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Standard Deviation Method Based PSO: An Instigated Approach to Optimize Multi-Objective Manufacturing Process Parameters

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  • Arindam Majumder

    (Mechanical Engineering Department, National Institute of Technology Agartala, Agartala, India)

  • Abhishek Majumder

    (Computer Science and Engineering Department, Tripura University (A Central University), Agartala, India)

Abstract

Nowadays, optimization of process parameters in manufacturing process deals with a number of objectives. However, the optimization of such process becomes more complex if selected attributes are conflicting in nature. Therefore, to overcome this problem in this study a SDM based PSO algorithm is proposed for optimizing the manufacturing process having multi attribute. In this proposed approach the SDM is used to convert multi attributes into single attribute, named as multi performance index, while the optimal value of this multi performance index is predicted by PSO. Finally, three instances related to optimization of advanced manufacturing process parameters are solved by the proposed approach and are compared with the results of the other established optimization techniques such as Desirability based RSM, SDM-GA and SDM-CACO. From the comparison it has been revealed that the proposed approach performs better as compare to the existing approaches.

Suggested Citation

  • Arindam Majumder & Abhishek Majumder, 2016. "Standard Deviation Method Based PSO: An Instigated Approach to Optimize Multi-Objective Manufacturing Process Parameters," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 7(2), pages 15-35, April.
    • Handle: RePEc:igg:jsir00:v:7:y:2016:i:2:p:15-35
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