PurposeThe purpose of this paper is to present models and practical procedures for the analysis of maintenance operations and development of maintenance policies in the context of an oil filling factory. Basic maintenance models, maintenance policy selection and optimum spare part quantity determination procedures are illustrated with a specific case application in a factory.Design/methodology/approachMaintenance formulas are constructed and applied in a factory to determine down time due to various types of failures and maintenance practices in the system. Based on the analysis of the current system, a new preventive maintenance policy is proposed and its effect on reducing down time due to random failures is estimated by using the formulation developed. Procedures for spare part requirements and optimum order quantities with respect to total costs are outlined for critical spares.FindingsModels and case study results presented in this paper demonstrate that selection of appropriate maintenance policy and optimum spare part order quantities should be based on scientific procedures since the results can significantly affect system performance.Research limitations/implicationsThe results obtained in this paper are specific to the case application. However, the models and procedures presented are general and can be applied to any similar problems.Practical implicationsFormulations and procedures outlined in this paper can be used to determine effects of various types of maintenance activities and related policies on system performance. They can be valuable tools for maintenance engineers and operational managers in improving system productivity.Originality/valueThe paper considers a management problem related to maintenance policy selection and spare part order quantity determination in a factory. Detailed procedures outlined in this paper can be highly valuable tools for maintenance managers.
Flexible manufacturing Systems (FMSs) typically operate at 70-80% utilization, which is much higher than the utilization of traditional machines that can operate with as low as 20% utilization. A result is that an FMS may incur four times more wear and tear than a traditional system. This requests the execution of effective maintenance plans on FMSs. While maintenance actions can reduce the effects of breakdowns due to wear-outs, random failures are still unavoidable. It is important to understand the implications of a given maintenance plan on an FMS before its implementation. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on the performance of an FMS. The FMS performance is measured by its operational availability index, which is determined using the production output rate of the FMS under a variety of time between failure distributions and different operational conditions. The effects of various maintenance policies on FMS performance are simulated and the results are compared to determine the best policy for a given system.
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