An integrated approach for lean production using simulation and data envelopment analysis


BÜYÜKSAATÇI KİRİŞ S., ERYARSOY E., Zaim S., Delen D.

ANNALS OF OPERATIONS RESEARCH, cilt.320, sa.2, ss.863-886, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 320 Sayı: 2
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s10479-021-04265-z
  • Dergi Adı: ANNALS OF OPERATIONS RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Computer & Applied Sciences, INSPEC, Public Affairs Index, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.863-886
  • Anahtar Kelimeler: Lean production, Time study, Multi-machine set-up reduction (MMSUR), Single minute exchange of dies (SMED), Simulation, Data envelopment analysis (DEA), PRODUCTION SYSTEM, MANUFACTURING SYSTEM, MEASURING EFFICIENCY, GREEN STRATEGIES, PERFORMANCE, DESIGN, MODEL, TIME, OPTIMIZATION, FLEXIBILITY
  • İstanbul Üniversitesi Adresli: Hayır

Özet

According to the extant literature, improving the leanness of a production system boosts a company's productivity and competitiveness. However, such an endeavor usually involves managing multiple, potentially conflicting objectives. This study proposes a framework that analyzes lean production methods using simulation and data envelopment analysis (DEA) to accommodate the underlying multi-objective decision-making problem. The proposed framework can help identify the most efficient solution alternative by (i) considering the most common lean production methods for assembly line balancing, such as single minute exchange of dies (SMED) and multi-machine set-up reduction (MMSUR), (ii) creating and simulating various alternative assembly line configuration options via discrete-event simulation modeling, and (iii) formulating and applying DEA to identify the best alternative assembly system configuration for the multi-objective decision making. In this study, we demonstrate the viability and superiority of the proposed framework with an application case on an automotive spare parts production system. The results show that the suggested framework substantially improves the existing system by increasing efficiency while concurrently decreasing work-in-process (WIP).