Preventive Maintenance of Complex Assets in Continuous Operating Mode

Abstract

Today, the ability to maintain a continuous complex system operation is viewed as a key attribute for ensuring uninterrupted revenue contribution and the survival of a business. Complex assets consist of many different components working together. Each of the components is important in relation to the operation and performance of the whole asset. Examples of complex assets include aircraft, power generation plants and production lines. When one of the components in a complex asset is removed from service due to maintenance, it may cause failure of operation of the whole or part of the asset.

Many industrial organisations have come to understand that by having an effective maintenance plan, a system's efficiency and reliability can be improved. At the same time, costs can be minimised. Unless failure modes are carefully considered, the replacement of components or breakdown can lead to the shutdown of the whole system. Failure modes vary depending on the configuration of components and subsystems in the system. Some failure modes do not need complete stoppage of the system, but a good portion of failure modes also require switching off the system for urgent repairs. Hence, if failure modes are not evaluated and identified, maintenance activities could not be planned properly, resulting in the shutdown of the entire system and causing significant maintenance costs. Therefore, preventive maintenance should be developed for complex multi-component systems, considering failure modes.

This research aims to explore the preventive strategy to manage maintenance service for complex assets in continuous operating mode. The research examines models of asset failure modes to investigate methods and algorithms for optimising preventive maintenance costs and operational continuity of the asset. The novelty of this research is based on using Failure Modes and Effects Analysis (FMEA) to investigate and develop a holistic preventive maintenance schedule for a complete system that will ensure continuity of production output while maintaining a high level of system reliability, ensuring the availability of necessary inventory and minimising the total maintenance costs. A system can be modelled as a series and parallel arrangement of subsystems and components, and failure of different components of the system can be determined from their life expectancy. Using FMEA modeling, it becomes possible to identify FMEA blocks and develop a preventive maintenance strategy to help select an optimal replacement interval. Unlike the previous studies in the literature review, our approach includes using a group replacement strategy in the form of matrices to treat the components separately. Subsequently, we integrate these treated components according to the FMEA Block. This novel method allows us to address the reliability of the complete complex system with multi-nonidentical components more effectively.

Using FMEA to analyse system failures due to components, subsystems, parts and functions, planned stoppages of parts of the system can be scheduled to maintain revenue generation production and minimise overall maintenance costs. The research will examine influential factors such as reliability of complete system, failure rate, spare parts stock level, spare parts lead time, repair sequences and breakdown costs due to different failure modes. A new PM methodology for continuous operation will be developed to allow general application to any form of complex systems and at every step of the process starting from conceptualization to technological upgrades. The proposed approach is applied to production system and the effects of failure on overall system reliability, changing lead time, preventive replacement intervals, and production lost costs on the optimal policy are examined. The approach is also generalised the preventive maintenance methodology, which includes spare parts inventory management, to a different scenario, specifically a complex CNC system. It can not only improve system reliability and minimise cost of replacement components, but also maintain the continuity of the system’s outputs.