Optimising System Continuity in Preventive Maintenance Schedules Based on Integrated Failure Mode and Spare Part Inventory Modelling

Systems with multiple components and various configurations are classified as complex. Unless failure modes are carefully considered, the replacement of components or breakdown can lead to the shutdown of the whole system. Because of this, maintaining a complex system output can be challenging, especially if the right preventive maintenance schedule is not determined. In order to support replacement activities, a sufficient supply of spare parts is required. Based on the failure mode identified and effects analysis, this research presents an integrated preventive maintenance scheduling methodology for complex systems. Components and subsystems in the system can be modelled, such that failures in different parts of the system can be predicted based on expected life. To maintain a high level of production during PM, the need to analyze failure modes that result in only partial system failures is necessary. For determining the required number of spare parts, we factor in preventive replacements for each FMEA block. Optimal replacement intervals and spare part quantities are determined using the genetic algorithm. In order to demonstrate the application of the proposed method, numerical experiments are conducted. The developed method in this paper not only improves system reliability and minimises costs but also maintains the continuity of system outcomes during replacement activities.