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Dynamics performance in a hybrid system with information sharing and push policies adopted in remanufacturing process

Dynamics performance in a hybrid system with information sharing and push policies adopted in remanufacturing process

Zhou, Li ORCID: 0000-0001-7132-5935 and Lin, Yong ORCID: 0000-0001-7118-2946 (2010) Dynamics performance in a hybrid system with information sharing and push policies adopted in remanufacturing process. In: The 1st Regional Conference of the European Decision Sciences Institute, July 2-3, 2010, IESE Business School Barcelona, Spain. (Unpublished)

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Abstract

This research studies a manufacturing and remanufacturing joint system in which a pull-based remanufacturing process with inventory information shared with manufacturing. We use the control theory and simulation as the research methodology. The inventory control strategy in the manufacturing loop is the well known APIOBPCS (Automatic Pipeline, Inventory and Order Based Production Control System). The aim of this research is to study how information sharing influences the system dynamics. We are in particular interested in the uncertainties in remanufacturing process and their impact on system dynamics behavior. Our results show that the information sharing can generally help to improve overall system dynamics performance. However, it also depends on which level of information sharing. In a pull-based remanufacturing process, it is not necessarily always true that the higher level of inform sharing the better dynamics performance.

Item Type: Conference or Conference Paper (Paper)
Additional Information: This paper was given at the 1st Regional Conference of the European Decision Sciences Institute held at IESE Business School in Barcelona, Spain, on July 2nd and 3rd, 2010
Uncontrolled Keywords: Performance measurement; dynamics performance; manufacturing; remanufacturing; pull strategy; information sharing; APIOBPCS.
Subjects: H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HF Commerce
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Systems Management & Strategy
Faculty of Business > Supply Chain Management Research Group
Related URLs:
Last Modified: 20 Oct 2016 15:30
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/5275

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