Manufacturing Technology Today

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Genetic Algorithm (GA) Based Tolerance Allocation of Machine Assembly with Loss Function


Affiliations
1 Department of Production Engineering, J. J. College of Engineering and Technology, Tiruchirappalli, India
2 Department of Mechatronics Engineering, Kumaraguru College of Technology, Coimbatore, India
3 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, India
     

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In modern manufacturing engineering tolerances plays an important role because it is directly impact quality of the product, machining cost, and quality loss. In traditional approach, tolerances have been allocated based on designer’s experience or trial and error method. Practically it is not feasible. A more scientific approach is often desirable for better performance. In this work, the optimization of tolerance allocation of over running clutch assembly and punch and die assembly are taken for analysis. This multi objective non linear, constraint, problems are solved with the Genetic Algorithm (GA). The results are compared with conventional method and the performances are analyzed.
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  • Genetic Algorithm (GA) Based Tolerance Allocation of Machine Assembly with Loss Function

Abstract Views: 164  |  PDF Views: 0

Authors

K. Sivakumar
Department of Production Engineering, J. J. College of Engineering and Technology, Tiruchirappalli, India
R. Saravanan
Department of Mechatronics Engineering, Kumaraguru College of Technology, Coimbatore, India
A. Noorul Haq
Department of Production Engineering, National Institute of Technology, Tiruchirappalli, India

Abstract


In modern manufacturing engineering tolerances plays an important role because it is directly impact quality of the product, machining cost, and quality loss. In traditional approach, tolerances have been allocated based on designer’s experience or trial and error method. Practically it is not feasible. A more scientific approach is often desirable for better performance. In this work, the optimization of tolerance allocation of over running clutch assembly and punch and die assembly are taken for analysis. This multi objective non linear, constraint, problems are solved with the Genetic Algorithm (GA). The results are compared with conventional method and the performances are analyzed.