Development of dynamic programming algorithm for maintenance scheduling problem - Zafira Adlia, Mohd Fauzi (2020)
Maintenance is one of the important methods that can be used to ensure machines and equipment can operate at the best condition. Maintenance schedule is one of the maintenance management and planning methods that can be used to organize and coordinate timely maintenance work. What, when, where and how the certain operation will be done will be stated to make sure that the planned activity is going smoothly without any delays. However, the uncertainty that happened during maintenance or inspections will affect the original schedule and lead to delays or suspension of the task that had been scheduled. Thus, the original schedule proposed will be useless and rescheduling needs to be done. The objectives of this research are to develop a dynamic programming algorithm for the maintenance scheduling problem that can deal with the uncertainty and to determine the optimum maintenance schedule that will change according to the uncertainty that happened. This research starts with reviewing the previous researches to find the gap in knowledge and find the possible solutions of the gap found. Then, the data of the maintenance team from one of the utilities provider company in Malaysia was collected to be implemented in the development of a dynamic programming algorithm. The dynamic programming model developed for this research reflected the flow of the maintenance activity of the company and implemented the model by Lieberman and Hillier (2010). Then, from the model developed, a formulation was created based on the problem of the maintenance schedule proposed. This model was then simulated using the data collected to verify whether the model was operating effectively and can be used to achieve the objective of this research. Once the model was developed, the calculations to determine the optimum maintenance schedule were done using the dynamic programming formulation created for this maintenance scheduling problem. The calculation was done using the Microsoft Office Excel software and the schedules for each maintenance team obtained were displayed in the result section. The model was then tested by the assumptions to verify that the model can reschedule after dealing with the uncertainty. The dynamic programming model developed was capable to produce the possible combinations and is flexible enough to deal with the uncertainties during the maintenance activity by increasing the choice of scheduling varieties according to the preference of the research which was to minimize the total time of the maintenance schedule. Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. The optimum maintenance schedule was then generated by comparing all of the total time of all the possible outcomes and selecting the most minimum total time which simultaneously will reduce the cost to pay for the extra working hours of the teams involved.