A Rule Based System for Reliability Centered Maintenance

In order to achieve failure free functionality of heavy plant equipment, reliability centered maintenance technique is used which has its own limitations, such as tedious preventive maintenance tasks and significant start up costs. Moreover, previous method uses cased based reasoning which does not work when two or more cases conflict and no or an inapplicable solution is provided to the problem. We resolve the issue by incorporating the rule based reasoning in order to achieve performance indicators for the plant management. Our approach not only reduces repeated tasks but also helps in predicting failure in the equipment. For this purpose, we use artificial neural networks. The overall objective of this work is to improve the analysis efficiency of reliability centered maintenance without trading off its quality.