TY - JOUR
T1 - A multi-agent system to support heuristic-based dynamic manufacturing rescheduling
AU - Zhang, Luping
AU - Wong, T. N.
AU - Fung, R. Y K
PY - 2013
Y1 - 2013
N2 - In manufacturing systems, process planning and scheduling are the two important pre-production planning functions which are usually performed sequentially. In a dynamic manufacturing environment, however, the shop floor has to encounter disruptions caused by disturbances and uncertainties. The original process plan and schedule may then become inefficient or even infeasible. Ideally, the process plan and the schedule have to be dynamically modified in accordance with the resource availability and conflicts on the shop floor. The merit of integrated process planning and scheduling (IPPS) is to increase the production feasibility and optimality by combining both the process planning and scheduling problems. An increasing number of intelligent approaches, such as search-based algorithms and negotiation-based multi-agent systems, have been proposed for IPPS, Research on the negotiation-based IPPS systems has been focused on the establishment of negotiation protocols to cater for the integration of process planning and scheduling. However, it is intricate to determine the appropriate utility functions and negotiation strategies for individual agentsin the negotiation-based IPPS system. In this paper, a multi-agent system (MAS) architecture is proposed to solve the dynamic IPPS problem with embedded heuristic algorithms. The MAS system is able to support a variety of heuristic methods to effect dynamic process planning, scheduling and re-scheduling. As a result, the proposed MAS system for dynamic IPPS using heuristics possesses high flexibility, extensibility, and accessibility for manufacturing applications. © 2013-IOS Press and the authors. All rights reserved.
AB - In manufacturing systems, process planning and scheduling are the two important pre-production planning functions which are usually performed sequentially. In a dynamic manufacturing environment, however, the shop floor has to encounter disruptions caused by disturbances and uncertainties. The original process plan and schedule may then become inefficient or even infeasible. Ideally, the process plan and the schedule have to be dynamically modified in accordance with the resource availability and conflicts on the shop floor. The merit of integrated process planning and scheduling (IPPS) is to increase the production feasibility and optimality by combining both the process planning and scheduling problems. An increasing number of intelligent approaches, such as search-based algorithms and negotiation-based multi-agent systems, have been proposed for IPPS, Research on the negotiation-based IPPS systems has been focused on the establishment of negotiation protocols to cater for the integration of process planning and scheduling. However, it is intricate to determine the appropriate utility functions and negotiation strategies for individual agentsin the negotiation-based IPPS system. In this paper, a multi-agent system (MAS) architecture is proposed to solve the dynamic IPPS problem with embedded heuristic algorithms. The MAS system is able to support a variety of heuristic methods to effect dynamic process planning, scheduling and re-scheduling. As a result, the proposed MAS system for dynamic IPPS using heuristics possesses high flexibility, extensibility, and accessibility for manufacturing applications. © 2013-IOS Press and the authors. All rights reserved.
KW - heuristics
KW - Integrated process planning and scheduling
KW - multi-agent system
KW - rescheduling
UR - http://www.scopus.com/inward/record.url?scp=84880218421&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84880218421&origin=recordpage
U2 - 10.3233/IDT-130163
DO - 10.3233/IDT-130163
M3 - RGC 21 - Publication in refereed journal
SN - 1872-4981
VL - 7
SP - 197
EP - 211
JO - Intelligent Decision Technologies
JF - Intelligent Decision Technologies
IS - 3
ER -