Optimal design of fixture layout in a multi-station assembly using highly optimized tolerance inspired heuristic
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Shukla, Nagesh
Kulkarni, Sumant
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Abstract
The multi-station assembly (MSA) process requires auxiliary devices such as fixtures and clamps to accurately locate and firmly hold the workpiece in a desired position. Improper positioning of these fixtures and clamps affects the dimensional integrity of final product. This study determines the optimal design of fixture layout that minimizes the product dimensional variations caused by the manhandling and aging of auxiliaries. In order to model variation propagation from one assembly station to another in the MSA, a state space model is employed. Further, an E-optimality based sensitivity criterion is proposed to mathematically formulate and measure the quality of the fixture layout design. In order to solve the mathematical formulation, a highly optimized tolerance inspired heuristic is proposed. The proposed approach takes its governing traits from local incremental algorithm (LIA) which was initially exploited to maximize the design parameter (yield) in the percolation model. LIA analogous to the evolution by natural selection schema, assists in suitably exploring the search space of the underlying problem. The assembly of Sports Utility Vehicle side frame has been used to illustrate the concepts and test the performance the proposed solution methodology. Further, robustness of the proposed heuristic is demonstrated by comparing its results with that of obtained from Basic Exchange Algorithm used in the literature.
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Applied Mathematical Modelling
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40
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11-Dec
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© 2016 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
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Tyagi, S; Shukla, N; Kulkarni, S, Optimal design of fixture layout in a multi-station assembly using highly optimized tolerance inspired heuristic, Applied Mathematical Modelling, 2016, 40 (11-12), pp. 6134-6147