Two types of learning effects on maintenance activities

This paper proposes an opportunistic maintenance policy for the multi-unit series production system, which is on the basis of the failure rate analysis. When system halts for performing preventive maintenance or opportunistic maintenance, the alternative decision of replacement and repair is made by economic evaluation of two types of maintenance actions. The optimal preventive maintenance plans in a finite time horizon can be obtained by adjusting the preventive and opportunistic maintenance threshold. A numerical example is given for illustrating the applications of the policy.

In this chapter maintenance concept is defined and maintenance types are classified with regard to implementing maintenance policies toward preventive maintenance. Especially achieving planned maintenance policies toward preventive (planned) maintenance and condition based maintenance policies toward predictive maintenance is taken into consideration primarily. Maintenance concept is defined and maintenance types are classified. Due care is given for ‘Preventive Maintenance’ in this chapter. In general ‘Maintenance’ term could be defined as; The integration of all possible technical and administrative actions, including planning, supervising, monitoring and controlling toward retaining an item, a system, a machine to restore their original functional state in which they can perform the intended functions. In addition maintenance, include protective and corrective actions to keep the plant operational system in intended conditions or to maintain the acceptable manufacturing conditions. Optimum maintenance policies aims to sustain system reliability and robustness within minimum cost. In line with the progress of industry, increase in the system, material and manpower costs, increasing demand for robustness and the complex structure of the machines increases also the importance of maintenance policies. Maintenance types could be divided into two main parts namely; 1. Preventive Maintenance, 2. Corrective Maintenance. Preventive Maintenance is also classified into following sub groups; 1.a- Planned Maintenance, 1.b- Predictive Maintenance, 1.c- Advanced Maintenance Implementations; 1.c.1 Reliability Centered Maintenance 1.c.2 Risk Based Maintenance. All of these maintenance types elaborated with relevant figures in the chapter. In this chapter Comparison of Planned and Unplanned (corrective) Maintenance (With regard to transaction and output) is defined with a table. Additionally, Comparison of Planned and Unplanned (corrective) Maintenance (With regard to infra structure) is also tabulated. ‘Benefits of Preventive & Predictive Maintenance’ and ‘Predictive Maintenance Methods’ are defined with relevant descriptive figures in the chapter. For Corrective Maintenance, basic definitions and corrective maintenance steps, types of corrective Maintenance, improvement strategies in corrective maintenance effectiveness are also given. In the final part of ‘Results and conclusions’ expected and verified benefits of implementing maintenance policies for planned and predictive maintenance are explained. Comparisons in some maintenance policies is given.

This paper presents a novel reliability-centered multilevel maintenance optimization model tailored for multicomponent systems subjected to stochastic dependent (s-dependent) competing risks (CRs). Four types of maintenance actions, including minimal repair (MR), medium preventive maintenance (MPM), overhaul preventive maintenance (OPM), and preventive replacement (PR), are incorporated into the development of the multilevel maintenance model. The Copula function is utilized to quantify the s-dependence among failure risks, and subsequently, all unknown parameters are estimated via the inference function for margins (IFM) method. Three types of decision variables are designed to minimize the long-run expected cost rate of the system. Finally, sequential decision process method is utilized to solve the model, and a numerical example of a metro door system illustrates the effectiveness of our proposed model.

This study explores the feasibility of applying an integrated inventory model with the consideration of incorporating production programs and maintenance to an imperfect process involving a deteriorating production system. The main target of this research is to build an integrated inventory model with the issues of backorder and repair. Additionally, our proposed model tries to provide an optimal number of shipments m and lower cost. Furthermore, this article offers the detailed discussion of two preventive maintenances of the production run period which are named as perfect preventive maintenance and imperfect preventive maintenance. Also, in this study, we develop various special cases that consider the failure rate such as Weibull, geometric and learning effect. Based on the results, the demand and production ratio influences the holding cost and purchase cost and has the highest impact on the integrated model.

This paper studies the problem of multi-stage preventive maintenance (PM) optimization on the basis of reliability thresholds. According to the change rule of product's failure rate and by means of setting the reliability thresholds, the replacement cycle is divided into three maintenance stages, they are: (1) Stage I: do not carry out PM; (2) Stage II: carry out periodic PM; (3) Stage III: carry out sequential PM. In each stage, the failures are restored with minimal repair. Age reduction factor and quasi-renewal coefficient are adopted to derive the recursive relations of failure rate function in each stage. A multi-stage PM optimization model is established based on the reliability thresholds, with the aim to minimize the equipment's expected cost rate. Taking the gearbox, rotor and bearing of wind turbine as an example, a case study is conducted to illustrate the effectiveness of the proposed method.

An inspection & imperfect maintenance model for a system with two competing failure modes

In this paper, an imperfect preventive maintenance model with two modes of failures is proposed and analyzed for the deteriorating system. We introduce the concept of two modes of failures: maintainable and non-maintainable. The deteriorating system experiences minimal repair when the system fails and experiences preventive maintenance at a periodic interval. The hazard rate of maintainable failures is reduced by preventive maintenance, but the hazard rate of non-maintainable failures isn't changed by preventive maintenance. Therefore, the preventive maintenance is imperfect. Generally, it is assumed that the dependence of two modes of failures is independent, but, in fact, the maintainable failure is influenced by the non-maintainable. The paper considers the dependence of two modes of failures and introduces the doubly stochastic Poisson in order to describe the dependence of two modes of failure. The optimal interval between the preventive maintenance and the optimal number of preventive maintenances are determined for minimizing the expected cost rate. Finally, the feasibility of model is illustrated by a numerical example.

The Kentucky Transportation Cabinet’s (KYTC) bridge inventory is rapidly aging. As such, the Cabinet needs to identify and implement relevant preventative maintenance (PM) actions to extend the useful service lives of those structures. Maintenance actions, costs, and application interval/repair durability information have been obtained for both cyclical and condition-based bridge PM. Additionally, information rehabilitation actions were acquired from a regional Department of Transportation (DOT) survey and from other literature. As part of this study, the Kentucky Transportation Center (KTC) researchers monitored a KYTC bridge washing project to assess its level of effectiveness and to identify potential improvements. Based upon these tasks, recommended guidance was provided to KYTC for use when implementing bridge PM programs. The guidance includes a discussion of critical PM activities, strategies to adopt training and work documents (i.e., special notes) for contract work, and the implementation of work standards/special operating procedures for work performed by KYTC personnel. This report also includes details on the tools and training KYTC district-level personnel will need and outlines a roadmap for conducting pilot programmatic PM work in several districts.

PurposeThis paper aims to propose an approach for the optimization of imperfect preventive maintenance and corrective actions performed on a single machine. After maintenance, the machine returns to an age between “as good as new” and “as bad as old”.Design/methodology/approachThe approach is based on fuzzy logic and simulation‐based optimization. Fuzzy logic is preferred over crisp logic because it is relatively easy to implement in this situation considering that the human factor is hardly interpreted by analytical methods because of its unpredictable nature. Simulation‐based optimization is used to have a more reactive and accurate tool for practitioners.FindingsTaking into account the impact of the imperfections due to human factors, the period for preventive maintenance, which minimizes the expected cost rate per unit of time or maximizes the availability of the system, is evaluated by the simulation‐based optimization.Research limitations/implicationsDifferent and more realistic maintenance levels must be considered and the traceability of a specific system could be used to determine the most appropriate failure law. For this study, cost reduction was considered as the priority, but the model can be adjusted according to the user's preferences.Practical implicationsThis paper considers a single repairable machine as a system that undergoes periodic preventive and corrective maintenance actions. Considering maintenance imperfections, rule‐based fuzzy logic can be integrated into the maintenance program to determine the times for the periodic preventive maintenance actions.Originality/valueConsidering human factors in maintenance programs is indispensable to assure more accurate and realistic results. However, due to the difficulty engendered by their modeling, most theoretical maintenance models do not consider these factors. Therefore, the proposed fuzzy model in the paper can be an important tool to include them.

The paper aims to bring out the profit analysis of a system with cold standby redundancy of two identical units. In the system, we keep one unit in working and the other is to back up the operation. The system requires preventive maintenance after a specific time. The server has the dual role to carry out repair activities in terms of preventive maintenance and repair of the failed unit. In addition to that, the server is allowed to take rest after each repair. There is no need of rest of the server after preventive maintenance. The provision of priority has been made for the preventive maintenance over repairs. The repairs are done to increase the efficiency and productivity level of the system. The failure rate follows exponential distribution while repair time, rest time of the server and preventive maintenance rate follow arbitrary distributions. The significant reliability characteristics including MTSF, long run availability, server busy time due to repair & preventive maintenance, expected number of repairs, expected number of preventive maintenances per unit time and profit function are obtained using the usual stochastic processes approach. For particular values of the parameters, the revenue per unit up-time and cost functions related to repair activities are considered to carry out the profit analysis of the system model. The results are shown graphically and numerically to highlight the effect of different parameters on some significant reliability characteristics

This paper deals with minimal repair and sequential imperfect preventive maintenance (imperfect PM) for a fishing vessel. Failure that occur at random times rectified by minimal repair, result minimal repair cost. We add the downtime cost to modify the cost model previously discussed by Jiang and Murthy (2008). That cost is intended as a cost of losses when the vessel is being repaired. Because of the time value of money, each cost should be subject to interest rate. The performance measure is the minimization of the expected total maintenance cost during a certain period. The decision variables are the number of imperfect PM and the level of preventive actions. We assume the distribution of first failure rate is Weibull and follows a nonhomogeneous Poisson process (NHPP). We give the comparison of maintenance costs between the cost resulting from our model and that from the previous model. The previous model is nested in our model and the result shows that in our model a higher interest rate will increase the maintenance cost.

PurposeThis study focuses on the application of reliability-centered maintenance (RCM) to a textile industry steam boiler. The study aims to demonstrate the development and application of RCM to a steam boiler used in the textile industry.Design/methodology/approachRCM is a structured process that develops maintenance activities needed on physical resources in their operational environment to realize their inherent reliability by logically incorporating an appropriate mixture of reactive, preventive, condition-based and proactive maintenance methods. A detailed analysis of the RCM approach is presented to develop preventive maintenance (PM) program and improve the reliability and availability of the steam boiler system.FindingsThe research reveals that the identification of PM tasks is a good indicator of the PM program's efficiency and can serve as an important maintenance-related downtime source. It is also discovered that the majority of maintenance programs that claim to be proactive are, in fact, reactive. This article also shows how RCM may be successfully implemented to any system, resulting in increased system reliability.Research limitations/implicationsThe paper focuses on a pilot study of the development and implementation of the RCM technique to a textile industry steam boiler. It is suggested that the developed RCM model can be applied to the entire plant.Originality/valueThe paper presents a comprehensive RCM model framework as well as an RCM decision framework, providing maintenance managers and engineers with a step-by-step approach to RCM implementation. The proposed framework is significant in that it may be utilized for both qualitative and quantitative analysis at the same time.

In semiconductor manufacturing, preventive maintenance (PM) activities are typically scheduled via a two tier hierarchical decomposition approach. The first decision tier determines a PM cycle plan while the second tier schedules these planned events into the manufacturing operations. Following recent work based on the use of G/G/m queueing approximations for PM planning, we develop a method to allow for multiple PM cycles in a tool set. We formulate a nonlinear program with the PM cycle durations as continuous decision variables with the objective of minimizing the mean cycle time. We examine certain special cases and characterize the optimal solutions. Numerical studies are conducted with realistic multiple PM cycle data to assess the implications of the proposed approach. The results suggest that it may be possible to obtain significant improvements in the overall cycle time performance of tool sets in semiconductor manufacturing relative to existing PM planning procedures.

Economic production lot-sizing for an unreliable machine under imperfect age-based maintenance policy

Maintenance is an important activity in ensuring the machine operation in a company. If maintenance activities are carried out in a planned manner, production activities can run smoothly. This research was conducted in a manufacturing company engaged in the manufacture of paper packaging. Based on the data, Duplex machines have a higher frequency of breakdown compared to other machines, which is 125 times in 22 months. This study aims to implement preventive maintenance of Duplex machines. The analysis starts with determining the critical components on a Duplex machine. Furthermore, the calculation of Mean Time to Failure (MTTF), Cost of Failure (Cf), and reliability. Finally, a preventive maintenance cost calculation (Cp) was carried out to determine the time interval for replacing components at a low cost. After the implementation of preventive maintenance, there were three components that experienced a decrease in maintenance costs. Bearing components experience a cost reduction of 8.30% with a reliability of 61%, chain components have decreased costs by 15.60% with a reliability of 62% and unwinder components have decreased costs by 10.70% with a reliability of 61%. Keywords: Duplex machine, preventive maintenance, MTTF, reliability