Optimal policies for a delay time model with postponed replacement

We develop a delay time model (DTM) to determine the optimal maintenance policy under a novel assumption: postponed replacement. Delay time is defined as the time lapse from the occurrence of a defect up until failure. Inspections can be performed to monitor the system state at non-negligible cost. Most works in the literature assume that instantaneous replacement is enforced as soon as a defect is detected at an inspection. In contrast, we relax this assumption and allow replacement to be postponed for an additional time period. The key motivation is to achieve better utilization of the system’s useful life, and reduce replacement costs by providing a sufficient time window to prepare maintenance resources. We model the preventive replacement cost as a non-increasing function of the postponement interval. We then derive the optimal policy under the modified assumption for a system with exponentially distributed defect arrival time, both for a deterministic delay time and for a more general random delay time. For the settings with a deterministic delay time, we also establish an upper bound on the cost savings that can be attained. A numerical case study is presented to benchmark the benefits of our modified assumption against conventional instantaneous replacement discussed in the literature.     

Opportunity-based age replacement with a one-cycle criterion

In this paper age replacement (AR) and opportunity-based age replacement (OAR) for a unit are considered, based on a one-cycle criterion, both for a known and unknown lifetime distribution. In the literature, AR and OAR strategies are mostly based on a renewal criterion, but in particular when the lifetime distribution is not known and data of the process are used to update the lifetime distribution, the renewal criterion is less appropriate and the one-cycle criterion becomes an attractive alternative. Conditions are determined for the existence of an optimal replacement age T^* in an AR model and optimal threshold age T_opp^* in an OAR model, using a one-cycle criterion and a known lifetime distribution. In the optimal threshold age T_opp^*, the corresponding minimal expected costs per unit time are equal to the expected costs per unit time in an AR model. It is also shown that for a lifetime distribution with increasing hazard rate, the optimal threshold age is smaller than the optimal replacement age. For unknown lifetime distribution, AR and OAR strategies are considered within a nonparametric predictive inferential (NPI) framework. The relationship between the NPI-based expected costs per unit time in an OAR model and those in an AR model is investigated. A small simulation study is presented to illustrate this NPI approach.     

The opportunistic replacement problem: theoretical analyses and numerical tests

We consider a model for determining optimal opportunistic maintenance schedules w.r.t. a maximum replacement interval. This problem generalizes that of Dickman et?al. (J Oper Res Soc India 28:165?C175, 1991) and is a natural starting point for modelling replacement schedules of more complex systems. We show that this basic opportunistic replacement problem is NP-hard, that the convex hull of the set of feasible replacement schedules is full-dimensional, that all the inequalities of the model are facet-inducing, and present a new class of facets obtained through a ${\{0, \frac{1}{2}\}}$ -Chvátal?CGomory rounding. For costs monotone with time, a class of elimination constraints is introduced to reduce the computation time; it allows maintenance only when the replacement of at least one component is necessary. For costs decreasing with time, these constraints eliminate non-optimal solutions. When maintenance occasions are fixed, the remaining problem is stated as a linear program and solved by a greedy procedure. Results from a case study on aircraft engine maintenance illustrate the advantage of the optimization model over simpler policies. We include the new class of facets in a branch-and-cut framework and note a decrease in the number of branch-and-bound nodes and simplex iterations for most instance classes with time dependent costs. For instance classes with time independent costs and few components the elimination constraints are used favorably. For fixed maintenance occasions the greedy procedure reduces the computation time as compared with linear programming techniques for all instances tested.     

Optimizing System Availability Under Minimal Repair with Non-Negligible Repair and Replacement Times

Availability measures are given for a repairable system under minimal repair with constant repair times. A new policy and an existing replacement policy for this type of system are discussed. Each involves replacement at the first failure after time T, with T representing total operating time in the existing model and total elapsed time (i.e. operating time + repair time) in the new model. Optimal values of T are found for both policies over a wide range of parameter values. These results indicate that the new and administratively easier policy produces only marginally smaller optimal availability values than the existing policy.     

A discussion on “A bivariate optimal replacement policy for a repairable system”

In this short paper, a bivariate optimal replacement policy for a repairable system with a geometric process maintenance model is discussed. Zhang [Zhang, Y.L., 1994. A bivariate optimal replacement policy for a repairable system. Journal of Applied Probability 31, 1123–1127] and Sheu [Sheu, S.H., 1999. Extended optimal replacement model for deteriorating systems. European Journal of Operational Research 112, 503–516] obtained different expression of the long-run average cost per unit time (i.e. average cost rate) of the system respectively. We show that both of their results are correct, therefore, Sheu’s comment (1999) on the result of Zhang (1994) is wrong.     

A state space condition monitoring model for furnace erosion prediction and replacement

The paper develops a replacement action decision aid for a key furnace component subject to condition monitoring. A state space model is used to predict the erosion condition of the inductors in an induction furnace in which a measure of the conductance ratio (CR) is used to indirectly assess the relative condition of the inductors, and to guide replacement decisions. This study seeks to improve on this decision process by establishing the relationship between CR and the erosion condition of the inductors. To establish such a relationship, a state space model has been established and the system parameters estimated from CR data. A replacement cost model to balance at any time costly replacements with possible catastrophic failure is also proposed based upon the predicted probability of inductor erosion conditional upon all available information. The well known Kalman filter is employed to derive the predicted and updated probability of inductor erosion level conditional upon CR data to date. This is the first time the condition monitoring decision process has been modelled for real plant based upon filtering theory. The model fits the data well, gives a sensible answer to the actual problem, and is transferable to other condition monitoring contexts. Possible extensions are discussed in the paper.     

A number-dependent replacement policy for a system with continuous preventive maintenance and random lead times

This paper considers a number-dependent replacement policy for a system with two failure types that is replaced at the nth type I (minor) failure or the first type II (catastrophic) failure, whichever occurs first. Repair or replacement times are instantaneous but spare/replacement unit delivery lead times are random. Type I failures are repaired at zero cost since preventive maintenance is performed continuously. Type II failures, however, require costly system replacement. A model is developed for the average cost per unit time based on the stochastic behavior of the system and replacement, storage, and downtime costs. The cost-minimizing policy is derived and discussed. We show that the optimal number of type I failures triggering replacement is unique under certain conditions. A numerical example is presented and a sensitivity analysis is performed.     

A Robust Replacement Model with Applications to Medical Equipment

Perceived shortcomings in the applicability of capital equipment replacement modelling, identified in a 1987 survey within the UK are addressed and a robust replacement model formulated. First, however, a comparison between the 1987 survey and a similar 1988 survey undertaken within the USA is made and explanations for apparent differences in conclusions are presented. A replacement model is then developed in the context of medical equipment where factors such as service and risk play a role in replacement decision-making. A mechanism for quantitatively allowing for qualitative and for political type factors within a short time horizon replacement model is introduced by means of a penalty factor. A case example is presented for medical ventilator equipment.     

Optimal age-replacement model with age-dependent type of failure and random lead time based on a cumulative repair-cost limit policy

In this paper, we consider an age-replacement model with minimal repair based on a cumulative repair cost limit and random lead time for replacement delivery. A cumulative repair cost limit policy uses information about a system’s entire repair cost history to decide whether the system is repaired or replaced; a random lead time models delay in delivery of a replacement once it is ordered. A general cost model is developed for the average cost per unit time based on the stochastic behavior of the assumed system, reflecting the costs of both storing a spare and of system downtime. The optimal age for preventive replacement minimizing that cost rate is derived, its existence and uniqueness is shown, and structural properties are presented. Various special cases are included, and a numerical example is given for illustration. Because the framework and analysis are general, the proposed model extends several existing results.     

Optimal replacement model with age-dependent failure type based on a cumulative repair-cost limit policy

This paper presents a replacement model with age-dependent failure type based on a cumulative repair-cost limit policy, whose concept uses the information of all repair costs to decide whether the system is repaired or replaced. As failures occur, the system experiences one of the two types of failures: a type-I failure (minor), rectified by a minimal repair; or a type-II failure (catastrophic) that calls for a replacement. A critical type-I failure means a minor failure at which the accumulated repair cost exceeds the pre-determined limit for the first time. The system is replaced at the nth type-I failure, or at a critical type-I failure, or at first type-II failure, whichever occurs first. The optimal number of minimal repairs before replacement which minimizes the mean cost rate is derived and studied in terms of its existence and uniqueness. Several classical models in maintenance literature are special cases of our model.     

Periodical replacement problem without assuming minimal repair

In this paper, a periodical replacement problem with a general repair is considered where a system is replaced at only scheduled times kT (k = 0,1,…) and is repaired whenever it fails. By general repair, we mean that repair brings the state of the system to a certain better state. A stochastic model to describe the operation in time of a repairable system which is maintained by a general repair is developed. The model contains the minimal repair case in which repair restores a system to its functioning condition just prior to failure. The sensitivity of replacement policies under a general repair to derivation from the minimal repair assumption is numerically examined. It will be seen that the policies are insensitive when the deterioration of the system is not fast and the replacement cost is high relative to the repair cost. The minimal repair assumption is then justified for such situations.     

Optimization problems of replacement first or last in reliability theory

This paper takes up age and periodic replacement last models with working cycles, where the unit is replaced before failure at a total operating time T or at a random working cycle Y, whichever occurs last, which is called replacement last. Expected cost rates are formulated, and optimal replacement policies which minimize them are discussed analytically. Comparisons between such a replacement last and the conventional replacement first are made in detail. It is determined theoretically and numerically which policy is better than the other according to the ratios of replacement costs and how the mean time of working cycles affects the comparison results. It is also shown that the unit can be operating for a longer time and avoid unnecessary replacements when replacement last is done. For further studies, expected cost rates of modified models and their applications in a standard cumulative damage model with working cycles are obtained and computed numerically. Finally, case studies on replacement last and first in maintaining electronic systems of naval ships under battle and non-battle statuses are given.     

Optimal Replacement Policy for a General Model with Imperfect Repair

A general model is considered which incorporates imperfect repair and repair cost which depends on time and on the number of repairs in the cycle. This model is an extension of models examined previously in the literature. The objective of this paper is to find the optimal replacement policy and compare it with the replacement policies considered earlier for some variants of this model. The form of the optimal replacement policy is found in the general case and the expected average cost per unit time is derived in two special cases. Numerical examples show that the optimal policy is considerably better than the optimal periodic policy. This paper generalizes and unifies previous research in the area.     

有限可修备件条件下系统计划更换策略

在现有的计划更换模型的基础上 ,研究了一种备件有限及部件可修的更换策略问题。利用在更换周期点上具有的马尔可夫性质 ,以系统首次故障前平均工作时间最大为目标建立了确定最佳更换周期的模型。     

Reliable tool replacement policy for quality and cost

A tool management model is developed which determines the optimal initial tool setting and tool replacement time in consideration of balancing quality loss, replacement cost, and possible tool failure. A quadratic loss function is employed to characterize the costs resulting from the deviation of part dimension from its target value. The tool reliability function is used to represent the probability of possible tool failure. The model development does not attempt to explain the underlying physics of tool wear and tool failure and does not intend to apply to on-line tool replacement decision. Instead, the present study provides a decision model for management engineers in off-line tool management applications.     

Optimal warranty policies for systems with imperfect repair

We investigate a system whose basic warranty coverage is minimal repair up to a specified warranty length. An additional service is offered whereby first failure is restored up to the consumers’ chosen level of repair. The problem is studied under two system replacement strategies: periodic maintenance before and after warranty. It turns out that our model generalizes the model of Rinsaka and Sandoh [K. Rinsaka, H. Sandoh, A stochastic model with an additional warranty contract, Computers and Mathematics with Applications 51 (2006) 179–188] and the model of Yeh et al. [R.H. Yeh, M.Y. Chen, C.Y. Lin, Optimal periodic replacement policy for repairable products under free-repair warranty, European Journal of Operational Research 176 (2007) 1678–1686]. We derive the optimal maintenance period and optimal level of repair based on the structures of the cost function and failure rate function. We show that under certain assumptions, the optimal repair level for additional service is an increasing function of the replacement time. We provide numerical studies to verify some of our results.     

A continuous time markov-renewal replacement model for manpower systems

A continuous time Markov-renewal model is presented that generalizes the classical Young and Almond model for manpower systems with given size. The construction is based on the associated Markov-renewal replacement process and exploits the properties of the embedded replacement chain. The joint cumulant generating function of the grade sizes is derived and an asymptotic analysis provides conditions for these to converge in distribution to a multinominal random vector exponentially fast independently of the initial distribution, both for aperiodic and periodic embedded replacement chains. A regenerative approach to the wastage process is outlined and two numerical examples from the literature on manpower planning illustrate the theory.     

Comments on Finite-Period Applications of Age-Based Replacement Models

The age-based replacement problem is considered when a finitetime zone is placed upon the duration of the process and, accordingly,for which an asymptotic model could be of questionable validity.Three models to be optimized with respect to the decision variableare considered: first, the commonly used limiting asymptoticcost per unit time; secondly, the refined asymptotic cost perunit time; and thirdly, the exact expected cost. These modelsare investigated in the case of a negative exponential and Weibullfailure-time distribution. In both cases, it is found that theestimated cumulative cost resulting from the refined model approachesquickly that of the exact formulation. The practical use and decision consequences of this result areinvestigated for a Weibull failure distribution. It is arguedthat, because of the essential illconditioned nature of theage based replacement model, for short time-zone applications,the model should be extended to accommodate non-zero replacementtimes.     

A quantitative model of accelerated vehicle-retirement induced by subsidy

A number of accelerated vehicle-retirement programs have been implemented by private companies and public agents to reduce pollution and promote environment friendly technology. Our paper examines subsidy programs for the acquisition of a new low-pollution vehicle, provided that an old technology unit is retired. A model is developed to determine the appropriate subsidy level that induces the replacement of a specified number of existing old technology units within a given time period. Alternatively, given the subsidy level, the model allows the determination of the required time period to achieve a desired replacement target. In this way, the proposed method could be used to assess the effectiveness of a subsidy-based policy of accelerated vehicle-retirement in reaching a targeted number of scraped vehicles within a specified time framework.     

The Availability and Hazard of a System Under a Cumulative Damage Process With Replacements

Zacks (Failure distribution associated with general renewal damage processes. In: Nikulin M, Commenges D, Haber C (eds) Probability statistics and modelling in public health. Springer, Berlin, pp 465–475, 2006) studied the reliability function, the hazard function and the distribution of the failure time when a system is subject to a cumulative, compound renewal damage process. The failure occurs when the damage process crosses a threshold β. In the present paper these results are generalized to the model where the system is replaced after failures. Two cases are considered: instant replacement and random positive replacement time. The distribution of the age of the current renewal cycle, as well as its excess life, and the availability function are studied. We derive also the distribution of total time in (0, t) at which the system has been operational.