A bivariate optimal replacement policy for a repairable system

1994 ◽  
Vol 31 (04) ◽  
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∗.

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∗.

Cataloging of Unit Replacement Based on Long Run Repair Average Cost Rate (ACR) Based on Weibull Distribution Model

2021 ◽  
pp. 149-152
Author(s):  
K. Uma Maheswari ◽  
K. Subrahmanyam ◽  
A. Mallikarjuna Reddy
Keyword(s):  
Weibull Distribution ◽  
Average Cost ◽  
Replacement Policy ◽  
Weibull Analysis ◽  
Distribution Method ◽  
Major Repair ◽  
Optimal Replacement ◽  
Long Run ◽  
Wide Range ◽  
Optimal Replacement Policy

Large amounts of money are lost each year in the real-estate industry because of poor schedule and cost control, In Industry the investigated failure and repair pattern, reliabilities of generators, compressors, turbines, using simple statistical tools and simulation techniques. The repair duration is divided into the 1) Major repair 2) Minor repair, In major repair having (repair hour greater than a threshold valve) and Minor repair having (repair hour less than (or)equal to threshold valve). This approach is mainly for Weibull distribution method. In Weibull analysis is a common method for failure analysis and reliability engineering used in a wide range of applications. In this paper, the applicability of Weibull analysis for evaluating and comparing the reliability of the schedule performance of multiple projects is presented, while the successive performance of multiple projects is presented, while the successive repair times are increasing and are exposing to Weibull distribution, under these assumptions, an optimal replacement policy ‘T’ in which we replace the system, when the repair time reaches T. It can be determined that an optimal repair replacement policy T* such that long run average cost and the corresponding optimal replacement policy T* can be determined analytically.

scholarly journals A study on an optimal replacement policy for a deteriorating system under partial product process

10.26524/cm65 ◽  
2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Govindaraju P ◽  
Rajendiran R
Keyword(s):  
Explicit Expression ◽  
Average Cost ◽  
Replacement Policy ◽  
Partial Product ◽  
Maintenance Policy ◽  
Optimal Replacement ◽  
Optimal Replacement Policy ◽  
Optimal Maintenance ◽  
Random Shocks ◽  
Optimal Maintenance Policy

In this paper, we consider an optimal maintenance policy for a reparable deteriorating system subject to random shocks. For a reparable deteriorating system, the repair time by a partial product process and the failure mechanism by a generalized δshock process. Develop an explicit expression of the ling run average cost per unit time under N policy is studied.

scholarly journals A Monotone Process Maintenance Model for a Multistate System

2005 ◽  
Vol 42 (01) ◽  
pp. 1-14 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Average Cost ◽  
Process Model ◽  
Replacement Policy ◽  
Geometric Process ◽  
Optimal Replacement ◽  
Multistate System ◽  
Long Run ◽  
Optimal Replacement Policy ◽  
Monotone Process ◽  
Maintenance Model

In this paper, we study a monotone process maintenance model for a multistate system with k working states and ℓ failure states. By making different assumptions, we can apply the model to a multistate deteriorating system as well as to a multistate improving system. We show that the monotone process model for a multistate system is equivalent to a geometric process model for a two-state system. Then, for both the deteriorating and the improving system, we analytically determine an optimal replacement policy for minimizing the long-run average cost per unit time.

scholarly journals A repair replacement model

1990 ◽  
Vol 22 (02) ◽  
pp. 494-497 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Average Cost ◽  
Replacement Policy ◽  
Average Reward ◽  
Survival Times ◽  
System Form ◽  
Optimal Replacement ◽  
Long Run ◽  
Replacement Model ◽  
Optimal Replacement Policy ◽  
Long Run Average Reward

In this paper, we study a similar replacement model in which the successive survival times of the system form a process with non-increasing means, whereas the consecutive repair times after failure constitute a process with non-decreasing means. The system is replaced at the time of the Nth failure since the installation or last replacement. Based on the long-run average cost per unit time, we determine the optimal replacement policy N∗ and the maximum of the long-run average reward explicitly. Under additional conditions, the policy N∗ is even optimal among all replacement policies.

scholarly journals Cataloging Of Unit Replacement Based On Long Run Repair Average Cost Rate (Acr) Based On Weibull Distribution Model

2021 ◽  
Vol 12 (11) ◽  
pp. 1880-1885
Author(s):  
Dr. K. Uma Maheswari, Et. al.
Keyword(s):  
Weibull Distribution ◽  
Average Cost ◽  
Replacement Policy ◽  
Weibull Analysis ◽  
Distribution Method ◽  
Major Repair ◽  
Optimal Replacement ◽  
Long Run ◽  
Wide Range ◽  
Optimal Replacement Policy

Large amounts of money are lost each year in the real-estate industry because of poor schedule and cost control, In Industry the investigated failure and repair pattern, reliabilities of generators, compressors, turbines, using simple statistical tools and simulation techniques. The repair duration is divided into the 1)Major repair 2)Minor repair ,In major repair having(repair hour greater than a threshold valve)and Minor repair having(repair hour less than (or)equal to threshold valve).This approach is mainly for Weibull distribution method. In Weibull analysis is a common method for failure analysis and reliability engineering used in a wide range of applications. In this  paper, the applicability of Weibull analysis for evaluating and comparing the reliability of the schedule performance of multiple projects is presented, while the successive performance of multiple projects is presented ,while the successive repair times are increasing and are exposing  to Weibull distribution ,under these assumptions ,an optimal replacement policy ‘T’ in which we replace the system ,when the repair time reaches T. It can be determined that an optimal repair replacement policy T* such that long run average cost and the corresponding optimal replacement policy T* can be determined analytically.

scholarly journals A repair replacement model

1990 ◽  
Vol 22 (2) ◽  
pp. 494-497 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Average Cost ◽  
Replacement Policy ◽  
Average Reward ◽  
Survival Times ◽  
System Form ◽  
Optimal Replacement ◽  
Long Run ◽  
Replacement Model ◽  
Optimal Replacement Policy ◽  
Long Run Average Reward

In this paper, we study a similar replacement model in which the successive survival times of the system form a process with non-increasing means, whereas the consecutive repair times after failure constitute a process with non-decreasing means. The system is replaced at the time of the Nth failure since the installation or last replacement. Based on the long-run average cost per unit time, we determine the optimal replacement policy N∗ and the maximum of the long-run average reward explicitly. Under additional conditions, the policy N∗ is even optimal among all replacement policies.

scholarly journals A Monotone Process Maintenance Model for a Multistate System

2005 ◽  
Vol 42 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Lam Yeh
Keyword(s):  
Average Cost ◽  
Process Model ◽  
Replacement Policy ◽  
Geometric Process ◽  
Optimal Replacement ◽  
Multistate System ◽  
Long Run ◽  
Optimal Replacement Policy ◽  
Monotone Process ◽  
Maintenance Model

In this paper, we study a monotone process maintenance model for a multistate system with k working states and ℓ failure states. By making different assumptions, we can apply the model to a multistate deteriorating system as well as to a multistate improving system. We show that the monotone process model for a multistate system is equivalent to a geometric process model for a two-state system. Then, for both the deteriorating and the improving system, we analytically determine an optimal replacement policy for minimizing the long-run average cost per unit time.

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