Single Machine Scheduling with Breakdown and Maintenance

• Main Authors: Chen Wen-Jinn, 陳文進
• Other Authors: 廖慶榮
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/18018658154953019328

博士 === 國立臺灣科技大學 === 工業管理系 === 90 === Most scheduling models assume that machines are available at all times. However, this assumption may not be true in real industrial settings. For example, a preventive maintenance activity is required or a machine breakdown occurs. In many industries, machine breakdowns are found prevalently and make the shop behavior hard to predict, and thereby reducing the efficiency of the production system. Therefore, how to schedule maintenance to reduce the breakdown rate has been recognized by the decision makers. In this thesis, we address the single machine scheduling problem with breakdown and maintenance. In particular, three related problems are discussed as follows: 1.Based on the experience of the studied company, a longer idle time can reduce the breakdown rate when machine is running without stopping for a long period of time (i.e. a heavy load). Thus, a heuristic is proposed to maximize the total setup time (or the total idle time). The proposed heuristic is evaluated by using the branch-and-bound algorithm. 2.In many manufacturing systems, maintenance has been scheduled regularly or periodically. Therefore, we need to develop scheduling method to deal with systems with periodic maintenance. A heuristic is proposed to solve the scheduling problem with nonresumable jobs. The objective is to minimize the maximum tardiness subject to periodic maintenance. Computational results based on real industrial data are provided to demonstrate the effectiveness of the heuristic. 3.Under different maintenance circumstances, we develop six algorithms to improve the EDD method used by the studied company. The problem under consideration is to find a schedule that minimizes the number of tardiness jobs subject to one maintenance. The improvement ratios of the six algorithms are shown in this thesis. Computational results are provided to demonstrate the effectiveness of the algorithms.