An optimal inspection and replacement policy for a deteriorating system

1986 ◽  
Vol 23 (04) ◽  
pp. 973-988 ◽  
Author(s):  
Masamitsu Ohnishi ◽  
Hajime Kawai ◽  
Hisashi Mine
Keyword(s):  
Markov Process ◽  
Optimal Policy ◽  
Continuous Time ◽  
Average Cost ◽  
Control Limit ◽  
Replacement Policy ◽  
Optimal Time ◽  
Time Interval ◽  
Long Run ◽  
Monotonic Properties

This paper investigates a system whose deterioration is expressed as a continuous-time Markov process. It is assumed that the state of the system cannot be identified without inspection. This paper derives an optimal policy minimizing the expected total long-run average cost per unit time. It gives the optimal time interval between successive inspections and determines the states at which the system is to be replaced. Furthermore, under some reasonable assumptions reflecting the practical meaning of the deterioration, it is shown that the optimal policy has monotonic properties. A control limit rule holds for replacement, and the time interval between successive inspections decreases as the degree of deterioration increases.

An optimal inspection and replacement policy for a deteriorating system

1986 ◽  
Vol 23 (4) ◽  
pp. 973-988 ◽  
Author(s):  
Masamitsu Ohnishi ◽  
Hajime Kawai ◽  
Hisashi Mine
Keyword(s):  
Markov Process ◽  
Optimal Policy ◽  
Continuous Time ◽  
Average Cost ◽  
Control Limit ◽  
Replacement Policy ◽  
Optimal Time ◽  
Time Interval ◽  
Long Run ◽  
Monotonic Properties

This paper investigates a system whose deterioration is expressed as a continuous-time Markov process. It is assumed that the state of the system cannot be identified without inspection. This paper derives an optimal policy minimizing the expected total long-run average cost per unit time. It gives the optimal time interval between successive inspections and determines the states at which the system is to be replaced. Furthermore, under some reasonable assumptions reflecting the practical meaning of the deterioration, it is shown that the optimal policy has monotonic properties. A control limit rule holds for replacement, and the time interval between successive inspections decreases as the degree of deterioration increases.

An optimal inspection and replacement policy for a deteriorating system

1986 ◽  
Vol 23 (04) ◽  
pp. 973-988 ◽  
Author(s):  
Masamitsu Ohnishi ◽  
Hajime Kawai ◽  
Hisashi Mine
Keyword(s):  
Markov Process ◽  
Optimal Policy ◽  
Continuous Time ◽  
Average Cost ◽  
Control Limit ◽  
Replacement Policy ◽  
Optimal Time ◽  
Time Interval ◽  
Long Run ◽  
Monotonic Properties

This paper investigates a system whose deterioration is expressed as a continuous-time Markov process. It is assumed that the state of the system cannot be identified without inspection. This paper derives an optimal policy minimizing the expected total long-run average cost per unit time. It gives the optimal time interval between successive inspections and determines the states at which the system is to be replaced. Furthermore, under some reasonable assumptions reflecting the practical meaning of the deterioration, it is shown that the optimal policy has monotonic properties. A control limit rule holds for replacement, and the time interval between successive inspections decreases as the degree of deterioration increases.

scholarly journals A Time-Replacement Policy for Multistate Systems with Aging Components under Maintenance, from a Component Perspective

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Chao-Hui Huang ◽  
Chun-Ho Wang
Keyword(s):  
Continuous Time ◽  
Markov Models ◽  
Replacement Policy ◽  
Optimal Time ◽  
Entire System ◽  
Multiple Components ◽  
Performance Indexes ◽  
Long Run ◽  
Multistate Systems ◽  
Markov Reward

This study aims for multistate systems (MSSs) with aging multistate components (MSCs) to construct a time-replacement policy and thereby determine the optimal time to replace the entire system. The nonhomogeneous continuous time Markov models (NHCTMMs) quantify the transition intensities among the degradation states of each component. The dynamic system state probabilities are therefore assessed using the established NHCTMMs. Solving NHCTMMs is rather complicated compared to homogeneous continuous time Markov models (HCTMMs) in determining reliability related performance indexes. Often, traditional mathematics cannot acquire accurate explicit expressions, in particular, for multiple components that are involved in designed system configuration. To overcome this difficulty, this study uses Markov reward models and the bound approximation approach to assess rewards of MSSs with MSCs, including such things as total maintenance costs and the benefits of the system staying in acceptable working states. Accordingly, we established a long-run expected benefit (LREB) per unit time, representing overall MSS performance through a lifetime, to determine the optimal time to replace the entire system, at which time the LREB values are maximized. Finally, a simulated case illustrates the practicability of the proposed approach.

A bivariate optimal replacement policy for a repairable system

1994 ◽  
Vol 31 (4) ◽  
pp. 1123-1127 ◽  
Author(s):  
Yuan Lin Zhang
Keyword(s):  
Explicit Expression ◽  
Average Cost ◽  
Replacement Policy ◽  
Repairable System ◽  
Optimal Replacement ◽  
Long Run ◽  
Optimal Replacement Policy ◽  
Working Age ◽  
Better Than

In this paper, a repairable system consisting of one unit and a single repairman is studied. Assume that the system after repair is not as good as new. Under this assumption, a bivariate replacement policy (T, N), where T is the working age and N is the number of failures of the system is studied. The problem is to determine the optimal replacement policy (T, N)∗such that the long-run average cost per unit time is minimized. The explicit expression of the long-run average cost per unit time is derived, and the corresponding optimal replacement policy can be determined analytically or numerically. Finally, under some conditions, we show that the policy (T, N)∗ is better than policies N∗ or T∗.

Optimal repair/replacement policy for a general repair model

2001 ◽  
Vol 33 (1) ◽  
pp. 206-222 ◽  
Author(s):  
Xiaoyue Jiang ◽  
Viliam Makis ◽  
Andrew K. S. Jardine
Keyword(s):  
Average Cost ◽  
Failure Time ◽  
Operating Time ◽  
Replacement Policy ◽  
Repair Cost ◽  
Virtual Age ◽  
Preventive Replacement ◽  
Long Run ◽  
Special Cases ◽  
Cost Limit

In this paper, we study a maintenance model with general repair and two types of replacement: failure and preventive replacement. When the system fails a decision is made whether to replace or repair it. The repair degree that affects the virtual age of the system is assumed to be a random function of the repair-cost and the virtual age at failure time. The system can be preventively replaced at any time before failure. The objective is to find the repair/replacement policy minimizing the long-run expected average cost per unit time. It is shown that a generalized repair-cost-limit policy is optimal and the preventive replacement time depends on the virtual age of the system and on the length of the operating time since the last repair. Computational procedures for finding the optimal repair-cost limit and the optimal average cost are developed. This model includes many well-known models as special cases and the approach provides a unified treatment of a wide class of maintenance models.

Optimal control of a finite dam: average-cost case

1985 ◽  
Vol 22 (02) ◽  
pp. 480-484 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Optimal Control ◽  
Wiener Process ◽  
Release Rate ◽  
Optimal Policy ◽  
Average Cost ◽  
Output Rate ◽  
Penalty Cost ◽  
Long Run ◽  
Negative Drift ◽  
Finite Dam

We consider the problem of minimizing the long-run average cost per unit time of operating a finite dam in the class of the policies of the following type. Assume that the dam is initially empty, the release rate is kept at 0 until the dam storage increases to λ, and as soon as this occurs, water is released at rate M, then the output rate is kept at M as long as the dam storage is more than τ and it must be decreased to 0 if the dam storage becomes τ. We assume that the input of water into the finite dam is a Wiener process with non-negative drift μ and variance parameter σ 2. There is a cost in increasing the output rate from 0 to M as well as in decreasing the rate from M to 0 and whenever the dam storage is below level a, there is a penalty cost per unit time depending on the level. A reward is given for each unit of water released. In this paper, the long-run average cost per unit time is determined, and therefore the optimal policy can be found numerically.

scholarly journals On the control of a truncated general immigration process through the introduction of a predator

2006 ◽  
Vol 2006 ◽  
pp. 1-12
Author(s):  
E. G. Kyriakidis
Keyword(s):  
Real Line ◽  
Optimal Policy ◽  
Average Cost ◽  
Control Limit ◽  
Decision Algorithm ◽  
Mild Conditions ◽  
Entire Real Line ◽  
Immigration Process ◽  
Markov Decision

This paper is concerned with the problem of controlling a truncated general immigration process, which represents a population of harmful individuals, by the introduction of a predator. If the parameters of the model satisfy some mild conditions, the existence of a control-limit policy that is average-cost optimal is proved. The proof is based on the uniformization technique and on the variation of a fictitious parameter over the entire real line. Furthermore, an efficient Markov decision algorithm is developed that generates a sequence of improving control-limit policies converging to the optimal policy.

scholarly journals Determining Optimal Replacement Policy with an Availability Constraint via Genetic Algorithms

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Shengliang Zong ◽  
Guorong Chai ◽  
Yana Su
Keyword(s):  
Genetic Algorithm ◽  
Average Cost ◽  
Operating Time ◽  
Threshold Value ◽  
Replacement Policy ◽  
Time Interval ◽  
Cost Rate ◽  
Optimal Replacement ◽  
Optimal Replacement Policy ◽  
Average Cost Rate

We develop a model and a genetic algorithm for determining an optimal replacement policy for power equipment subject to Poisson shocks. If the time interval of two consecutive shocks is less than a threshold value, the failed equipment can be repaired. We assume that the operating time after repair is stochastically nonincreasing and the repair time is exponentially distributed with a geometric increasing mean. Our objective is to minimize the expected average cost under an availability requirement. Based on this average cost function, we propose the genetic algorithm to locate the optimal replacement policyNto minimize the average cost rate. The results show that the GA is effective and efficient in finding the optimal solutions. The availability of equipment has significance effect on the optimal replacement policy. Many practical systems fit the model developed in this paper.

scholarly journals Optimal Maintenance of a Production-inventory System With Continuous Repair Times and Idle Periods

2020 ◽  
Vol Volume 14 ◽  
Keyword(s):  
Preventive Maintenance ◽  
Average Cost ◽  
Inventory System ◽  
Control Limit ◽  
Raw Material ◽  
Production Unit ◽  
Numerical Examples ◽  
Long Run ◽  
Production Inventory ◽  
Production Inventory System

In this paper two similar models for the maintenance of a production-inventory system are considered. In both models, an input generating installation supplies a buffer with a raw material and a production unit pulls the raw material from the buffer. The installation in the first model and the production unit in the second model deteriorate stochastically over time and the problem of their optimal preventive maintenance is considered. In the first model, it is assumed that the installation, after the completion of its maintenance, remains idle until the buffer is evacuated, while in the second model, it is assumed that the production unit, after the completion of its maintenance, remains idle until the buffer is filled up. The preventive and corrective repair times of the installation in the first model and the preventive and corrective repair times of the production unit in the second model are continuous random variables with known probability density functions. Under a suitable cost structure, semi-Markov decision processes are considered for both models in order to find a policy that minimizes the long-run expected average cost per unit time. A great number of numerical examples provide strong evidence that, for each fixed buffer content, the average-cost optimal policy is of control-limit type in both models, i.e. it prescribes a preventive maintenance of the installation in the first model and a preventive maintenance of the production unit in the second model if and only if their degree of deterioration is greater than or equal to a critical level. Using the usual regenerative argument, the average cost of the optimal control-limit policy is computed exactly in both models. Four numerical examples are also presented in which the preventive and corrective repair times follow the Exponential, the Weibull, the Gamma and the Log-Normal distribution, respectively.

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