Distributing inspections in space and time – Proposed solution of a difficult problem

There are several identical facilities in which precious or dangerous material is processed or stored. Since parts of this material may be diverted by some manager or employee of these facilities or since failures in the processing of the material may occur, an authorized organization inspects these facilities regularly at the beginning and at the end of some reference time interval. In order to shorten the time required for detecting such an illegal activity or failures, in addition some interim inspections are performed in these facilities during the reference time interval. The optimal distribution of these interim inspections in space and time poses considerable analytical problems since adversary strategies have to be taken into account. So far only special cases have been analysed successfully, but these results lead to a conjecture for the solution of the general case which is surprisingly simple in view of the complexity of this inspection problem.     

Cost effective scheduling of imperfect inspections in systems with hidden failures and rescue possibility

Motivated by real-world critical applications such as aircraft, medical devices, and military systems, this paper models non-repairable systems subject to a delay-time failure process involving hidden and fatal failures in two stages during their missions. A hidden failure cannot cause the system to stop functioning while a fatal failure causes the entire system loss. The system undergoes scheduled inspections for detecting the hidden failure. In the case of a positive inspection result, the system main mission is aborted and a rescue operation is started to mitigate the risk of the entire system loss. The inspections are imperfect and may produce false positive and negative failures. We propose probabilistic models for evaluating performance metrics of the system considered, including mission success probability, system survival probability, expected number of inspections during the mission, and total expected losses. Based on the evaluation models, we formulate and solve an optimization problem of finding the optimal inspection schedule on a fixed mission time horizon to minimize the total expected loss. Examples are provided to demonstrate the proposed methodology and effects of key system parameters on system performance and optimization solutions.     

Uncertainty in reliability evaluation processes and a simulation approach to treating it

This paper considers the problem of uncertainty in reliability data that are used in many decision making processes and describes a simulation approach to dealing explicitly with this uncertainty. The causes of uncertainty are discussed for three different situations: (a) in the process of designing new systems, when failure data are not yet available, (b) after performing reliability test and gathering failure data, and (c) in mission reliability prediction. It is concluded that, in performing reliability prediction or failure rate prediction, one should use interval estimates rather than point estimates. These intervals can be used to perform component classification and then, employing simulation, to obtain tables or scattergrams for the mean time between failures of a system or for system reliability.     

Optimal inspection policies for a storage system with degradation at periodic tests

A system such as missiles and spare parts of aircrafts is in storage for a long time from transportation to usage. The reliability of a system in storage will go down with time, and so, it should be inspected and maintained at suitable times to hold a high reliability. However, we do not wish to inspect a system too often because each inspection involves a cost and sometimes might degrade some parts of a system during the test interval.This paper considers a periodic inspection policy for a storage system which has to hold a higher reliability. A system has two types of units, where Unit 1 is maintained at each test, however, Unit 2 is degraded with time and at each test. A system is also overhauled, if the reliability becomes lower than a prespecified value q. The reliability of a system is derived, and using this result, the time and the average cost until overhaul is obtained. The optimal policies which maximize the time to overhaul and minimize the average cost are discussed. Finally, numerical examples are given.     

Maintenance models based on the <Emphasis Type="Italic">np</Emphasis> control charts with respect to the sampling interval

This paper develops models for the maintenance of a system based on np control charts with respect to the sampling interval. At any given time, the system is assumed to be in one of the three possible states; in-control, out-of-control and failure. If the control chart signals, suggesting the possibility of an out-of-control state, an investigation will be carried out. We assume that this investigation is perfect in that it reveals the true state of the system. If an assignable cause is confirmed by the investigation, a minor repair will be carried out to remove the cause. If the assignable cause is not attended to, it will gradually develop into a failure. When a failure occurs, the system cannot operate and a major repair is needed. We discuss three models depending on the assumptions related to the renewal mechanism, the occurrence of failures, and the time between minor repairs. The paper seeks to optimise the performance of such a system in terms of the sampling interval. Geometric processes are utilised for modelling the lifetimes between minor repairs if the minor repair cannot bring the system back to an as good as new condition. The expected cost per unit time for maintaining the systems with respect to the sampling interval of the control chart is obtained. Numerical examples are conducted to demonstrate the applicability of the methodology derived.     

Optimal burn-in for maximizing reliability of repairable non-series systems

Burn-in is a manufacturing process applied to products to eliminate early failures in the factory before the products reach the customers. Various methods have been proposed for determining an optimal burn-in time of a non-repairable system or a repairable series system, assuming that system burn-in improves all components in the system. In this paper, we establish the trade-off between the component reliabilities during system burn-in and develop an optimal burn-in time for repairable non-series systems to maximize reliability. One impediment to expressing the reliability of a non-series system is in that successive failures during system burn-in cannot be described precisely because a failed component is not detected until the whole system fails. For approximating the successive failures of a non-series system during system burn-in, we considered two types of repair: minimal repair at the time of system failure, and repair at the time of component or connection failure. The two types of repair provide bounds on the optimal system burn-in time of non-series systems.     

An optimal maintenance policy for repairable systems with delayed repairs

This work considers a combined maintenance strategy in which the repair of the system failures is performed only in an interval of time of the working period. The objective of this paper is to find the optimal interval in which the repairs can be performed.     

Replacement Policies under Minimal Repair

In many situations where system failures occur the concept of ‘minimal repair’ is important. A minimal repair occurs when the failed system is not treated so as to return it to ‘as new’ condition but is instead returned to the average condition for a working system of its age. Examples include complex systems where the repair or replacement of one component does not materially affect the condition of the whole system.For a system with decreasing reliability it will become increasingly expensive to maintain operation by minimal repairs, and the question then arises as to when the entire system should be replaced. We consider cases where the failure distribution can be modelled by the Weibull distribution. Two policies have been suggested for this case. One is to replace at a fixed time and the other is to replace at a fixed number of failures. We consider a third policy, to replace at the next failure after a fixed time, and show that it is optimal.Expressions to decide the replacement point and the cost of this policy are derived. Unfortunately these do not give rise to explicit representations, and so they are used to provide extensive numerical comparisons of the policies in a search for effective explicit approximations. Conclusions are drawn from these comparisons regarding the relative effectiveness of the policies and approximations.     

Sequencing interval situations and related games

Uncertainty accompanies almost every situation in real world and it influences our decisions. In sequencing situations it may affect parameters used to determine an optimal order in the queue, and consequently the decision of whether (or not) to rearrange the queue by sharing the realized cost savings. This paper extends the analysis of one-machine sequencing situations and their related cooperative games to a setting with interval data, i.e. when the agents’ costs per unit of time and/or processing time in the system lie in intervals of real numbers obtained by forecasting their values. The question addressed here is: How to determine an optimal order (if the initial order in the queue is not so) and which approach should be used to motivate the agents to adopt the optimal order? This question is an important one that deserves attention both in theory and practice.     

An efficient fault-tolerant decentralized commit protocol for single site failure

To maintain consistency on a distributed database system, a commit protocol is often employed to ensure that either all the sub-transactions of a transaction commit or all abort. Special care needs to be taken to ensure the correct functioning of a commit protocol in the face of node failures during the execution of the protocol. A protocol is said to be fault-tolerant if it properly commits or aborts, even if nodes fail.In this paper, we present a fault tolerant decentralized commit protocol which is message optimal in the absence of failures. Furthermore, the protocol (FTDCP) ensures that all sites can achieve a consistent final decision by at most 4 extra messages in the single site failure situation.     

The average optimality of a repair-limit replacement policy

We consider a minimal-repair and replacement problem of a reliability system whose state at a failure is described by a pair of two attributes, i.e., the total number of its past failures and the current failure level. It is assumed that the system is bothered by more frequent and more costly failures as time passes. Our problem is to find and/or characterize a minimal-repair and replacement policy of minimizing the long-run average expected maintenance cost per unit time over the infinite time horizon. Formulating the problem as a semi-Markov decision process, we show that a repairlimit replacement policy is average optimal. That is, for each total number of past system failures, there exists a threshold, called a repair limit, such that it is optimal to repair minimally if the current failure level is lower than the repair limit, and to replace otherwise. Furthermore, the repair limit is decreasing in the total number of past system failures.     

A stochastic model for joint spare parts inventory and planned maintenance optimisation

Spare parts demands are usually generated by the need of maintenance either preventively or at failures. These demands are difficult to predict based on historical data of past spare parts usages, and therefore, the optimal inventory control policy may be also difficult to obtain. However, it is well known that maintenance costs are related to the availability of spare parts and the penalty cost of unavailable spare parts consists of usually the cost of, for example, extended downtime for waiting the spare parts and the emergency expedition cost for acquiring the spare parts. On the other hand, proper planned maintenance intervention can reduce the number of failures and associated costs but its performance also depends on the availability of spare parts. This paper presents the joint optimisation for both the inventory control of the spare parts and the Preventive Maintenance (PM) inspection interval. The decision variables are the order interval, PM interval and order quantity. Because of the random nature of plant failures, stochastic cost models for spare parts inventory and maintenance are derived and an enumeration algorithm with stochastic dynamic programming is employed for finding the joint optimal solutions over a finite time horizon. The delay-time concept developed for inspection modelling is used to construct the probabilities of the number of failures and the number of the defective items identified at a PM epoch, which has not been used in this type of problems before. The inventory model follows a periodic review policy but with the demand governed by the need for spare parts due to maintenance. We demonstrate the developed model using a numerical example.     

Two-stage generalized age maintenance of a queue-like production system

In general, the initiation of preventive maintenance should be based on the technical state as well as the operating state of a production system. Since the operating state of a production system is often subject to fluctuations in time, the planning of preventive maintenance at preset points in time (e.g. age/block replacement) cannot be optimal. Therefore, we propose a so-called two-stage maintenance policy, which - in a first stage - uses the technical state of the production system to determine a finite interval [t, t + At] during which preventive maintenance must be carried out, and - in a second stage - uses the operating state of the production system to determine the optimal starting time t̂ for preventive maintenance within that interval. A generalized age maintenance policy optimizing both t and At is formulated in the first stage. To this end, the actual starting time of preventive maintenance is modelled in terms of a uniform distribution over the maintenance interval. Moreover, the expected costs of preventive maintenance are modelled as a decreasing function of the interval size. An efficient algorithm is developed to demonstrate the optimal strategy for a queue-like production system, via numerical results that offer useful insights.     

On the terminal control problem

A minimum-time problem is considered, where the final point is locally controllable. It is shown that it is possible to construct a suboptimal control with a transfer time close to the optimal transfer time of the relaxed system. The resulting trajectory will satisfy initial and final conditions. Furthermore, it is shown that, if an optimal solution exists for the problem, then this optimal solution is also an optimal solution of the relaxed problem. In this case, the relaxed problem need not be solved.The authors wish to thank Dr. D. Hazan, Scientific Department, Ministry of Defense, Israel, for a fruitful discussion of this problem.     

Checking weak optimality of the solution to linear programming with interval right-hand side

The interval linear programming (IvLP) is a method for decision making under uncertainty. A weak feasible solution to IvLP is called weakly optimal if it is optimal for some scenario of the IvLP. One of the basic and difficult tasks in IvLP is to check whether a given point is weak optimal. In this paper, we investigate linear programming problems with interval right-hand side. Some necessary and sufficient conditions for checking weak optimality of given feasible solutions are established, based on the KKT conditions of linear programming. The proposed methods are simple, easy to implement yet very effective, since they run in polynomial time.     

Reliability analysis of a single warm-standby system subject to repairable and nonrepairable failures

An n-unit system provisioned with a single warm standby is investigated. The individual units are subject to repairable failures, while the entire system is subject to a nonrepairable failure at some finite but random time in the future. System performance measures for systems observed over a time interval of random duration are introduced. Two models to compute these system performance measures, one employing a policy of block replacement, and the other without a block replacement policy, are developed. Distributional assumptions involving distributions of phase type introduce matrix Laplace transformations into the calculations of the performance measures. It is shown that these measures are easily carried out on a laptop computer using Microsoft Excel. A simple economic model is used to illustrate how the performance measures may be used to determine optimal economic design specifications for the warm standby.     

A condition based maintenance model for a two-unit series system

This paper discusses a condition based maintenance model with exponential failures and fixed inspection intervals for a two-unit system in series. The condition of each unit, such as vibration or heat, is monitored at equidistant time intervals. The condition indicator variables for each unit are used to decide whether to repair an individual unit or to overhaul the whole system. After a maintenance action is performed the monitored condition indicator variable takes on its initial value. Each unit can fail only once within an inspection interval and when one or both units fail the system fails. The probability of failure is exponential and the failure rate is dependent on the condition. The cost to be minimized is the long-run average cost of maintenance actions and failures. We study the optimal solution to this problem obtained via dynamic programming.     

Determination/estimation of an optimal replacement interval under minimal repair

In this paper the problem of estimation of an optimal replacement interval for a system which is minimally repaired at failures is studied. The problem is investigated both under a parametric and a nonparametric form of the failure intensity of the system. It is assumed that observational data from n systems are available. Some asymptotic results are shown. A graphical procedure for determining/estimating an optimal replacement interval is presented. The procedure is particularly valuable for sensitivity analyses, for example with respect to the costs involved.     

Extended optimal inspection policies for a system in storage

A system such as missiles and spare parts of aircraft has to perform a normal operation in a severe environment at any time when it is used. However, the system is in storage for a long time from the delivery to the usage and its reliability goes down with time. Thus, a system in storage should be inspected and maintained at periodic times to hold a higher reliability than is prespecified.The following inspection model is considered: A system has three types of units, where unit 1 is maintained, unit 21 is not maintained but is replaced and unit 22 is neither maintained nor replaced. The system is overhauled if its reliability becomes lower than a prespecified probability. The number of replacements and time until overhaul are derived. Using these results, the average cost is obtained and both an optimal inspection time and an optimal replacement time to minimize it are numerically discussed.     

在折现率大于零的情况下,具有完成时间和残值不确定性的R&D项目的投资策略

利用随机停时理论 ,考虑 R&D项目的连续投资策略 .在折现率大于零的情况下 ,给出了具有建设期和残值的不确定性的 R&D投资模型、放弃 R&D项目投资的临界值和最优决策规则 ,并讨论参数对临界值的影响 .也进一步验证了随机停时理论和实物期权理论在投资决策分析中的一致性 .