the Fisher Type Equation. Int. J.
Math. Computation, 27(3), pp.1-9.
[7] Nourazar, S.S., Soori, M. and Nazari-Golshan, A., 2015. On the Homotopy Perturbation
Method for the Exact Solution of Fitzhugh–Nagumo Equation. International Journal of
Mathematics & Computation™, 27(1), pp.32-43.
[8] M. Abramovici, D. Gerhard, A Flexible Web-based PDM Approach to Support Virtual
Engineering Cooperation, Proceedings of the 33rd Annual Hawaii International Conference on
System Sciences HICSS, DOI: 10.1109/HICSS.2000.926882, 2000.
[9] Nourazar, S.S., Soori, M. and Nazari-Golshan, A., 2015. On the Exact Solution of Burgers-
Huxley Equation Using the Homotopy Perturbation Method. Journal of Applied Mathematics
and Physics, 3(03), p.28.](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Abstract
This paper deals with elimination of defects in aluminium alloy castings produced by gravity die casting process. The main intention of work is to investigate the defects and improve quality of a gravity die cast component using Computer Aided Casting Simulation Software. In this study an industrial gravity casting die is used which was producing defective components. The die and components produced by the die are studied to eliminate the defects using virtual simulations. The defects in the components are identified to be solidification shrinkage, cracks, unfilled riser and incomplete mould cavity. The reasons for the defects are analyzed as either improper selection of process parameters, or improper design of gating and risering system. SOLIDCast simulation software is used for simulating the solidification process of casting and visualizing outputs showing possible problematic areas or defects which may occur in the cast product. The work is carried out in two stages. In first stage, few test castings are produced by modifying the process parameters (pouring temperature, pouring time, pre heat and alloy type) and results are compared with simulation results produced using same parameters. The pouring and simulation results are observed to be in good accordance with each other. In second stage, number of virtual iterations of casting is performed by changing riser dimensions. It was found from the simulation results that riser with 35mm diameter is required to produce casting with zero defects. The die is modified accordingly with the simulation results and metal is poured. The castings produced are observed to be sound and contain no defects; and also it is verified that solidification simulation helps in locating the defects, eliminating them and ultimately improving the quality of castings without any shop-floor trails.
Keywords: Aluminum-Alloys, Casting Defects, Gravity Die Casting, Material Density and SOLIDCast Simulation
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30420140503002
The document discusses an intelligent hybrid multi-criteria decision making technique to solve a plant layout problem. It first compares several MCDM methodologies including TOPSIS, A-TOPSIS, and VIKOR to validate their consistency on a plant layout case study. It then proposes using M-TOPSIS and A-TOPSIS to evaluate layout alternatives and feeding the results into an unsupervised artificial neural network to generate a new composite ranking of the alternatives. The aim is to derive an optimal configuration ranking by averaging rankings from multiple MCDM methods.
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30420140503002
Multi criteria decision making (MCDM) techniques in today’s organizations, as a key
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TOPSIS, AHP-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution),
PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation),
ELECTRE, VIKOR etc in crisp throughout the literature. In this work, we first compare
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to build an unsupervised artificial neural network (ANN) to obtain a new ranking of
alternatives. This study proposes an approach of deriving the rank value, in order to get
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H0373058071
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
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algorithms namely(a) matching using global orientation features and (b) matching using minutia triangulation.The comparison is done using accuracy, time and number of similar features. The experiment is conducted on a datasets of 100 candidates using four (4) fingerprints from each candidate. The data is sampled from a mass registration conducted by a reputable organization in Kenya.Theresearch reveals that fingerprint matching based on algorithm (b) performs better in speed with an average of 38.32 milliseconds
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This document summarizes a study on modeling and analyzing an involute helical gear using CATIA and ANSYS software. It begins with an introduction to gears and motivation for using numerical analysis methods. It then describes how a helical gear model was generated in CATIA and its stresses were analyzed using ANSYS. Bending stresses from ANSYS were compared to theoretical Lewis equation values and AGMA standards, showing maximum 1.4% deviation. Face width was varied and stresses decreased with increasing width. Overall, complex gear designs require advanced software for accurate modeling and stress analysis to optimize design and prevent failures.
Fast Automatized Parameter Adaption Process of CNC Milling Machines under use...
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A WORKSPACE SIMULATION FOR TAL TR-2 ARTICULATED ROBOT
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285 294
1) The document presents the use of the Homotopy Perturbation Method (HPM) to obtain exact solutions to the Burgers-Huxley nonlinear differential equation.
2) As a case study, the HPM is applied to solve a specific Burgers-Huxley equation with given initial conditions. Approximate solutions are obtained as a power series in the embedding parameter.
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1400 1411
In the present work, we use the homotopy perturbation method (HPM) to solve the Newell- Whitehead-Segel non-linear differential equations. Four case study problems of Newell-Whitehead- Segel are solved by the HPM and the exact solutions are obtained. The trend of the rapid convergence of the sequences constructed by the method toward the exact solution is shown numerically. As a result the rapid convergence towards the exact solutions of HPM indicates that, using the HPM to solve the Newell-Whitehead-Segel non-linear differential equations, a reasonable less amount of computational work with acceptable accuracy may be sufficient. Moreover the application of the HPM proves that the method is an effective and simple tool for solving the Newell-Whitehead-Segel non-linear differential equations
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Application of Mathematical Modelling to Virtual Manufacturing
- 1. Title: Application of Mathematical Modelling to Virtual Manufacturing By: Mohsen Soori Department of Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran Date: 10 November 2018 Abstract: To analyze and modify manufacturing process in virtual environments, mathematical modelling can be used. Effects and behavior of the system are simulated by mathematical concepts in order to be analyzed and modified. So, different parameters of the process can be analyzed in order to be optimized. Thus, efficiency of part production can be increased by applying optimization methods to the simulated manufacturing process in virtual environments. Modification can also be presented to the simulated system in virtual environments by analyzing and decreasing errors of manufacturing process. Therefore, accuracy of produced parts can be increased in order to improve efficiency of part production. Overall, mathematical modelling can develop manufacturing process by providing analysis abilities in virtual environments. Keywords: Mathematical modelling, Virtual manufacturing, Production optimization, Efficiency of part production, Accuracy of produced parts References [1] Soori, M., Arezoo, B. and Habibi, M., 2013. Dimensional and geometrical errors of three-axis CNC milling machines in a virtual machining system. Computer-Aided Design, 45(11), pp.1306- 1313. [2] Soori, M., Arezoo, B. and Habibi, M., 2014. Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines. Journal of Manufacturing Systems, 33(4), pp.498-507. [3] Nourazar, S.S., Soori, M. and Nazari-Golshan, A., 2015. On the exact solution of Newell- Whitehead-Segel equation using the homotopy perturbation method. Australian Journal of Basic and Applied Sciences 5 (8), pp.1400-1411. [4] Soori, M., Arezoo, B. and Habibi, M., 2016. Tool Deflection Error of Three-Axis Computer Numerical Control Milling Machines, Monitoring and Minimizing by a Virtual Machining System. Journal of Manufacturing Science and Engineering, 138(8), pp. 081005.
- 2. [5] Soori, M., Arezoo, B. and Habibi, M., 2017. Accuracy analysis of tool deflection error modeling in prediction of milled surfaces by a virtual machining system. International Journal of Computer Applications in Technology, 55(4), pp. 308-321. [6] Soori, M., Nourazar, S.S. and Nazari-Golshan, A., 2015. Application of the Variational Iteration Method and the Homotopy Perturbation Method to the Fisher Type Equation. Int. J. Math. Computation, 27(3), pp.1-9. [7] Nourazar, S.S., Soori, M. and Nazari-Golshan, A., 2015. On the Homotopy Perturbation Method for the Exact Solution of Fitzhugh–Nagumo Equation. International Journal of Mathematics & Computation™, 27(1), pp.32-43. [8] M. Abramovici, D. Gerhard, A Flexible Web-based PDM Approach to Support Virtual Engineering Cooperation, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences HICSS, DOI: 10.1109/HICSS.2000.926882, 2000. [9] Nourazar, S.S., Soori, M. and Nazari-Golshan, A., 2015. On the Exact Solution of Burgers- Huxley Equation Using the Homotopy Perturbation Method. Journal of Applied Mathematics and Physics, 3(03), p.28.