Adaptive Age Replacement Using On-Line Monitoring

Age replacement is one of the most used maintenance policies based on preventive action in order to prevent the failure of a system. Age replacement means that a system is replaced at failure or at a specified replacement age, whichever occurs first. In current age replacement policies, the replacement age is identified without consideration of the effects from operating conditions. However, the lifetime of a system may be affected by various operating conditions, such as the surrounding environment and the operators. In such cases, the replacement age of the system should differ for different situations. Thanks to the improvement of information communication technology, various information about the systems operating conditions can be obtained via the on-line monitoring. This research proposed an adaptive age replacement policy for systems under variable operating conditions using a cumulative exposure model. Based on the on-line information, we proposed a new time-scale instead of the age with consideration of operating conditions. Next, the new time-scale is used to determine the optimal replacement interval which will minimize the average maintenance cost per unit time (also known as cost rate). Some numerical examples are carried out in order to illustrate the proposed adaptive age replacement policy. The optimal age replacement policy considering the operating conditions reduces the total maintenance costs and enhances the effective maintenance plan for systems operating under various conditions.