Download or read book An Agent-Based Approach for Integrating Process Planning and Scheduling written by Chun-Wai David Leung and published by Open Dissertation Press. This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "An Agent-based Approach for Integrating Process Planning and Scheduling" by Chun-wai, David, Leung, 梁俊偉, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled An Agent-Based Approach for Integrating Process Planning and Scheduling Submitted by David Chun Wai Leung for the degree of Doctor of Philosophy at The University of Hong Kong August 2006 Conventionally, manufacturing process planning and scheduling functions are performed separately and sequentially. In general, process plans have to be determined prior to scheduling. Due to the complexity of manufacturing systems, process plans and schedules may easily become inefficient or even infeasible. In this respect, integrated process planning and scheduling (IPPS) plays an important role in the generation of feasible process plans and optimal schedules. With IPPS, the process plan for producing a part and its operations' schedule are determined concurrently, taking into account process planning flexibilities and scheduling requirements. This integrative approach can address the actual and practical needs of industry, but due to the flexibilities in the manufacturing systems IPPS is a very complex problem. This thesis presents an agent-based approach for integrating process planning with scheduling. Firstly, a simple multi-agent system (MAS) architecture using the Multi-Agent Negotiation (MAN) approach is proposed to solve IPPS problems. Under MAN, part agents (PAs) and machine agents (MAs), which represent parts and machines respectively, determine the actual process plan and schedule via a currency-based negotiation. Each PA is given with an AND/OR graph recording all flexible routings and alternative machines of a product. It enters the system with some fictitious currency incorporating important IPPS parameters including processing time and due date and bargains with MAs to purchase their processing capability. These agents aim to achieve their individual objectives so as to minimize the parts' flowtimes and to maximize machine utilization. A contract-net based negotiation protocol is introduced to coordinate their negotiation. A hybrid MAS architecture using Hybrid-based Agent Negotiation (HAN) approach is then proposed to improve the global objectives of IPPS. HAN is similar to MAN except that a supervisory agent (SA) is added. The primary role of the SA is to observe and guarantee the global objectives which are neglected in MAN. The SA can access and intervene in the local decisions made by the local agents. A hybrid contract net negotiation protocol is established to facilitate negotiations in HAN. Dynamic process planning and rescheduling problems have also been addressed. Online Multi-Agent Negotiation (oMAN) and Online Hybrid-based Agent Negotiation (oHAN) are established to solve the dynamic IPPS problems based on MAN and HAN respectively. Two types of disturbances (machine breakdowns and rush order arrivals) are investigated. A simulated manufacturing system is established to evaluate the effectiveness of MAN and HAN and oMAN and oHAN approaches. Simulation results show that the performance of these methods exceeds that of an evolutionary algorithm in general. On the other hand, in terms of achieving the global objectives, the hybrid approaches HAN and oHAN are the most effective, outperforming MAN and oMAN respectively. Finally, a search-based Ant Colony Optimization (ACO) algorithm is proposed and is incorporated into the established MAS platform. Artificial ants are implemented as software agents. A graph-based solution method is pr