An efficiency measurement framework for multi-stage production systems

被引:0
|
作者
Boaz Golany
Steven T. Hackman
Ury Passy
机构
[1] Technion—Israel Institute of Technology,Faculty of Industrial Engineering and Management
[2] Georgia Institute of Technology,School of Industrial and Systems Engineering
来源
关键词
Multi-stage production systems; Productivity and efficiency measurement; Data envelopment analysis;
D O I
暂无
中图分类号
学科分类号
摘要
We develop an efficiency measurement framework for systems composed of two subsystems arranged in series that simultaneously computes the efficiency of the aggregate system and each subsystem. Our approach expands the technology sets of each subsystem by allowing each to acquire resources from the other in exchange for delivery of the appropriate (intermediate or final) product, and to form composites from both subsystems. Managers of each subsystem will not agree to ‘`vertical integration’' initiatives unless each subsystem will be more efficient than what each can achieve by separately applying conventional efficiency analysis. A Pareto Efficient frontier characterizes the acceptable set of efficiencies of each subsystem from which the managers will negotiate to select the final outcome. Three proposals for the choice for the Pareto efficient point are discussed: the one that achieves the largest equiproportionate reduction in the classical efficiencies; the one that achieves the largest equal reduction in efficiency; and the one that maximizes the radial contraction in the aggregate consumption of resources originally employed before integration. We show how each choice for the Pareto efficient point determines a derived measure of aggregate efficiency. An extensive numerical example is used to illustrate exactly how the 2 subsystems can significantly improve their operational efficiencies via integration beyond what would be predicted by conventional analysis.
引用
收藏
页码:51 / 68
页数:17
相关论文
共 50 条
  • [41] Multi-Stage Supply Chain with Production Uncertainty
    Feng, Qi
    Ma, Zhongjie
    Mao, Zhaofang
    Shanthikumar, J. George
    PRODUCTION AND OPERATIONS MANAGEMENT, 2021, 30 (04) : 921 - 940
  • [42] Stochastic properties of fork/join multi-stage production systems with general blocking
    Nakade, K
    Ohno, K
    JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF JAPAN, 1997, 40 (03) : 341 - 355
  • [43] Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture
    Zhang, Huijie
    Lu, Yifu
    Alkhouri, Ismail
    Ravishankar, Saiprasad
    Song, Dogyoon
    Qu, Qing
    2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2024, 2024, : 7372 - 7381
  • [44] COST CONTROLS IN MULTI-STAGE PRODUCTION PROCESSES
    KLOOCK, J
    DORNER, E
    OR SPEKTRUM, 1988, 10 (03) : 129 - 143
  • [45] Multi-dimensional clearing functions for aggregate capacity modelling in multi-stage production systems
    Albey, Erinc
    Bilge, Umit
    Uzsoy, Reha
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2017, 55 (14) : 4164 - 4179
  • [46] On control strategies in a multi-stage production system
    Zhao, XB
    Gong, QG
    Wang, JC
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2002, 40 (05) : 1155 - 1171
  • [47] Thermal Efficiency of Cogeneration Units with Multi-Stage Reheating for Russian Municipal Heating Systems
    Lisin, Evgeny
    Sobolev, Alexander
    Strielkowski, Wadim
    Garanin, Ivan
    ENERGIES, 2016, 9 (04):
  • [48] A dynamic multi-stage design framework for staged deployment optimization of highly stochastic systems
    Bayan Hamdan
    Zheng Liu
    Koki Ho
    İ. Esra Büyüktahtakın
    Pingfeng Wang
    Structural and Multidisciplinary Optimization, 2023, 66
  • [49] A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems
    Yang, Li
    Shami, Abdallah
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 19 (02) : 2107 - 2116
  • [50] A dynamic multi-stage design framework for staged deployment optimization of highly stochastic systems
    Hamdan, Bayan
    Liu, Zheng
    Ho, Koki
    Buyuktahtakin, I. Esra
    Wang, Pingfeng
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2023, 66 (07)