TY - JOUR
T1 - Distributed adaptive control of production scheduling and machine capacity
AU - Cho, Sohyung
AU - Prabhu, Vittaldas V.
N1 - Funding Information:
This work was partially supported by National Science Foundation grants DMI-9908267 and DMI-0075572 and the Ben Franklin Technology Partnership through Penn State’s Center for Manufacturing Enterprise Integration.
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2007/4
Y1 - 2007/4
N2 - This paper considers modeling and simulation of a unified control system that uses a continuous control-theoretic approach for distributed production scheduling at the shop floor and machine capacity control at the CNC level. Specifically, a distributed production scheduling method is unified with a distributed machine capacity control to generate realistic schedules considering the available capacity of production resources. In this distributed control system, machine capacity is adaptively controlled based on current physical conditions of the production resources and changes in production demands at the shop-floor level as well. The proposed system considers a multi-attribute objective that consists of production rate and product quality, production cost, and mean-squared deviation of job completions about due dates. The results obtained from the computational experiments show that the proposed system can improve the system performance through fully utilizing machine capacity while reducing production costs, production delays, missed deliveries, and customer dissatisfaction.
AB - This paper considers modeling and simulation of a unified control system that uses a continuous control-theoretic approach for distributed production scheduling at the shop floor and machine capacity control at the CNC level. Specifically, a distributed production scheduling method is unified with a distributed machine capacity control to generate realistic schedules considering the available capacity of production resources. In this distributed control system, machine capacity is adaptively controlled based on current physical conditions of the production resources and changes in production demands at the shop-floor level as well. The proposed system considers a multi-attribute objective that consists of production rate and product quality, production cost, and mean-squared deviation of job completions about due dates. The results obtained from the computational experiments show that the proposed system can improve the system performance through fully utilizing machine capacity while reducing production costs, production delays, missed deliveries, and customer dissatisfaction.
UR - http://www.scopus.com/inward/record.url?scp=48049102820&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48049102820&partnerID=8YFLogxK
U2 - 10.1016/j.jmsy.2007.10.002
DO - 10.1016/j.jmsy.2007.10.002
M3 - Article
AN - SCOPUS:48049102820
VL - 26
SP - 65
EP - 74
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
SN - 0278-6125
IS - 2
ER -