Preventive maintenance has been well-recognised as an essential tool for productivity, quality and efficiency in manufacturing. There has been an increasing interest to explore the impact of incorporating preventive maintenance under various scenarios commonly encountered in manufacturing environment. However, besides integrating the preventive maintenance into manufacturing operations, it is also important to adopt a sound preventive maintenance strategy. This research discusses a new policy for scheduling jobs and preventive maintenance operations on a single machine. The proposed policy explores an option of procrastinating the preventive maintenance operations when they are due versus delaying these preventive maintenance operations with an additional requirement to carry out these maintenance operations at later times when it is opted to delay the preventive maintenance operations. The minimisation of the total completion time is considered as a performance measure. The problem is identified NP-hard. The properties of an optimal schedule are identified and a single pass heuristic algorithm is proposed using these properties. Two metaheuristics, tabu search and simulated annealing are also developed using the aforementioned properties. A lower bound is suggested in order to analyse the performance of the proposed heuristics in a numerical experimentation with randomly generated large size problems. The study shows that the performance of the single pass heuristic and the lower bound is sensitive to the maintenance related parameters. It is also reported that the metaheuristics outperform the single pass heuristic as well as are the most robust and efficient methods to solve the problem.
- Inderscience Publishers
- A new policy for scheduling maintenance on a single machine
Power and policy in floodplain management, drawing on research in Alberta, Canada
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Science for Environment Policy
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Science for Environment Policy
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