Equipment procurement for printed circuit board manufacturing using the analytic hierarchy process

Yu, Vincent F.; Kao, Hsuan-Chih

doi:10.1016/j.jksues.2022.05.004

Cited by 1 publication

(2 citation statements)

References 11 publications

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“…As a result, the machine selection problem in that industry regained focus from researchers to provide MCDM methods that guide decision-makers effectively. In [31], an approach based on the Delphi technique, which is used to compile opinions from separate experts, and AHP was proposed. The 12 criteria considered were technical, economic, and warranty related.…”

Section: Machining and Other Industrial Applicationsmentioning

confidence: 99%

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Multi-Criteria Decision-Making for Machine Selection in Manufacturing and Construction: Recent Trends

Hagag

Yousef²,

Abdelmaguid

2023

Mathematics

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As the number of alternative machines has increased and their technology has been continuously developed, the machine selection problem has attracted many researchers. This article reviews recent developments in applying multi-criteria decision-making (MCDM) methods for selecting machines in the manufacturing and construction industries. Selected articles are classified according to the application area and the applied MCDM method. By focusing on the last five years, this paper identifies recent trends in developing and using these methods. Results suggest that there has been a noticeable growth in the utilization of MCDM techniques for machine selection problems in both sectors. It is also noted that several decision-support tools and methods have been developed and successfully applied during this period. Accordingly, needs and directions for future research are discussed.

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Section: Machining and Other Industrial Applicationsmentioning

confidence: 99%

“…Figure 4 presents the frequency histogram of the number of alternatives. In two papers, [17,31], no specific alternatives were presented. The focus in these two papers was on developing an MCDM methodology to assess the criteria used and provide their weights to decision makers in two different industries.…”

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confidence: 99%