A Note on Pseudodynamic Cost Limit Replacement Model

1998 ◽  
Vol 05 (03) ◽  
pp. 287-292 ◽  
Author(s):  
Chung Hyeon Choi ◽  
Won Young Yun
Keyword(s):  
Replacement Policy ◽  
Repair Cost ◽  
Numerical Examples ◽  
Cost Rate ◽  
Replacement Model ◽  
Mean Cost ◽  
Cost Limit ◽  
Better Than

In this note, a pseudodynamic cost limit replacement policy presented by Park1 is considered. Park1 showed that the pseudodynamic policy is inferior to constant repair cost limit policy. In this note, the correct mean cost rate under the same assumption in the Park's model is obtained and the pseudodynamic policy is shown to be better than the constant repair cost limit policy2 through the same numerical examples of Park.1

REPLACEMENT MODEL WITH CUMULATIVE REPAIR COST LIMIT FOR A TWO-UNIT SYSTEM UNDER FAILURE RATE INTERACTION BETWEEN UNITS

2012 ◽  
Vol 19 (05) ◽  
pp. 1250023 ◽  
Author(s):  
MIN-TSAI LAI
Keyword(s):  
Failure Rate ◽  
Replacement Policy ◽  
Repair Cost ◽  
Unit System ◽  
Model Combining ◽  
Long Run ◽  
Replacement Model ◽  
Rate Interaction ◽  
Failure Rate Interaction ◽  
Cost Limit

In this paper, a periodical replacement model combining the concept of cumulative repair cost limit for a two-unit system with failure rate interaction is presented. In this model, whenever unit 1 fails, it causes a certain amount of damage to unit 2 by increasing the failure rate of unit 2 of a certain degree. Unit 2 failure whenever occurs causes unit 1 into failure at the same time and then the total failure of the system occurs. Without failure rate interaction between units, the failure rates of two units also increase with age. When unit 1 fails, the necessary repair cost is estimated and is added to the accumulated repair cost. If the accumulated repair cost is less than a pre-determined limit L, unit 1 is corrected by minimal repair. Otherwise, the system is preventively replaced by a new one. Under periodical replacement policy and cumulative repair cost limit, the long-run expected cost per unit time is derived by introducing relative costs as a criterion of optimality. The optimal period T* which minimizes that cost is discussed. A numerical example is given to illustrate the method.

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 modified block replacement policy with two variables and general random minimal repair cost

1996 ◽  
Vol 33 (2) ◽  
pp. 557-572 ◽  
Author(s):  
Shey-Huei Sheu
Keyword(s):  
Operating System ◽  
Replacement Policy ◽  
Repair Cost ◽  
Minimal Repair ◽  
Expected Cost ◽  
Cost Rate ◽  
Age Dependent ◽  
Modified Block ◽  
The Cost ◽  
Random Part

This paper considers a modified block replacement with two variables and general random minimal repair cost. Under such a policy, an operating system is preventively replaced by new ones at times kT (k= 1, 2, ···) independently of its failure history. If the system fails in [(k − 1)T, (k − 1)T+ T0) it is either replaced by a new one or minimally repaired, and if in [(k − 1) T + T0, kT) it is either minimally repaired or remains inactive until the next planned replacement. The choice of these two possible actions is based on some random mechanism which is age-dependent. The cost of the ith minimal repair of the system at age y depends on the random part C(y) and the deterministic part ci (y). The expected cost rate is obtained, using the results of renewal reward theory. The model with two variables is transformed into a model with one variable and the optimum policy is discussed.

GENERAL SEQUENTIAL IMPERFECT PREVENTIVE MAINTENANCE MODELS

2000 ◽  
Vol 07 (03) ◽  
pp. 253-266 ◽  
Author(s):  
DAMING LIN ◽  
MING J. ZUO ◽  
RICHARD C. M. YAM
Keyword(s):  
Weibull Distribution ◽  
Preventive Maintenance ◽  
Hazard Rate ◽  
Numerical Examples ◽  
Cost Rate ◽  
Effective Age ◽  
Rate Adjustment ◽  
The Mean ◽  
Mean Cost

This paper presents new sequential imperfect preventive maintenance (PM) models incorporating adjustment/improvement factors in hazard rate and effective age. The models are hybrid in the sense that they are combinations of the age reduction PM model and the hazard rate adjustment PM model. It is assumed that PM is imperfect: It not only reduces the effective age but also changes the hazard rate, while the hazard rate increases with the number of PMs. PM is performed in a sequence of intervals. The objective is to determine the optimal PM schedule to minimize the mean cost rate. Numerical examples for a Weibull distribution are given.

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