Non-periodic Preventive Maintenance Research Articles

Non-periodic preventive maintenance policies for complex multi-component products sold with loss-based two-dimensional warranties

Multi-component characteristics of complex industrial equipment, such as complex structures and stochastic dependencies, complicate analyzing the failure characteristics of such products and developing effective strategies to reduce warranty costs. In addition, a substantial customer loss or service interruption owing to the shutdown of these products forces manufacturers to formulate warranty contracts while considering customer loss. From the manufacturer’s perspective, with the aim of reducing the warranty costs while restraining the costs of customer loss, we propose the following two novel types of non-periodic imperfect preventive maintenance (PM) policies: unified and customized. The proposed PM policies simultaneously take into account the effects of customer usage rate heterogeneity and product deterioration on product failure. We characterize the failure relationship between the product and corresponding components based on the reliability block diagram and the Type I failure dependency model, and further construct the decision models for the proposed PM policies. The properties of the decision models are provided for certain special cases and are further used to design an algorithm for a general case. A comparison of the results of the numerical examples reveals the following: (1) Providing PM policies is beneficial for both the warranty providers and customers. The proposed PM policies are better than traditional periodic PM policies when shutdown loss costs are considered. (2) The stochastic dependencies will increase the costs of both the warranty and shutdown loss. It is necessary to take into account the stochastic dependencies of multi-component products when analyzing the warranty costs and formulating relevant decisions. (3) Beyond formulating effective PM policies, the manufacturer can mitigate the warranty cost pressure by adjusting the warranty coverage based on market information, or improving product reliability.

Optimal production and non-periodic maintenance plan for a degrading serial production system with uncertain demand

Over the past few decades, economic globalisation has intensified the competition among international enterprises. So, firms are working hard to improve their performances to stay competitive in markets. In the industrial domain, firms are continuously looking for the improvement of their production systems’ availability and the optimisation of production planning to assure the satisfaction of a random demand. Therefore, joint maintenance and production optimisation have been receiving increasing attention from researchers and firms. This study deals with joint nonperiodic preventive maintenance and production planning optimisation with regard to a manufacturing system composed of several machines mounted in series. The relationship between failure rate and production is considered to indicate the influence of variation of the production rate on the failure rate along with the average number of failures. The non-periodic preventive maintenance with respect to the production planning is proposed, to assure the continuity of the machines’ reliability by minimising the failures. In this paper, a mixed-integer-linear programme is developed to jointly find the optimal planning of integrated non-periodic preventive maintenance to production by minimising the total cost. Experimental results are presented to study the impact of the failure rate threshold on the number and periods of preventive maintenance actions.

Adaptive Preventive Maintenance for Flow Shop Scheduling With Resumable Processing

In this article, we focus on a joint scheduling problem that considers the corrective maintenance (CM) due to unexpected breakdowns and the scheduled preventive maintenance (PM) in a generic $M$ -machine flow shop. The objective is to find the optimal job sequence and PM schedule such that the total of the tardiness cost, PM cost, and CM cost is minimized. Currently, most existing studies on the PM schedules are based on a fixed PM interval, which is rigid and may lead to poor performance, as the fixed strategy fails to effectively balance the trade-offs between the production scheduling and maintenance. To address this critical research issue, our novel idea is to dynamically update the PM interval based on the real-time machine age, such that the maintenance activity coordinates with the job scheduling to the maximum extent, which results in an overall cost saving. Specifically, a correction factor is introduced to dynamically update the PM interval and to help evaluate whether it is worthwhile to process the job first at the risk of the CM before performing the PM action. To demonstrate the effectiveness of the adaptive strategy, simulations and a case study on mining operations are conducted to show that the adaptive strategy outperforms the existing methods with a less total cost. Note to Practitioners —This article is motivated by the critical problem of balancing the trade-offs between production scheduling and maintenance in a flow shop production line, where jobs are processed on the machines in the same route. On the one hand, production scheduling aims to meet the customer demands on time. On the other hand, the maintenance actions help restore the machines’ reliability by reducing the machine failure rate. Most existing approaches to scheduling the PM are based on the fixed PM interval, which is rigid and may lead to poor performance. Although the nonperiodic PM interval strategy has been proposed in the literature for production scheduling, it still does not consider the adaptive PM strategy in the context of flow shop scheduling with multiple machines. To fill this literature gap, in this article, we first model a generic $M$ -machine flow shop considering both the CM and PM. Then, we suggest a new adaptive and easy-to-implement approach to dynamically update the PM interval and improve the decision-making on the PM schedules. Compared with the conventional maintenance policy, the adaptive one greatly reduces the total cost in real-time scheduling.

Bi-objective optimization of non-periodic preventive maintenance strategy by considering time value of money

Recently, design of preventive maintenance (PM) policies during the warranty period has attracted the attention of researchers. The methods mainly design warranty servicing strategies in a way that reduce the cost imposed on the manufacturer without considering the impact of customer dissatisfaction. While dissatisfaction with a product is an important issue which may result in the loss of potential buyers and switching existing buyers to competitors. Therefore, this study develops a bi-objective model which simultaneously minimizes the manufacturer and the buyer cost under a Non-homogeneous Poisson Process framework. Also, a non-periodic preventive maintenance strategy is presented in which PM actions are performed at discrete time instants in a way that the expected number of failures remains a constant value over all PM intervals. Furthermore, it is a known fact that the value of money reduces over time due to different reasons and has a significant impact on long-term contracts. Since PMs and repairs are conducted at different times, the time value of money is considered to estimate the cost more accurately. A comparative study is conducted to support this claim that the presented non-periodic reliability-based PM policy has a better performance in comparison with a periodic PM policy.

On determining a non-periodic preventive maintenance schedule using the failure rate threshold for a repairable system

Maintenance activities are regarded as a key part of the repairable deteriorating system because they maintain the equipment in good condition. In practice, many maintenance policies are used in engineering fields to reduce unexpected failures and slow down the deterioration of the system. However, in traditional maintenance policies, maintenance activities have often been assumed to be performed at the same time interval, which may result in higher operational costs and more system failures. Thus, this study presents two non-periodic preventive maintenance (PM) policies for repairable deteriorating systems, employing the failure rate of the system as a conditional variable. In the proposed PM models, the failure rate of the system was restored via the failure rate reduction factors after imperfect PM activities. Operational costs were also considered, which increased along with the operating time of the system and the frequency of PM activities to reflect the deterioration process of the system. A numerical example was provided to illustrate the proposed PM policy. The results showed that PM activities performed at a low failure rate threshold slowed down the degradation of the system and thus extended the system lifetime. Moreover, when the operational cost was considered in the proposed maintenance scheme, the system replacement was more cost-effective than frequent PM activities in the severely degraded system.

최소 신뢰도를 보장하는 비 주기적 예방보전 모형 개발

최소 신뢰도를 보장하는 비 주기적 예방보전 모형 개발

On Determination of the Non-periodic Preventive Maintenance Scheduling with the Failure Rate Threshold for Repairable System

Determination of a preventive maintenance scheduling is regarded as a key part in manufacturing system to maintain the equipment in good condition. In practice, many preventive maintenance policies is used in manufacturing system to reduce the unexpected failures and increase sustainability of system. In this paper, the failure rate of system is used as a condition variable and a decision variable, and preventive maintenance policy is then developed for minimizing the expected maintenance cost rate. The imperfect preventive maintenance activities of the proposed models are modeled via the arithmetic reduction model which uses the age reduction factor or the hazard reduction factor. The results of the numerical example shows that the model based on age reduction can not only extend the system lifetime but also reduce the expected maintenance cost rate although the preventive maintenance cost is significantly higher than those of the model based on hazard reduction.

A customized two-dimensional extended warranty with preventive maintenance

This study proposes a customized two-dimensional extended warranty policy, in which customers are classified into three categories with different operating conditions according to their maintenance records in the basic warranty period, and then different preventive maintenance (PM) schedules are applied to customers in the different categories. This study investigates the effects that the classification of a customer and the time-usage ratio of the repairable deteriorating product have on breakdowns of such a product to effectively manage the total costs within the extended warranty period. Periodic and non-periodic preventive maintenance programs are both considered to meet different customer requirements to ensure that product reliability would not be gradually unacceptable. By adopting the proposed extended warranty approach, customers with high utilization rates could have satisfactory reliability on their products by performing more frequent PM activities, while those with low and average utilization rates could reduce the cost of PM within the extended warranty period, and also enjoy acceptable product availability. The results show that the classification of customers into different categories cannot only be beneficial by providing an effective mechanism to reduce the warranty costs, but also be a valuable competitive marketing strategy for product providers.

Integrated preventive maintenance and production decisions for imperfect processes

This paper integrates production, maintenance, and quality for an imperfect process in a multi-period multi-product capacitated lot-sizing context. The production system is modeled as an imperfect machine, whose the status is considered to be either in-control or out-of-control. When the machine is out of control, it produces a fraction of nonconforming items. During each period, this machine is inspected and imperfect preventive maintenance activities are simultaneously performed to reduce its age, proportional to the preventive maintenance level. The objective is to minimize the total cost, while satisfying the demand for all products. Our optimization model allows for a joint selection of the optimal values of production plan, and the maintenance policy, while taking into account quality related costs. A solution algorithm is developed and illustrative numerical examples are presented. It is found that the increase in PM level leads to reductions in quality control costs. Furthermore, if the cost of performing PM is high to the point where it is not compensated for by reductions in the quality related costs, then performing PM is not justifiable. Finally, using non-periodic preventive maintenance with the possibility of different preventive maintenance levels may result in an improvement of the total cost.

An optimal dynamic interval preventive maintenance scheduling for series systems

This paper studies preventive maintenance (PM) with dynamic interval for a multi-component system. Instead of equal interval, the time of PM period in the proposed dynamic interval model is not a fixed constant, which varies from interval-down to interval-up. It is helpful to reduce the outage loss on frequent repair parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency, when compared to a periodic PM scheme. According to the definition of dynamic interval, the reliability of system is analyzed from the failure mechanisms of its components and the different effects of non-periodic PM actions on the reliability of the components. Following the proposed model of reliability, a novel framework for solving the non-periodical PM schedule with dynamic interval based on the multi-objective genetic algorithm is proposed. The framework denotes the strategies include updating strategy, deleting strategy, inserting strategy and moving strategy, which is set to correct the invalid population individuals of the algorithm. The values of the dynamic interval and the selections of PM action for the components on every PM stage are determined by achieving a certain level of system availability with the minimum total PM-related cost. Finally, a typical rotary table system of NC machine tool is used as an example to describe the proposed method.

Non-periodic preventive maintenance with reliability thresholds for complex repairable systems

In general, a non-periodic condition-based PM policy with different condition variables is often more effective than a periodic age-based policy for deteriorating complex repairable systems. In this study, system reliability is estimated and used as the condition variable, and three reliability-based PM models are then developed with consideration of different scenarios which can assist in evaluating the maintenance cost for each scenario. The proposed approach provides the optimal reliability thresholds and PM schedules in advance by which the system availability and quality can be ensured and the organizational resources can be well prepared and managed. The results of the sensitivity anlysis indicate that PM activities performed at a high reliability threshold can not only significantly improve the system availability but also efficiently extend the system lifetime, although such a PM strategy is more costly than that for a low reliabiltiy threshold. The optimal reliability threshold increases along with the number of PM activities to prevent future breakdowns caused by severe deterioration, and thus substantially reduces repair costs.

Two-Dimensional Warranty With Reliability-Based Preventive Maintenance

In dealing with post-sale warranties, considering only operating time may not be sufficient because products often deteriorate through usage and over time, which both influence product reliability. A two-dimensional warranty is thus more reasonable in practice for both manufacturers and customers. Periodic preventive maintenance within the warranty term seems more prevalent in practice due to its convenience and operability for manufacturers and consumers. However, increases in product deterioration may cause breakdowns to occur more often, even after periodic preventive maintenance has just been performed. In this study, a two-dimensional warranty policy is examined with consideration of non-periodic preventive maintenance to determine the optimal two-dimensional warranty term with a constraint that the product reliability should be above a certain threshold. A numerical application is provided to demonstrate the effectiveness of the proposed approach, with sensitivity analyses being conducted to investigate the robustness of the derived optimal warranty policy.

Recursive operation time maximization model for the maintenance of power generation equipment

Repairable equipment requires preventive maintenance (PM) to maintain proper function. An appropriate PM strategy can extend the life of equipment and reduce variable costs. A power generation company in Taiwan that has a fixed-period PM strategy is studied. However, a fixed-period PM strategy is usually not an optimal solution for maintaining equipment those ages gradually. An age-related dynamical model is designed for creating a timely maintenance schedule that extends the life of equipment and improves its efficiency. A recursive mathematical programming model that considers regular maintenance, emergent maintenance, and maintenance improvement factors is used to obtain the optimal equipment PM schedule. An empirical experiment with the nonperiodic PM schedule computed using the proposed method was conducted. Results show a significant reduction in the PM cost and an extension of the life of equipment.

Minimisation of Non-periodic Preventive Maintenance Cost in Series-Parallel Systems

A new method to optimise the non-periodic preventive maintenance model of a series-parallel system is proposed. A two-stage algorithm that incorporates the failure limit policy to determine maintenance components, maintenance times, and total maintenance cost is suggested. When the reliability of the system reaches a threshold value, preventive maintenance is performed. The first stage identifies the parallel subsystem required to be maintained, while the second stage determines the component required to be maintained in the parallel sub-system. A unit-cost life index (UCL) has been developed to evaluate the extent to which maintaining a component extends the life of a system for the parallel subsystem. Three simulated cases demonstrate the effectiveness and the practicality of the proposed method in optimising the non-periodic preventive maintenance model of a series-parallel system. Defence Science Journal, 2011, 61(1), pp.44-50 , DOI:http://dx.doi.org/10.14429/dsj.61.61

Nonperiodic preventive maintenance for repairable systems

As a complex system with multiple components usually deteriorates with age, preventive maintenance (PM) is often performed to keep the system functioning in a good state to prolong its effective age. In this study, a nonhomogeneous Poisson process with a power law failure intensity is used to describe the deterioration of a repairable system, and the optimal nonperiodic PM schedule can be determined to minimize the expected total cost per unit time. However, since the determination of such optimal PM policies may involve numerous uncertainties, which typically make the analyses difficult to perform because of the scarcity of data, a Bayesian decision model, which utilizes all available information effectively, is also proposed for determining the optimal PM strategies. A numerical example with a real failure data set is used to illustrate the effectiveness of the proposed approach. The results show that the optimal schedules derived by Bayesian approach are relatively more conservative than that for non-Bayesian approach because of the uncertainty of the intensity function, and if the intensity function are updated using the collected data set, which indicates more severe deterioration than the prior belief, replacing the entire system instead of frequent PM activities before serious deterioration is suggested. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010

A Particle Swarm Optimization (PSO) approach for non-periodic preventive maintenance scheduling programming

This work presents a Particle Swarm Optimization (PSO) approach for non-periodic preventive maintenance scheduling optimization. The probabilistic model, which is focused on reliability and cost evaluation, is developed in such a way that flexible intervals between maintenance interventions are allowed. Due to the fact that PSO is typically skilled for real-coded continuous spaces, with fixed dimension (number of search parameters), a non-straightforward codification for solution candidates has been developed in order to allow PSO to deal with variable number of maintenance interventions. To evaluate the proposed methodology, the High Pressure Injection System (HPIS) of a typical 4-loop Pressurized Water Reactor (PWR) has been considered. The optimization problem consists in maximizing the system’s average availability for a given period of time, considering realistic features such as: i) the probability of needing a repair (corrective maintenance), ii) the cost of such repair, iii) typical outage times, iv) preventive maintenance costs, v) the impact of the maintenance in the systems reliability as a whole, vi) probability of imperfect maintenance, etc. Obtained results demonstrated good capability of proposed PSO approach for automatic expert knowledge acquisition (without any a priori information), which allowed it to find optimal solutions.