Preventive Maintenance Policy Research Articles

Optimization of periodic preventive maintenance policy following the expiration of two-dimensional warranty

This paper considers an optimal periodic preventive maintenance policy after the expiration of two-dimensional warranty. During the two-dimensional warranty period, both renewal warranty and nonrenewal warranty are considered and a repair time threshold is pre-specified so that the failed system is either minimally repaired or is replaced depending on whether the length of repair time exceeds the repair time threshold or not. After the warranty expires, the system undergoes the preventive maintenance periodically a fixed number of times by the user to prolong the life of the system and then the system is replaced preventively by a new one. In this study, we develop an optimal post-warranty periodic preventive maintenance strategy by minimizing the expected cost rate incurred during the life cycle of the system. From the user's perspective, the system is maintained free of charge or with prorated charge on the failed system during the warranty period. Once the warranty expires, the maintenance cost of the system is entirely charged to the user. Subject to such a cost structure, we derive the formula to evaluate the expected cost rate, which is used as an objective function for the optimality. The main goal of this paper is to determine an optimal preventive maintenance cycle after the warranty expires and thus to propose an optimal post-warranty strategy for the user. The effect of several parameters on the optimal strategy is also investigated numerically in this study. For the purpose of illustration of our proposed model, we present and discuss some numerical examples.

A model of system limiting availability under imperfect maintenance

PurposeThe purpose of this paper is to explore the impact of the Kijima Type II imperfect repair model on the availability of repairable systems (RS). Since many individuals are interested in measuring the extent to which the system will be available after it has been run for a long time, the specific interest in this study is in the steady-state (limiting) availability behavior of such systems. Furthermore, the authors study the impact of age-based preventive maintenance (PM) on the RS performance.Design/methodology/approachBecause of the complexity of the underlying assumptions of the Kijima Type II model, the authors use simulation modeling to estimate the system availability. Based on preliminary simulation results, the availability function achieves a steady-state value greater than zero. The system steady-state availability is then estimated from the simulation output by computing the average of the availability estimates beyond the initial transient period. Next, the authors develop a meta-model to convert the system reliability and maintainability parameters into the coefficients of the limiting availability estimate without the simulation effort. Using a circumscribed central composite experimental design, the authors confirm the accuracy of the meta-model.FindingsThe results show that the meta-model is robust, and provides good estimates of the system limiting availability. Also, the authors find that when using a Kijima Type II model for a system repair process, age-based PM can improve the steady-state availability value. Therefore, an optimal age-based PM policy that maximizes the system’s steady-state availability can be identified.Originality/valueIn practice, it is important to study the system steady-state availability because many individuals, i.e. engineers, are more interested in measuring the extent to which the system will be available after it has been run for a long time. Therefore, this study represents a significant addition to the body of knowledge related to virtual age modeling, in that it incorporates a Kijima type II model and considers system steady-state availability.

A Just-in-Time Inventory Model with Preventive Maintenance and Defect Rate

In competitive market environments, businesses employ Just-In-Time (JIT) systems not only to reduce costs, but also to enhance their business partnerships. Although product quality level is essential for maintaining competitiveness, traditional inventory models do not consider defect rate, which is the main determinant of product quality. Also, in real working environments, machines break down after long operating times, which increases product defect rate. Therefore, an effective preventive maintenance policy is needed to ensure that machinery is reliable. Reworking defective items is another important inventory problem. To answer the above questions regarding varying defect rate, preventive maintenance and rework, this study developed an integrated two-echelon inventory model to determine the best production quantity, delivery frequency and preventive maintenance schedule under JIT production and delivery policy. The model results can be used to minimize total cost.

Random preventive maintenance policy based on inspection for a multicomponent system using simulation

Random preventive maintenance policy based on inspection for a multicomponent system using simulation

Optimal preventive maintenance for a two dimensional lease contract

Abstract In this paper, we study a two dimensional lease equipment contract with involving imperfect preventive maintenance. The two dimensional lease contract is characterized by two parameters – age and usage limits. The lessor performs both preventive and corrective maintenance and a penalty cost incurred to the lessor when the time required to perform a corrective maintenance exceeds a pre-specified target. Failures are influenced by the age and usage of the equipment and modelled by using a one dimensional approach. We consider that an imperfect preventive maintenance (PM) policy reduces the equipment failure rate and hence it will decrease the penalty cost and maintenance cost during the lease contract. We find the optimal PM interval, number of PM, PM degree (reduction in failure rate) minimizing the expected total cost.

A predictive maintenance system for hybrid degradation processes

PurposeThe purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance effectiveness.Design/methodology/approachThe PdM system updates the degradation model using partial condition monitoring information based on degradation type judgment. In addition, an extended multi-step-ahead updating stopping condition is adopted for performance enhancement of the PdM system.FindingsAn extensive numerical investigation compares the performance of the PdM system with the corresponding preventive maintenance (PM) policy. By carefully choosing the updating stopping condition, the PdM policy performs better than the corresponding PM policy.Research limitations/implicationsThe proposed PdM system is applicable to single-unit systems. And the continuous degradation process should be well modeled by the stochastic linear degradation model (Gebraeel et al., 2009).Originality/valueIn literature, there are abundant studies on PdM policies for continuous degradation processes. However, research on hybrid degradation processes still focuses on condition-based maintenance policy and a PdM policy for a hybrid degradation process is still unreported. In this paper, a PdM system for hybrid degradation processes with continuous degradation and sudden damage is proposed. The PdM system decides PM schedules by fully utilizing the condition monitoring data of each specific product, and can hopefully improve maintenance effectiveness.

Joint optimization of economic production quantity and preventive maintenance with considering multi-products and reserve time

Purpose: We deal with the problem of the joint determination of optimal economic production quantity (EPQ) and optimal preventive maintenance (PM) for a system that can produce multiple products alternately. The objective is to find the optimal number of production cycles and the PM policy simultaneously by minimizing the cost model.Design/methodology/approach: Considering the products go through the system in a sequence and a complete run of all products forms a production cycle. In each cycle, beyond production time we also consider some reserve time for maintenance and setup, shortage and overproduction may occur. We study the integrated problem based on two PM policies, and explain the situation with the other PM policies. The delay – time concept is used to model PM decisions.Findings: Using the integrated EPQ and PM model, we can calculate the optimal production planning and PM schedule simultaneously, especially we consider multiple products in each production cycle, which is more practical and economic than previous works.Originality/value: In modern companies, the production planning and maintenance schedule share the same system, and traditional research about two activities is separated, that always generate conflicts, such as inadequate or excessive maintenance, and shortages, etc., so we develop the integrated EPQ and PM model to avoid these undesirable effects.

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.

Optimal hybrid imperfect preventive maintenance policy for leased equipment

This paper presents a mathematical model for a sequential hybrid imperfect preventive maintenance (PM) policy for leased equipment over a finite lease period in a context where PM actions are imperfect and minimal repairs are performed following failures. Maintenance is entrusted to the lessor. The latter incurs a penalty if the number of failures exceeds a specified threshold over the lease period. Imperfect PM is executed whenever the equipment reliability reaches a certain threshold. It simultaneously reduces the effective age and increases the failure rate of the equipment. The proposed model allows finding the number n of PM actions to be performed on the equipment together with the reliability threshold Rth minimizing the expected total cost over the lease period. And therefore obtain the optimal PM intervals durations Tj*(j* = 1, 2, …, n) corresponding to the optimal reliability threshold. The model considers the expected costs of PM, repairs and penalty during the lease period. A numerical example is presented to illustrate the use of the proposed model. The optimal PM strategy is computed for a leased equipment whose time to failure follows a Weibull distribution. We investigate numerically the effect of the variation of the PM action cost and the age reduction factor on the optimal policy.

On reliability improvement program for second-hand products sold with a two-dimensional warranty

The growing market for second-hand products facilitates the acceptance of warranty provided by dealers to promote sales and provide assurance for customers. Offering warranty results in additional cost due to warranty claims servicing. Such cost can be reduced through upgrade and preventive maintenance (PM) that improve the reliability of the product. Reliability improvement is worthwhile only if the cost incurred is less than the reduction in the warranty cost. For repairable second-hand products sold with a two-dimensional warranty, this paper investigates the worthiness of reliability improvement from the dealer’s viewpoint. A new modeling approach is proposed and studied, allowing the same product to have distinct degradation processes due to customer usage intensity variation. The effects of customer usage heterogeneity, upgrade and PM actions on the product reliability and the corresponding expected cost to the dealer are characterized. Optimal reliability program including the upgrade degree and PM policy is derived so that the expected total cost of the second-hand product to the dealer can be minimized. Numerical examples are utilized to illustrate the applicability of the proposed model. In addition, some practical implications from a sensitive analysis regarding the important parameters are elaborated.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system.

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

Numerical study of inventory management under various maintenance policies

Capital assets, such as manufacturing equipment, require maintenance to remain functioning. Maintenance can be performed when a component breaks down and needs replacement (i.e., corrective maintenance), or the maintenance and part replacement can be performed preventively. Preventive maintenance can be planned on a periodic basis (periodic maintenance), or it can be triggered by a certain monitored condition (condition-based maintenance). Preventive maintenance policies are gaining traction in the business world, but for many companies it is unclear what their impact is on the resulting inventory requirements for the spare parts that are used for the maintenance interventions. We study the impact of the maintenance policy on the inventory requirements and the corresponding costs for a setting that is realistic at an OEM in the compressed air industry. Preventive policies increase the total demand for spare parts compared to corrective maintenance, since the former do not exploit the entire useful life of the components. This leads to higher inventory requirements. At the same time, the preventive policies inhibit advance demand information, as the interventions, and correspondingly the spare parts demands, are planned in advance. Using a simulation study, we show that by using this advance demand information in managing the spare part inventory, the increase in inventory requirements of preventive maintenance policies can to a large extent be offset; for condition-based maintenance, we find that inventories can even be lower compared to corrective maintenance, provided that the advance demand information is used correctly when managing inventories. Our analysis sheds light on the behaviour of the inventory related costs under various maintenance policies.

A preventive maintenance of circular consecutive-k-out-of-n: F systems

PurposeThe purpose of this paper is to develop a preventive maintenance policy with continuous monitoring for a circular consecutive-k-out-of-n: F systems. A preventive maintenance policy is developed based on the system critical condition which is related to the number of working components in the minimal cut sets of the system. If there is at least one minimal cut set which consists of only one working component, the system is maintained preventively (PM) after a certain time interval and the failed components are replaced with the new ones to prevent the system failures. If the system fails prior to the preventive maintenance, the system is correctively maintained (CM) immediately by replacing the failed components.Design/methodology/approachThe mathematical function of the expected cost rate for the proposed maintenance policy is derived. The costs of PM, CM, and replacement per component are considered. The optimal maintenance parameter, which is the PM interval, is obtained by enumeration, and the numerical studies are shown with various system and cost parameters. The performance of the proposed policy is evaluated by comparing its expected cost rate to those of the no-PM and age-PM policies. The percentage of cost increase from the no-PM and age-PM policies to the proposed PM policy is calculated and this value can represents how important the continuous monitoring in this policy.FindingsThe proposed policy outperforms other policies. When the cost of CM is high and the cost of PM is low, the proposed PM policy is more suitable.Research limitations/implicationsThe system consists of identical components and the component failure times follow an exponential distribution. Continuous monitoring is considered, which means that the component states can be known at any time. Three cost parameters, cost of PM, CM, and replacement per component, are considered.Originality/valueThis paper shows a maintenance problem for circular consecutive-k-out-of-n: F systems. Many studies on this system type focused on the reliability estimation or system design problem. Previous study with this policy (Endharta and Yun, 2015) has been developed for linear systems, although the study used a simulation approach to estimate the expected cost rate. Also, Endharta et al. (2016) considered a similar method for the different types of system, which is linear consecutive-k-out-of-n: F system.

Impact of Correlated Component Failure on Preventive Maintenance Policies

A primary goal of maintenance is to minimize the consequences of component and system failures. Two subcategories of maintenance actions include: preventive maintenance (PM) at predetermined time intervals prior to failure and emergency repair (ER) upon failure, where the cost and downtime of ER is significantly greater than PM. Most maintenance models developed over the past several decades assume component failures are statistically independent. This assumption simplifies calculations, but is dangerous for safety critical systems that must be maintained because correlated failures can lower the mean time to failure and increase the probability of ER. This paper presents a simple method with an explicit correlation parameter to characterize the impact of correlated component failures on the optimal PM interval of a system with arbitrary structure. This method is applied to five maintenance policies, including: periodic group repair based on operation time, minimal repair with complete renewal, minimal repair with partial renewal, age replacement to minimize cost, and age replacement to maximize availability. Examples illustrate our approach identifies optimal maintenance strategies for these policies such as reward or cost per unit time, cost per renewal period, and stationary availability despite correlated failures.

Preventive maintenance of a batch production system under time-varying operational condition

This paper proposes a dynamic opportunistic preventive maintenance (PM) strategy for a production system with a time-varying batch production pattern. The operation of such a system is generic in that the operational condition (OC) varies from batch to batch and the information about the next batch can be confirmed only upon the completion of the current batch. To accommodate time-varying OC, a modified imperfect maintenance model is developed to optimise the performance of maintenance actions that can only be performed at batch-shift points. The first study presents a PM policy for a single machine with short-term production plans. Then, a multi-machine system is studied with a goal of developing an optimum dynamic opportunistic PM strategy for a group of machines at batch-shift points. Numerical examples are proceeded to illustrate the proposed maintenance strategy in practice. The result reveals that more cost will be incurred if OC is ignored. Moreover, the proposed opportunistic PM strategy achieves the lowest total cost comparing with other strategies as the system downtime cost and maintenance cost has been jointly minimised.

Generalized geometric process and its application in maintenance problems

Since the repair effect may be varying with the number of repairs, we propose a generalized geometric process (GGP) to model the deteriorating process of repairable systems. For a GGP, the geometric ratio changes with the number of repairs rather than being a constant. Based on the GGP, two repair-replacement models are studied. Existing preventive maintenance (PM) models based on geometric process (GP) commonly assume that the PM is ‘as good as new’ in each working circle, which is not realistic in many situations. In this study, that the system is assumed to be geometrically deteriorating after PM or corrective maintenance (CM). Firstly, an age-dependent PM model is considered, in which the optimal policies N* and T* are obtained theoretically, and the optimal bivariate policy (N*, T*) which minimizes the average cost rate (ACR) can be determined by a searching algorithm. Next, because of the fact that the system deteriorates after maintenance, the schedule time to PM should decrease with the maintenance number increasing. Therefore, a sequential PM policy is investigated, and the optimal policy N* and the optimal schedule times T1*,T2*,…,TN** are computed. Finally, numerical examples are provided to illustrate the proposed models.

Preventive maintenance of a single machine system working under piecewise constant operating condition

Manufacturing machines usually work under piecewise constant operating condition (PCOC) and are subject to imperfect preventive maintenance (PM). In this paper, an extended imperfect maintenance (IM) model for a machine working under PCOC is developed by combining an age-based hybrid IM model and an accelerated failure time model (AFTM). Maximum likelihood method is provided for estimating the model parameters. A dynamic cost-effective PM policy based on a short-term production plan is proposed for a common situation where the production plan is updated dynamically and only the current operating condition (OC) is confirmed. A numerical example is conducted to demonstrate the use of the proposed policy in practice.

Jointly Production and Correlated Maintenance Optimization for Parallel Leased Machines

This paper deals with a preventive maintenance strategy optimization correlated to production for a manufacturing system made by several parallel machines under lease contract. In order to minimize the total cost of production and maintenance by reducing the production system interruptions due to maintenance activities, a correlated group preventive maintenance policy is developed using the gravity center approach (GCA). The aim of this study is to determine an economical production plan and an optimal group preventive maintenance interval Tn at which all machines are maintained simultaneously. An analytical correlation between failure rate of machines and production level is considered and the impact of the preventive maintenance policy on the production plan is studied. Finally, the proposed maintenance policy GPM is compared with an individual simple strategy approach IPM in order to illustrate its efficiency.

Integrated maintenance–quality policy taking into account the economical impact of reworking activities

ABSTRACTIn this paper, we study integrated strategies joining maintenance and quality. We consider an imperfect manufacturing system composed of a single machine subject to an increasing random failure rate and producing conforming (first and second choice) and non conforming items. In order to decrease the failure rate and its impact on teh quality of output products, a preventive maintenance (PM) policy, block type, with minimal reapair is applied. Indeed, two different strategies are developed: The first strategy consists on selling top quality products at the best price, selling products with substandard quality at a lower price and rejecting non-conforming items. For the second strategy, we propose reworking activities for products with substandard quality and non-conforming items in order to be sold at the best price. We aim to establish the optimal number of batches produced N* before each PM action maximizing the total profit per time unit. These two strategies are studied for both an infinite and finite horizon. A comparative study between these two strategies for an infinite horizon is developed in order to identify the most economical strategy. Numerical and sensitivity studies are developed, inspired from an industrial case, in order to illustrate the proposed models.

Discrete maintenance optimization of complex multi-component systems

A complex multi-component system consists of finite number of non-identical components that can be realized as maintained components with different maintenance modes. We distinguish between four component models: non-repairable components, repairable components with corrective maintenance, repairable components with latent failures that are identified by means of preventive maintenance and component with preventive maintenance policy in which the component is restored (either repaired or renewed). The paper describes a new method for optimal maintenance strategy of a complex system respecting a given reliability constraint. It is based on our previously developed direct analytical method that enables exact reliability quantifications of highly reliable systems with maintenance. The method takes into account complex systems with maintained components, including all above models. Cost-optimization problem is solved where decision variables are changeable maintenance parameters that are optimally selected from a set of possible realistic maintenance modes. As a discrete maintenance model in this paper is considered such a model, where each maintained component can be operated in one or few discrete maintenance modes. One maintenance mode is characterized by fixed decision variables that affect maintenance cost of the mode. If a system hypothetically contains k components with 5 independent maintenance modes, in total we have 5k maintenance configurations of the system, from which the optimal is found. The optimization method is demonstrated on real system from practice – a complex power distribution network.