Age-replacement policy and optimal work size

2002 ◽  
Vol 39 (2) ◽  
pp. 296-311 ◽  
Author(s):  
Jie Mi
Keyword(s):  
Time Distribution ◽  
Failure Time ◽  
Repair Time ◽  
Replacement Policy ◽  
Average Amount ◽  
Failure Time Distribution ◽  
Long Run ◽  
Random Failure ◽  
Age Replacement ◽  
Work Size

Suppose that there is a sequence of programs or jobs that are scheduled to be executed one after another on a computer. A program may terminate its execution because of the failure of the computer, which will obliterate all work the computer has accomplished, and the program has to be run all over again. Hence, it is common to save the work just completed after the computer has been working for a certain amount of time, say y units. It is assumed that it takes a certain time to perform a save. During the saving process, the computer is still subject to random failure. No matter when the computer failure occurs, it is assumed that the computer will be repaired completely and the repair time will be negligible. If saving is successful, then the computer will continue working from the end of the last saved work; if the computer fails during the saving process, then only unsaved work needs to be repeated. This paper discusses the optimal work size y under which the long-run average amount of work saved is maximized. In particular, the case of an exponential failure time distribution is studied in detail. The properties of the optimal age-replacement policy are also derived when the work size y is fixed.

Age-replacement policy and optimal work size

2002 ◽  
Vol 39 (02) ◽  
pp. 296-311 ◽  
Author(s):  
Jie Mi
Keyword(s):  
Time Distribution ◽  
Failure Time ◽  
Repair Time ◽  
Replacement Policy ◽  
Average Amount ◽  
Failure Time Distribution ◽  
Long Run ◽  
Random Failure ◽  
Age Replacement ◽  
Work Size

Suppose that there is a sequence of programs or jobs that are scheduled to be executed one after another on a computer. A program may terminate its execution because of the failure of the computer, which will obliterate all work the computer has accomplished, and the program has to be run all over again. Hence, it is common to save the work just completed after the computer has been working for a certain amount of time, say y units. It is assumed that it takes a certain time to perform a save. During the saving process, the computer is still subject to random failure. No matter when the computer failure occurs, it is assumed that the computer will be repaired completely and the repair time will be negligible. If saving is successful, then the computer will continue working from the end of the last saved work; if the computer fails during the saving process, then only unsaved work needs to be repeated. This paper discusses the optimal work size y under which the long-run average amount of work saved is maximized. In particular, the case of an exponential failure time distribution is studied in detail. The properties of the optimal age-replacement policy are also derived when the work size y is fixed.

AN OPPORTUNITY-BASED AGE REPLACEMENT POLICY CONSIDERING WARRANTY

1999 ◽  
Vol 06 (03) ◽  
pp. 229-236 ◽  
Author(s):  
BERMAWI P. ISKANDAR ◽  
HIROAKI SANDOH
Keyword(s):  
Time Distribution ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Replacement Policy ◽  
Minimal Repair ◽  
Failure Time Distribution ◽  
Warranty Period ◽  
Preventive Replacement ◽  
Long Run ◽  
Age Replacement

This study discusses an opportunity-based age replacement policy for a system which has a warranty period (0, S]. When the system fails at its age x≤S, a minimal repair is performed. If an opportunity occurs to the system at its age x for S<x<T, we take the opportunity with probability p to preventively replace the system, while we conduct a corrective replacement when it fails on (S, T). Finally if its age reaches T, we execute a preventive replacement. Under this replacement policy, the design variable is T. For the case where opportunities occur according to a Poisson process, a long-run average cost of this policy is formulated under a general failure time distribution. It is, then, shown that one of the sufficient conditions where a unique finite optimal T* exists is that the failure time distribution is IFR (Increasing Failure Rate). Numerical examples are also presented for the Weibull failure time distribution.

OPTIMAL AGE REPLACEMENT AND INSPECTION POLICIES WITH RANDOM FAILURE AND REPLACEMENT TIMES

2011 ◽  
Vol 18 (05) ◽  
pp. 405-416 ◽  
Author(s):  
TOSHIO NAKAGAWA ◽  
XUFENG ZHAO ◽  
WON YOUNG YUN
Keyword(s):  
Finite Time ◽  
Failure Time ◽  
Replacement Policy ◽  
Inspection Cost ◽  
Preventive Replacement ◽  
Optimal Policies ◽  
Excess Costs ◽  
Random Failure ◽  
Age Replacement ◽  
Replacement Time

It is well-known in the standard age replacement policy that a finite preventive replacement time does not exist when the failure time is exponential and the optimal preventive replacement time is nonrandom. It is shown that when the failure time is exponential, a finite time exists by introducing the shortage and excess costs. In addition, the random age replacement is proposed and similar discussions are made. Furthermore, the periodic and random inspection policies are taken up, and their optimal policies are shown to correspond theoretically to those of the age replacement ones. It is shown finally that when the random inspection cost is the half of the periodic one, two expected costs are almost the same.

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.

A hybrid preventive maintenance model for systems with partially observable degradation

2020 ◽  
Vol 31 (3) ◽  
pp. 345-365 ◽  
Author(s):  
Maxim Finkelstein ◽  
Ji Hwan Cha ◽  
Gregory Levitin
Keyword(s):  
Preventive Maintenance ◽  
Replacement Policy ◽  
Hybrid Strategy ◽  
Cost Rate ◽  
Shot Noise Process ◽  
Shock Process ◽  
Long Run ◽  
Age Replacement ◽  
Partially Observable ◽  
Maintenance Model

Abstract A new model of hybrid preventive maintenance of systems with partially observable degradation is developed. This model combines condition-based maintenance with age replacement maintenance in the proposed, specific way. A system, subject to a shock process, is replaced on failure or at some time ${T}_S$ if the number of shocks experienced by this time is greater than or equal to m or at time $T&gt;{T}_S$ otherwise, whichever occurs first. Each shock increases the failure rate of the system at the random time of its occurrence, thus forming a corresponding shot-noise process. The real deterioration of the system is partially observed via observation of the shock process at time ${T}_S$. The corresponding optimization problem is solved and a detailed numerical example demonstrates that the long-run cost rate for the proposed optimal hybrid strategy is smaller than that for the standard optimal age replacement policy.

Replacement Policy for Cold Standby Repairable System with Priority in Use by Using Arithmetico-Geometric Process

2019 ◽  
Vol 27 (03) ◽  
pp. 2050009
Author(s):  
Raosaheb V. Latpate ◽  
Babasaheb K. Thorve
Keyword(s):  
Working Time ◽  
Repair Time ◽  
Replacement Policy ◽  
Repairable System ◽  
Policy System ◽  
Geometric Process ◽  
Long Run ◽  
Cold Standby ◽  
Study Component ◽  
Renewal Cycle

In this paper, we consider the arithmetico-geometric process (AGP) repair model. Here, the system has two nonidentical component cold standby repairable system with one repairman. Under this study, component 1 has given priority in use. It is assumed that component 2 after repair is as good as new, whereas the component 1 follows AGP. Under these assumptions, by using AGP repair model, we present a replacement policy based on number of failures, [Formula: see text], of component 1 such that long-run expected reward per unit time is maximized. For this policy, system can be replaced when number of failure of the component 1 reaches to [Formula: see text]. Working time of the component 1 is AGP and it is stochastically decreasing whereas repair time of the component 1 is AGP which is stochastically increasing. The expression for long-run expected reward per unit time for a renewal cycle is derived and illustrated proposed policy with numerical examples by assuming Weibull distributed working time and repair time of the component 1. Also, proposed AGP repair model is compared with the geometric process repair model.

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