4.7 Article

An integrated contract manufacturer selection and product quality optimization methodology for the mechanical manufacturing industry

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 183, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2021.115336

Keywords

Outsourcing; Process capability index; Pareto optimality; Contract manufacturer selection; Mechanical manufacturing industry

Funding

  1. National Natural Science Foundation of China [71762008]
  2. Quality and Brand Development Research Center in Dongguan University of Technology [GB200101]
  3. Foundation of College's Key Research base on Humanities and Social Science in Guangdong Province, China: Pearl River Delta Industrial Ecology Research Center [2016WZJD005]
  4. Ministry of Science and Technology Taiwan [MOST 109-2221-E-167-021-MY2]

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Outsourcing is a crucial strategy in the mechanical manufacturing industry. This study introduces an integrated methodology for quality performance assessment and optimization of products with multiple quality characteristics for contract manufacturer selection. The methodology includes a novel process capability analysis chart and Pareto optimality approach, with a feedback mechanism for improvement suggestions.
Outsourcing is a crucial strategy of the mechanical manufacturing industry. When outsourcing, it is necessary for companies to carefully inspect the performance of contract manufacturers (CMs) to ensure high-quality products and satisfactory services. This study presents an integrated methodology for the quality performance assessment and optimization of products with multiple quality characteristics for CM selection in the mechanical manufacturing industry. First, we present a novel process capability analysis chart (PCAC) using the 100(1-alpha)% upper confidence limits of C-pmh, C-puh, and C-plh to gauge the process capabilities of products with multiple quality characteristics and reduce the influence of sampling errors. Second, we apply Pareto optimality to reexamine eligible CMs under the objectives of maximizing performance in individual quality characteristics and minimizing variance in overall performance. A feedback mechanism is included to advise ineligible CMs on means of improvement. Finally, we present a case study to demonstrate the feasibility and effectiveness of the proposed methodology.

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