A unified methodology of maintenance management for repairable systems based on optimal stopping theory

This dissertation focuses on the study of maintenance management for repairable systems based on optimal stopping theory. From reliability engineering’s point of view, all systems are subject to deterioration with age and usage. System deterioration can take various forms, including wear, fatigue, fracture, cracking, breaking, corrosion, erosion and instability, any of which may ultimately cause the system to fail to perform its required function. Consequently, controlling system deterioration through maintenance and thus controlling the risk of system failure becomes beneficial or even necessary. Decision makers constantly face two fundamental problems with respect to system maintenance. One is whether or when preventive maintenance should be performed in order to avoid costly failures. The other problem is how to make the choice among different maintenance actions in response to a system failure. The whole purpose of maintenance management is to keep the system in good working condition at a reasonably low cost, thus the tradeoff between cost and condition plays a central role in the study of maintenance management, which demands rigorous optimization. The agenda of this research is to develop a unified methodology for modeling and optimization of maintenance systems. A general modeling framework with six classifying criteria is to be developed to formulate and analyze a wide range of maintenance systems which include many existing models in the literature. A unified optimization procedure is developed based on optimal stopping, semi-martingale, and lambda-maximization techniques to solve these models contained in the framework. A comprehensive model is proposed and solved in this general framework using the developed procedure which incorporates many other models as special cases. Policy comparison and policy optimality are studied to offer further insights. Along the theoretical development, numerical examples are provided to illustrate the applicability of the methodology. The main contribution of this research is that the unified modeling framework and systematic optimization procedure structurize the pool of models and policies, weed out non-optimal policies, and establish a theoretical foundation for further development

Optimal Overhaul-Replacement Policies for Repairable Machine Sold with Warranty

This research deals with an overhaul-replacement policy for a repairable machine sold with Free Replacement Warranty (FRW). The machine will be used for a finite horizon, T (T <ï‚¥), and evaluated at a fixed interval, s (s< T). At each evaluation point, the buyer considers three alternative decisions i.e. Keep the machine, Overhaul it, or Replace it with a new identical one. An overhaul can reduce the machine age virtually, but not to a point that the machine is as good as new. If the machine fails during the warranty period, it is rectified at no cost to the buyer. Any failure occurring before and after the expiry of the warranty is restored by minimal repair. An overhaul-replacement policy is formulated for such machines by using dynamic programming approach to obtain the buyer's optimal policy. The results show that a significant rejuvenation effect due to overhaul may extend the length of machine life cycle and delay the replacement decision. In contrast, the warranty stimulates early machine replacement and by then increases the replacement frequencies for a certain range of replacement cost. This demonstrates that to minimize the total ownership cost over T the buyer needs to consider the minimal repair cost reduction due to rejuvenation effect of overhaul as well as the warranty benefit due to replacement. Numerical examples are presented for both illustrating the optimal policy and describing the behavior of the optimal solution

Post-Sale Cost Modeling and Optimization Linking Warranty and Preventive Maintenance

Ph.DDOCTOR OF PHILOSOPH

Inventory management in a manufacturing/remanufacturing hybrid system with condition monitoring

Traditional supply chains consist of manufacturers, who process, assemble and sell products to customers. Once the product has been sold, the ownership of the product is transferred on to the customer. Typically after a possible warranty period, the repair, maintenance and eventual disposal of the product is then the responsibility of the customer. The reverse processing activities of inspection, parts remanufacturing, and materials recycling can substantially reduce the material and energy consumed by producing goods. Although these activities have a beneficial environmental impact, customers fail to participate in the remanufacturing efforts by producers or third parties because they often lack incentives. To overcome this drawback, several environmental and economic thinkers have proposed a concept called servicizing . In this paradigm, producers become service providers who provide the use and maintenance of products while retaining ownership; customers become clients who pay fees to receive the benefits the products provide. Instead of extensive buying and disposing of products, servicizing includes the obligation to dispose of used products responsibly, while reusing them and their constituent parts and materials as much as possible. However, because the provider retains responsibility for the product while it is in use by different client firms, the service paradigm also creates the need for better information and communication technology to increase the provider\u27s knowledge of the product condition. Monitoring the condition of the equipment enhances the ability of the service provider to make better replacement decisions (when to replace the product in the fleet to avoid failures) and better inventory management decisions (how much remanufactured stock to maintain so the customer is ensured a working product at all times). This thesis aims at optimizing the replacement and inventory decisions of the service provider in order to minimize the long-run overall cost per unit time

Smart Maintenance Decision Support Systems (SMDSS)

Computerized information systems are used in all contemporary industries and have been applied to track maintenance information and history. To a lesser extent, such information systems have also been used to predict or simulate maintenance decisions and actions. This work details two models, a population data analysis, and a system infrastructure, to aid operations and maintenance managers with the difficult resource allocation decisions they face in the field. The first model addresses the consideration of component dependency for series network connections using a Markov Decision Process model and solution algorithm. The second model addresses the prioritization of maintenance activities for a fleet of equipment using an Analytical Hierarchy Process and solution algorithm. A recurrent event data analysis is performed for a population data set. The final element is the information system architecture linking these two models to a marketing information system in order to provide quotations for maintenance services. The specific industry of interest is the electrical power equipment industry with a focus on circuit breaker maintenance decision actions and priorities and the development of quotations for repair and replacement services. This dissertation is arranged in a three paper format in which each topic is self contained to one chapter of this document

Repair and Replacement Strategy for Optimizing Cost and Time of Warranty Process using Integer Programming

Warranty is an assurance issued by a company as the manufacturer to guarantee that its product is damage-free within a specified period. The warranty process is usually carried out when a complaint or damage regarding the product is received. The warranty process consists of two decisions that the company establishes to handle the process. The occurring problem is in the warranty process; there is not any standard established to determine the cost to incur for the warranty process. In this research, integer programming method was used to do optimization on repair and replacement strategy in warranty process. Before doing optimization, mathematical model must be created. Using that mathematical model, the results show that the costs of the warranty process decrease by 16.97%, while the time increases by 13.9%. So, with this method company will be increase the profit

Risk-Based Decision-Making Modeling for Wastewater Pipes

The dissertation research work described here has three primary objectives under risk-based decision making. (1) The development of a comprehensive sewer pipe condition rating model that incorporates many environmental, structural, and hydraulic parameters. (2) The development of a sewer pipe deterioration model used to predict future overall condition states of the pipe, as well as determining the probability of failure at any given age of the pipe. (3) The development of a comprehensive consequence of failure model that assesses the consequence of sewer pipe failure using economic, social, and environmental cost factors. The Pipeline Assessment and Certification Program (PACP) was developed by the National Association of Sewer Service Companies, the industry-accepted protocol for condition rating sewer pipes in the US. The PACP method relies exclusively on visual inspections performed using Closed-Circuit Television (CCTV), where existing structural and operation and maintenance (O&M) defects are observed by certified operators. A limitation of the PACP method is that it does not use pipe characteristics, depth, soil type, surface conditions, pipe criticality, capacity, the distribution of structural defects, or history of preventative maintenance to determine the condition rating of the sewer pipe segment. Therefore, a comprehensive rating model with pipe characteristics, external characteristics, and hydraulic characteristics was developed. The calculating of a comprehensive rating is an entirely manual process. Therefore, this research work addresses this limitation of Analytical Hierarchy Process (AHP) and suggests AHP is not a suitable method to calculate comprehensive rating. Develops a faster calculation of a comprehensive rating model using and K-NN that incorporates pipe characteristics, environmental characteristics, and information about PACP structural score and PACP O&M score in hydraulic factors. Factors such as pipe age, pipe material, diameter, shape, depth, soil type, loading, carried waste, seismic zone, PACP structural score, and PACP O&M score are used. Our proposed model is applied to the data received from the City of Shreveport, LA, which is currently under a Federal Consent Decree. The results of a comprehensive rating model showed a below-average validity percentage because linear regression assumes a linear relationship between the input and output variables. Still, the relationship between response and the predictor is not linear for AHP to prove AHP is not a suitable method and satisfactory results for K-NN. As part of decision-making, for capital improvement planning and budgeting, the capacity to predict future sewer pipe conditions and potential breakdowns is essential. In contrast to the often-used Discrete Time Markov Chain approaches in the literature, the deterioration model created here uses a Continuous Time Markov Chain method to calculate the likelihood that a pipe will change from a better to a worse condition at given age. The consequence of the pipe\u27s failure is established to ascertain the risk of failure and to create a comprehensive framework for risk-based decision-making. To estimate the impact of the asset\u27s failure, the established consequence of failure model considers a significant number of economic, social, and environmental cost elements. For budgeting future capital projects and improvements, the CTMC model and failure consequences for sewers are useful

Some contributions to modeling usage sensitive warranty servicing strategies and their analyses

Providing a warranty as a part of a product\u27s sale is a common practice in industry. Parameters of such warranties (e.g., its duration limits, intensity of use) must be carefully specified to ensure their financial viability. A great deal of effort has been accordingly devoted in attempts to reduce the costs of warranties via appropriately designed strategies to service them. many such strategies, that aim to reduce the total expected costs of the warrantor or / and are appealing in other ways such as being more pragmatic to implement - have been suggested in the literature. Design, analysis and optimization of such servicing strategies is thus a topic of great research interest in many fields. In this dissertation, several warranty servicing strategies in two-dimensional warranty regimes, typically defined by a rectangle in the age-usage plane, have been proposed, analyzed and numerically illustrated. Two different approaches of modeling such usage sensitive warranty strategies are considered in the spirit of Jack, Iskandar and Murthy (2009) and Iskandar (2005). An `Accelerated Failure Time\u27 (AFT) formulation is employed to model product degradation resulting due to excessive usage rate of consumers. The focus of this research is on the analysis of warranty costs borne by the manufacturer (or seller or third party warranty providers) subject to various factors such as product\u27s sale price, consumer\u27s usage rate, types and costs of repair actions. By taking into account the impact of the rate of use of an item on its lifetime, a central focus of our research is on warranty cost models that are sensitive to the usage rate. Specifically, except the model in Chapter 4 where the rate at which an item is used is considered to be a random variable; all other warranty servicing policies that we consider, have usage rate as a fixed parameter, and hence are policies conditional on the rate of use. Such an approach allows us to examine the impact of a consumer\u27s usage rate on the expected warranty costs. For the purpose of designing warranties, exploring such sensitivity analysis may in fact suggest putting an upper limit on the rate of use within the warranty contract, as for example in case of new or leased vehicle warranties. A Bayesian approach of modeling 2-D Pro-rated warranty (PRW) with preventive maintenance is considered and explored in the spirit of Huang and Fang (2008). A decision regarding the optimal PRW proportion (paid by the manufacturer to repair failed item) and optimal warranty period that maximizes the expected profit of the rm under different usage rates of the consumers is explored in this research. A Bayesian updating process used in this context combines expert opinions with market data to improve the accuracy of the parameter estimates. The expected profit model investigated here captures the impact of juggling decision variables of 2-D pro-rated warranty and investigates the sensitivity of the total expected profit to the extent of mis-specification in prior information