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Maintenance is one of the most important operations in industrial and service systems, which use various types of equipment and machinery in the production of goods and delivery of services. All systems are subject to deterioration with usage and time. As a system deteriorates, its efficiency and productivity decreases. To keep production efficiency high and to maintain good product quality, preventive maintenance is necessarily performed on systems subject to deterioration. The cost of maintenance related activities in industrial facilities has been estimated by Mobley (1990) to be as much as 40% of total costs. Due to increased automation, artificial intelligence, and information technologies, equipment has become more complex and various modes of maintenance activities are implemented by managers to keep them in available state. Basic modes of maintenance include corrective maintenance (CM), which is performed when equipment fails, and preventive maintenance (PM), which is a scheduled maintenance planned in advance. It should be noted that preventive maintenance is different from pre-emptive maintenance. While pre-emptive maintenance plans are considered at the design stage to eliminate the maintenance requirement, preventive maintenance plans are applied during equipment operation in order to eliminate failures.
Optimization of maintenance operations and minimization of related costs has been subject of extensive studies. Literature abounds with many studies in this area. Several applications and case studies show the success of maintenance modeling and analysis in improving system performance and productivity. Chan et al. (2005) discussed issues of total productive maintenance in the context of a case study in electronics industry. Maintenance models for production system with intermediate buffers have been studied by Kyriakidis and Dimitrakos (2006). Leon Hijes and Cartagena (2006) presented a maintenance strategy based on equipment classification using a multi-criterion objective and Carnero (2006) discussed a procedure for setting up a predictive maintenance program using detailed system evaluation. Baraldi et al.(2012) presented a modeling framework for maintenance optimization of electrical components based on fuzzy logic and effective age. A hybrid approach based on Monte Carlo simulation method and fuzzy logic is applied to the problem to evaluate the performance of a given maintenance policy. The proposed methodology is successfully applied to a real case dealing with a medium-voltage test network. Martorella, et al. (2010) presented a maintenance model and optimization by integrating human and material resources. An application case is studied to optimize the maintenance plan of a motor-driven pump equipment by considering maintenance and test intervals and human and material resources as decision variables. Horenbeek et al. (2010) also presented maintenance optimization models and criteria. A literature review on maintenance optimization models, with special focus on optimization criteria and objectives is presented. Factors that have influence on optimization models are made explicit and their links are established. Waeyenbergh and Pintelon (2004) studied a case for maintenance concept development. Wang, et al. (2010) studied a case of condition based maintenance modeling based upon the oil analysis data of marine diesel engines using stochastic filtering. A decision model for optimizing the replacement time of the diesel engines conditional on observed measurements is derived and applied to the case problem. Savsar and Youssef (2004) and Savsar (2005, 2006a, 2006b, 2008, and 2011a) developed discrete mathematical and simulation models to analyze the effects of preventive and corrective maintenance policies on serial production lines and flexible manufacturing systems. A detailed maintenance analysis in the context of a plant has also been presented by Savsar (2011b). Abdulmalek et al. (2012) discusses the effects of maintenance policies on manufacturing productivity. Savsar and Abdulmalek (2012) discuss aircraft maintenance issues in a case application.
Key Terms in this Chapter
Maintenance Frequency: Number of maintenance actions carried out per unit time.
Maintenance: All necessary actions needed to keep a system or a product in service or to restore it into its original conditions for service.
Combined Mean Time Between Maintenances: Average time between maintenances when corrective and preventive maintenances are all considered.
Non-repairable Spares: A spare part that cannot be used when it fails. It has to be replaced by a new spare.
Mean Active Maintenance Time: Average time required to carry out any maintenance action.
Corrective Maintenance: Maintenance actions carried out when equipment fails at a random.
Availability: Percent of time a system or equipment is ready for operation.
Reliability: Probability that a system or a product will perform satisfactorily for a specified period of time under specified operating conditions.
Repairable Spares: A spare part that can be repaired when it fails and reused in the system again.
Preventive Maintenance: Maintenance actions carried out at scheduled times to keep equipment in operational state.