A multi-objective flexible manufacturing system design optimization using a hybrid response surface methodology

Nima Pasha (), Hannan Amoozad Mahdiraji (), Seyed Hossein Razavi Hajiagha (), Jose Arturo Garza-Reyes () and Rohit Joshi ()
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Nima Pasha: University of Tehran
Hannan Amoozad Mahdiraji: University of Birmingham
Seyed Hossein Razavi Hajiagha: Khatam University
Jose Arturo Garza-Reyes: The University of Derby
Rohit Joshi: Indian Institute of Management Shillong

Operations Management Research, 2024, vol. 17, issue 1, No 8, 135-151

Abstract: Abstract The present study proposes a hybrid framework combining multiple methods to determine the optimal values of design variables in a flexible manufacturing system (FMS). The framework uses a multi-objective response surface methodology (RSM) to achieve optimum performance. The performance of an FMS is characterized using various weighted measures using the best–worst method (BWM). Subsequently, an RSM approximates the functional relationship between the FMS performance and design variables. The central composite design (CCD) is used for this aim, and a polynomial regression model is fitted among the factors. Eventually, a bi-objective model, including the fitted and cost functions, is formulated and solved. As a result, the optimal percentage for deploying the FMS equipment and machines to achieve optimal performance with the lowest deployment cost is determined. The proposed framework can serve as a guideline for manufacturing organizations to lead strategic decisions regarding the design problems of FMSs. It significantly increases productivity for the manufacturing system, reduces redundant labor and material handling costs, and facilitates production.

Keywords: Flexible manufacturing system; Response surface methodology; Central composite design; Best–worst method; Multi-objective optimization (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12063-023-00412-w

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