Using a two-stage D-Optimal mode to select equipment for flexible manufacturing systems

Using a case study from the electronics sector, this research attempts to optimize equipment selection in flexible manufacturing systems (FMS) in order to save costs, improve procedures, and increase production efficiency. To assess equipment combinations, we use a two-stage D-Optimal design in conjunction with discrete event simulation. We compute a weighted response-surface value "y" based on important production indices (such as production rate, waste, and cycle time). With a first-stage response-surface value of 14733.09 and a second-stage refinement to 151317.88, the main results show an ideal combination that achieves 92.8% automation utilization, proving that complete automation does not enhance efficiency. The contribution resides in offering a balanced, measurable method of FMS optimization that can be used to a variety of industries for increased resource efficiency and flexibility without supposing that automation would always be beneficial.

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Publication Details

Journal
Scientific Reports
Published
2026-02-26
DOI
https://doi.org/10.1038/s41598-026-41466-7
Primary Topic
Flexible and Reconfigurable Manufacturing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Using a two-stage D-Optimal mode to select equipment for flexible manufacturing systems

Xiuming Li, Jiajia Liu, Xiaomo Yu, Jie Mi et al.
Scientific Reports
Flexible and Reconfigurable Manufacturing Systems
article

Using a two-stage D-Optimal mode to select equipment for flexible manufacturing systems

Xiuming Li, Jiajia Liu, Xiaomo Yu, Jie Mi, Qinglian Mo, Long Long
article en

Abstract

Using a case study from the electronics sector, this research attempts to optimize equipment selection in flexible manufacturing systems (FMS) in order to save costs, improve procedures, and increase production efficiency. To assess equipment combinations, we use a two-stage D-Optimal design in conjunction with discrete event simulation. We compute a weighted response-surface value "y" based on important production indices (such as production rate, waste, and cycle time). With a first-stage response-surface value of 14733.09 and a second-stage refinement to 151317.88, the main results show an ideal combination that achieves 92.8% automation utilization, proving that complete automation does not enhance efficiency. The contribution resides in offering a balanced, measurable method of FMS optimization that can be used to a variety of industries for increased resource efficiency and flexibility without supposing that automation would always be beneficial.

Scientific Reports
Guangxi Research Institute of Chemical Industry (CN), Nanning Normal University (CN)
National Natural Science Foundation of China, Guangxi University
Decent work and economic growth
Openalex Percentile: Top 46%
Flexible and Reconfigurable Manufacturing Systems
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