A study of the quantitative methods that support RCM operation

This paper investigates each of the quantitative methods that support Reliability Centered Maintenance (RCM) operation. The integration of quantitative methods with RCM activities is an innovative approach since previous RCM methodologies only utilized qualitative methods. A thorough literature review identified ten essential activities that are necessary for the application of RCM along with the respective quantitative methods that support these activities. Furthermore, in-person interviews were conducted at Brazilian manufacturing firms to confirm the actual application of the methods from the literature. These interviews also helped us identify additional methods that these companies use in their manufacturing practices. As a result, a table associating essential RCM activities with their quantitative method counterpart was created, along with a brief description of what each respective quantitative method contributes specifically. Among the quantitative methods evaluated, probability theory was identified as the one that was most commonly associated with RCM activities. The methods of Economic engineering and Monte Carlo simulation were also identified as key contributors since they allowed for more sophisticated analysis related to the cost and performance of production systems subject to maintenance. The use of probability distributions in modeling is important in many RCM activities. Not only should the average values be used, but it is necessary to understand the effects of times to failure and times to repair on time. The Economic engineering methods allowed the analysis of the life cycle costs of machines and equipment. Monte Carlo simulation is capable of analyzing real systems which are essentially stochastic. A more complete view of the equipment and their critical components is provided through the use of blocks diagram and system reliability analysis techniques. The methods of production planning and controlling, such as Manufacturing Resource Planni- g II (MRPII), support the optimal planning of maintenance activities. The stochastic and deterministic models of stocks management optimize storage costs in relation to the cost of lacking spare parts. Indicators specific to maintenance, such as Overall Equipment Effectiveness (OEE) and Total Effective Equipment Performance (TEEP), allow the monitoring of essential variables in the production lines and the calculation of global efficiency. Costing systems such as ABC quantify the productive system costs, which include the maintenance activities. These methods can have an expressive contribution to the RCM operation. The quantitative methods listed improve both the planning and activities control while also reducing costs.