OPTIMIZING A MULTIPRODUCT MANUFACTURINGSYSTEM WITH DELAYED DIFFERENTIATION, OUTSOURCING, EXPEDITED RATE, AND REWORK STRATEGIES

Multiproduct manufacturing with delayed differentiation, outsourcing, expedited rate, and rework strategies

  • Professor Yuan-Shyi Peter Chiu Dept. of Industrial Engineering & Management, Chaoyang University of Technology, Taiwan
  • Ms. Chih-Yun Ke Dept. of Industrial Engineering & Management, Chaoyang University of Technology
  • Dr. Victoria Chiu Dept. of Accounting, Finance and Law, The State University of New York at Oswego, NY, USA
  • Ming-Hon Hwang Dept. of Marketing & Logistics Management, Chaoyang University of Technology
Keywords: optimization, multi-item manufacturing, delayed differentiation, rework, expedited rate, outsourcing

Abstract


This study examines the effect of delayed differentiation, outsourcing, expedited fabrication rate, and rework strategies on optimal cycle-time decisions for a multi-item manufacturing system. Today’s manufacturing firms must simultaneously deal with externally increasing client multi-item requirements with rapid lead-time and high-quality products and internally on a limited capacity. This study is aimed at assisting manufacturers in meeting client needs in conditions of restricted-capacity and minimum total operating expenses, and adopts a delayed differentiation two-stage multiproduct manufacturing scheme to manage the end products’ commonality. The first stage produces all required common components, and the second stage fabricates individual finished goods. In both stages, we adopt the reworking of the inevitable nonconforming items produced to assure product quality. Furthermore, we implemented partial outsourcing of common parts’ batch and expedited the manufacturing rate of finished products to effectively reduce the uptimes in both stages. We explicitly developed a model to describe the characteristics of the problem. Mathematical analyses with optimization proved the cost function’s convexity and determined the cost-minimization rotation cycle policy. Finally, we numerically validated our model’s and results’ applicability and capability with a simulated example. Apart from creating a useful decision model, this study makes another important contribution to the existing literature in that its revelation of collective/individual effect of the manufacturing-relevant methods on the problem’s best-operating cycle policy and crucial performance indices helps manufacturers have better control over their operations and make effective and efficient managerial decisions.

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Published
2021/07/28
Section
Original Scientific Paper