Optimal Preventive Maintenance Time Research Articles

Multi-phase preventive maintenance strategy for leased equipment considering usage rate variation

Lessors are responsible for equipment maintenance during the lease period. The usage rate of these equipment affects their failures, reliability and decision-making on maintenance strategy. For some leased equipment, such as those producing seasonal products, the usage rate varies. However, conventional approaches usually set usage rate as a constant. Different from the existing literature, this work considers the variation of usage rate, and proposes a multi-phase preventive maintenance (PM) decision model to determine the PM times and degrees at different phases. The goal is to minimize lessors’ lease service cost by balancing corrective maintenance (CM) cost, PM cost and penalty cost during the lease period. In this model, an age correspondence framework is applied to characterize the variation of usage rate at different phases. An accelerated failure time model and an age reduction model are adopted to capture the effect of variable usage rate and imperfect PM on the equipment’s reliability. To verify the effectiveness of the proposed model, it is contrasted with a PM decision model with average usage rate. The impact of unit PM cost, CM cost, and penalty cost on maintenance strategy is discussed by numerical examples. Managerial insights for maintenance strategy are provided for lessors. The results indicate that the proposed approach considering varied usage rate can change the optimal PM times and degrees, and consequently lead to a lower lease service cost than conventional approaches using average usage rate; lessors need to enhance PM capability and reduce PM cost.

On preventive maintenance of k-out-of-n systems subject to fatal shocks

In this paper, we investigate optimal age-based preventive maintenance (PM) policies for an ( n- k + 1)-out-of- n system whose components are exposed to fatal shocks that arrive from various sources. We consider two different scenarios for the system failure. In the first one, it is assumed that the shock process is of the type of Marshall-Olkin where each shock affects one component of the system and puts it down, and one shock affects all components and destroys all of them. In the second scenario, it is assumed that the system is subject to an extended type of Marshall-Olkin shock process where the shocks arriving at random times may cause the breakdown of 1, 2, …, or n components. Under each scenario for the components failure, we investigate an optimal age-based PM model for the system by imposing the related cost function. Then, in each case, we explore the optimal PM time that minimizes the mean cost per unit of time. Some numerical results are presented to illustrate the applications of the proposed models.

A Hybrid Simulation Study to Determine an Optimal Maintenance Strategy

With the increasing complexity of the process industry, having excellent maintenance management is essential for manufacturing industries. Various parts that interact and interdependent with each other make a well-planned maintenance strategy is one of the major challenges facing by industry. The whole system could be interrupted just simply because of the failure of a component. Therefore, a review of a maintenance strategy must be done from a system perspective. It is suggested that the optimal preventive maintenance time interval is not only determined by the lowest maintenance cost of each machine but also its impact on the whole system. Two main indicators that can accommodate the system perspective are reliability and revenue. A large number of machines and the array of machines can be synthesized in the reliability indicator. Moreover, the creation of maximum revenue is always the main goal for a business. The best maintenance strategy will be determined from the revenue obtained by a process industry. The process industry discussed in this study is a flour mill which is very well known in Surabaya. This study applied a hybrid simulation to solve this problem. Monte Carlo simulation was used to observe the machine individually and the results are reviewed using the application of System Dynamics. Three improvement scenarios were proposed in this simulation study. Scenario 2 was chosen as the best scenario because it was able to generate the highest revenue at the end of the period. Scenario 2 recommends setting the preventive maintenance time interval considering resource availability.

Optimal preventive maintenance of coherent systems: A generalized Pólya process approach

We propose optimal preventive maintenance strategies for n-component coherent systems. We assume that in the early time of the system operation all failed components are repaired, such that the state of a failed component gets back to a working state, worse than that of prior to failure. To model this repair action, we utilize a counting process on the interval known as the generalized Pólya process (which subsumes the non-homogeneous Poisson process as a special case). Two generalized Pólya process-based repair strategies are proposed. The criteria to be optimized are the cost function formulated based on the repair costs of the components/system, and the system availability, to obtain the optimal time of preventive maintenance of the system. To illustrate the theoretical results, two coherent systems are studied for which the optimal preventive maintenance times are explored under different conditions.

A Generalized Chart-Based Decision-Making Tool for Optimal Preventive Maintenance Time under Perfect Renewal Process Modeling

The most commonly used probabilistic model in reliability studies is the Perfect Renewal Process (PRP), which is characterized by the condition or type of maintenance represented: once the maintenance activities are executed, the equipment is restored to its original condition, leaving it “as good as new.” It is widely used since it represents an optimistic state when an item is replaced, assuming a perfect operational condition of the item after the maintenance. Some models have been developed for determining optimum preventive maintenance (PM) based on different criteria, and almost all aimed at PRP reliability modeling. The contribution of this paper is to analyze a model for determining the optimal preventive maintenance policy for a long time run under PRP and developing a general and chart-based tool for the problem, making it easier to solve the day-to-day practice and operation of equipment. As a result, a generalized chart was developed to support maintenance decisions through the elaboration of an original isometric table and complemented with a step-by-step methodology to determine the optimum time in which the preventive maintenance activities must be implemented. In most cases, these types of maintenance activities will consider a replacement activity.

Decision method on optimal time of preventive maintenance for metro shield tunnels in soft soils

Abstract A reasonable maintenance time is vital in the metro shield tunnel maintenance to keep good structural performance and reduce maintenance cost. Lacking predictability, the existing maintenance mode cannot effectively resolve the contradiction between the limited maintenance cost and the growing maintenance need in the future. In this study, the degradation model of metro shield tunnels in soft soils was studied to predict the long-term serviceability. Based on that, a method was proposed to decide the optimal time of preventive maintenance for metro shield tunnels. It was found that the tunnel decay process can be expressed by the inverse exponential function-based prediction model. The cost-benefit analysis method was adopted to determine the optimal preventive maintenance time, considering the maintenance time, the maintenance cost and the maintenance measures adopted. The flow chart of this method and an application example were presented. Results can help metro operation owners to develop more scientific and reasonable preventive maintenance plans for shield tunnels in soft soils.

Maintenance cycle optimisation of multi-component systems under the constraints of overall cost and reliability

Periodic maintenance inevitably leads to 'over-maintenance' or 'non-timely maintenance' of equipment or systems. To improve reliability and reduce maintenance cost, this paper presents a dynamic maintenance cycle optimisation model for multi-component systems. In this paper, the influence of different maintenance intervals on system reliability and total maintenance cost is determined under the conditions that the system has a limited service time and the components are not fully maintained. The model uses the optimisation of system maintenance cost as the objective function to determine the optimal preventive maintenance times and maintenance intervals under the constraint of the lowest reliability of the system. The simulation results of the final example verify that the proposed method can significantly improve the maintenance cost, system reliability, and reliability fluctuation stability. And it can be used to guide subway maintenance cycle optimisation.

Optimal maintenance policies for coherent systems with multi-type components

We propose two new optimal maintenance strategies for preservation of a complex n-component coherent system. The criteria that will be optimized are some given imposed cost functions formulated based on the costs of the repairs of components (system) to get the optimal time of preventive maintenance of the system. The first strategy involves minimal repair on the failed components in an early life period of the system and then corrective maintenance on the entire system upon its failure or preventive/corrective maintenance on each component when the age of the system reaches t. In the second strategy, we assume that the system is inspected at times t,2t,…,mt,m=1,2⋯. At each inspection time, depending on the system conditions, a maintenance action is performed on the components of the system and then the imposed cost function is minimized to get the optimal preventive maintenance time. To interpret the theoretical results, a system constructed from 12 components of three types is examined for which the optimal preventive maintenance times are explored for both strategies under given cost functions.

Condition based opportunistic preventive maintenance policy for utility systems with both economic and structural dependencies [formula omitted] application to a gas supply network

The main challenge in the maintenance planing lies in the realistic modeling of the maintenance policy. However, the complexity of the industrial systems makes difficult the achievement of this prospect. To face the realistic constraints, the present paper provides an approach for the maintenance planning of utility systems on the basis of opportunistic maintenance policy and Bayesian theory. The reliability assessment, which can be updated according to the evolution of the environmental conditions using the Bayesian theory, is integrated in the maintenance model, in order to evaluate the optimal preventive maintenance times and to update them when new degradation data become available. The opportunistic replacement is used to take benefit from the non-operating state of some components, caused by the maintenance action on other components, in order to replace them opportunistically. The effectiveness of the proposed approach is illustrated through a numerical application on operating gas supply system.

Maintenance Policy in Public-Transport Involving Government Subsidy

A public transport with government subsidy is considered to encourage the sustainability of the transportation. The transportations revenue is determined by the maximum of the uptimes of the vehicle. In this paper, we study a one-dimensional maintenance policy for new vehicle which is characterized by age parameter. We consider that the degradation of the vehicle is affected by the age of the vehicle, and modelled by using a one-dimensional approach. The owner performs both preventive and corrective maintenance actions, and the preventive maintenance action will reduce the vehicle failure rate and hence it will decrease the corrective maintenance cost during the life time of the vehicle. The decision problem for the owner is to find the optimal preventive maintenance time of the vehicle of each subsidy option offered by maximizing the expected profit for each subsidy.

Investigation on physical and chemical parameters to predict long-term aging of asphalt binder

The objective of this paper is to investigate and determine the critical physical and chemical parameters corresponded with long-term aging of asphalt binder in both laboratory and field. Firstly, the basic properties, rheological properties, component analysis and functional group analysis were conducted to determine the critical physical and chemical parameters of long-term PAV aged binder in laboratory. Secondly, the asphalt binders in field with different service life are extracted and comparatively analysed with laboratory aged binder. Lastly, the critical physical and chemical parameters of aged asphalt were determined and discussed. The results indicate that viscosity ratio can be used as indicator to predict the aging of asphalt binder in both laboratory and field. Furthermore, the carbonyl area index can be used as a chemical indicator to effectively reflect the aging level of asphalt binder. The results of this paper will help to gain a better understanding of the long-term aging behavior of asphalt binder both in laboratory and in field pavement and provide methods to determine the optimal preventive maintenance time for aged asphalt pavement in service.

Adaptive Sequential Preventive Maintenance Policy and Bayesian Consideration

This article proposes an adaptive sequential preventive maintenance (PM) policy for which an improvement factor is newly introduced to measure the PM effect at each PM. For this model, the PM actions are conducted at different time intervals so that an adaptive method needs to be utilized to determine the optimal PM times minimizing the expected cost rate per unit time. At each PM, the hazard rate is reduced by an amount affected by the improvement factor which depends on the number of PM's preceding the current one. We derive mathematical formulas to evaluate the expected cost rate per unit time by incorporating the PM cost, repair cost, and replacement cost. Assuming that the failure times follow a Weibull distribution, we propose an optimal sequential PM policy by minimizing the expected cost rate. Furthermore, we consider Bayesian aspects for the sequential PM policy to discuss its optimality. The effect of some parameters and the functional forms of improvement factor on the optimal PM policy is measured numerically by sensibility analysis and some numerical examples are presented for illustrative purposes.

Studies on optimum preventive maintenance policies for general repair result

Abstract In this paper we consider that a unit is repaired preventively after it has operated for time T . After repair, the unit is not as good as a new one, but is equivalent to one which has been used for a period of time. If we let Y indicate such a period of time, then Y is a random variable related to the time for which the unit has already operated. Hence, under the same repair condition as above, we obtain the unit's renovation degree distribution of Y after the unit is repaired preventively at time kT ( k = 2, 3, … ). Further, using the method of leading variables, we obtain the mean number of times the unit has broken down from time ( k − 1)T to time kT ( k = 1, 2, … ). Finally, considering an objective function with a bound condition and using the Lagrange multipliers method, we obtain an optimal preventive maintenance time T , for which the minimum total repair cost is achieved.

Reliability Analysis of a Two-Unit Standby-Redundant System with Preventive Maintenance

We consider a standby-redundant model of two units, where we assume that one unit is operative and the other unit is in standby at time t = 0. If the operative unit fails, a unit in standby is put into preventive maintenance policy of the operative unit to maintain our the preventive maintenance policy of the operative unit to maintain our system with high reliability. Our concern for the system is the time to the first system-down. The Laplace-Stieltjes transform of the time distribution to the first system-down and the mean time to the first system-down are derived by applying the relationship between Markov renewal processes and signal flow graph. Further, the behavior after the system-down is investigated by using the results of Markov renewal processes. Finally, numerical examples are presented for the k-Erlang failure time distributions. The optimal preventive maintenance time is discussed.