A multi-agent system to support heuristic-based dynamic manufacturing rescheduling

  • Authors:

  • Luping Zhang;T. N. Wong;R. Y. K. Fung

  • Affiliations:

  • Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China;Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China;Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China

  • Venue:
  • Intelligent Decision Technologies
  • Year:
  • 2013

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Abstract

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.