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Cited 9 time in webofscience Cited 12 time in scopus
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A reactive decentralized coordination algorithm for event-driven production planning and control: A cyber-physical production system prototype case study

Authors
Okpoti, Evans SowahJeong, In Jae
Issue Date
Jan-2021
Publisher
Elsevier B.V.
Keywords
Cyber-physical production system; Decentralized coordination; Production planning; Smart factory
Citation
Journal of Manufacturing Systems, v.58, pp.143 - 158
Indexed
SCIE
SCOPUS
Journal Title
Journal of Manufacturing Systems
Volume
58
Start Page
143
End Page
158
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/142463
DOI
10.1016/j.jmsy.2020.11.002
ISSN
0278-6125
Abstract
Concepts and expectations of cyber-physical production systems (CPPSs) underscore their advantages over the present bespoke manufacturing systems. However, transitioning from traditional manufacturing to its CPPS counterpart remains a challenge. Although a CPPS can be realized, a gap between theory and practice exists considering the response of a CPPS to system disturbances, such as machine breakdowns and change in customer orders. Furthermore, the CPPS environment is stochastic; therefore, planning and control algorithms to reduce the discrepancy between the planned and actual system levels in real time is essential. In this paper, we present a CPPS prototype and a reactive production planning algorithm. Consistent with the literature on CPPS, we developed a moderately automated CPPS and a decentralized coordination mechanism that harnesses the inherent decentralized structure of the CPPS. Moreover, we have described the design and technologies used in building this CPPS. Through a production planning mathematical model, we proposed a control mechanism and measured the efficiency of the proposed algorithm under dynamic events based on work-in-progress inventories, throughput, and delayed demand. The decentralized algorithm determines a plan prior to start of production, which is re-optimized in case any dynamic events occur subsequent to the course of the production horizon. The results of the numerical investigation indicated that the proposed decentralized coordination algorithm outperforms other centralized planning algorithms on more than 50 % of the performance measures considered.
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