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.

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∗.

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

10.26524/cm66 ◽  
2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Govindaraju P ◽  
Ashok Kumar P
Keyword(s):  
Average Cost ◽  
Process Model ◽  
Replacement Policy ◽  
Partial Product ◽  
Cost Rate ◽  
Optimal Replacement ◽  
Optimal Replacement Policy ◽  
Monotone Process ◽  
Average Cost Rate

In this paper, we study a degenerative reparable system with two types of failure states.Any system after repair can not be as good as new. A general monotone process model for adegenerative system under partial product process is used. We use a replacement policy N based on the failure number of the system and to determine an optimal replacement policy N* such that the average cost rate is minimized.

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∗.

Sequential imperfect preventive maintenance policy with random maintenance quality under reliability limit

2011 ◽  
Vol 225 (8) ◽  
pp. 1926-1935 ◽  
Author(s):  
Z Wang ◽  
J Yang ◽  
G Wang ◽  
G Zhang
Keyword(s):  
Failure Rate ◽  
Preventive Maintenance ◽  
Average Cost ◽  
Numerical Control ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Proposed Model ◽  
Optimal Maintenance ◽  
Average Cost Rate ◽  
Optimal Maintenance Policy

To determine the optimal maintenance number for a system with random maintenance quality in infinite time horizon, a sequential imperfect preventive maintenance model considering reliability limit is proposed. The proposed model is derived from the combination of the Kijima type virtual age model and the failure rate adjustment model. Maintenance intervals of the proposed model are obtained through an iteration method when both failure rate increase factor and maintenance restoration factor are random variables with a uniform distribution. The optimal maintenance policy is presented by minimizing the long-run average cost rate. A real numerical example for the failures of numerical control equipment is given to demonstrate the proposed model. Finally, a discussion is presented to show how the optimal average cost rate depends on the different cost parameters. The results show that in order to satisfy the practical requirements of high reliability, it is necessary and worthwhile to consider the system's reliability limit in preventive maintenance practice.

OPTIMAL MAINTENANCE OF SEMI-MARKOV MISSIONS

2014 ◽  
Vol 29 (1) ◽  
pp. 77-98 ◽  
Author(s):  
Bora Çekyay ◽  
Süleyman Özekici
Keyword(s):  
Markov Process ◽  
Random Sequence ◽  
Replacement Policy ◽  
Markov Renewal Process ◽  
Cost Structures ◽  
Optimal Replacement ◽  
Optimal Replacement Policy ◽  
Semi Markov Process ◽  
Optimal Maintenance ◽  
Failure Properties

We analyze optimal replacement and repair problems of semi-Markov missions that are composed of phases with random sequence and durations. The mission process is the minimal semi-Markov process associated with a Markov renewal process. The system is a complex one consisting of non-identical components whose failure properties depend on the mission process. We prove some monotonicity properties for the optimal replacement policy and analyze the optimal repair problem under different cost structures.

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.

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.

Opportunistic maintenance (OM) as a new advancement in maintenance approaches

2014 ◽  
Vol 20 (2) ◽  
pp. 98-121 ◽  
Author(s):  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin
Keyword(s):  
Current Trend ◽  
Replacement Policy ◽  
Practical Significance ◽  
Clear Understanding ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Content Type ◽  
Research Areas ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Purpose – This paper reviews the literature on opportunistic maintenance (OM) as new advance maintenance approach and policy. The purpose of this paper is to conceptually identify common principle and thereby provide absolute definition, concept and characteristics of this policy. Design/methodology/approach – A conceptual analysis was conducted on various literatures to clarify a number of principle and concepts as a method for understanding information on OM. The analysis involves the process of separating the compound terms used in the literatures into a few parts, analyse them and then recombining them to have more clear understanding of the policy. Findings – The paper discussed the maintenance approach, genealogy, principle, concept and applications of OM both in numerical analysis and real industry. OM policy is developed based on combination of age replacement policy and block replacement policy and in practical; OM is applied as the combination of corrective maintenance which is applied when any failure occurred, with preventive maintenance (PM) – a planned and scheduled maintenance approach to prevent failure to happen. Any machine shutdown or stoppages due to failure is the “opportunity” to conduct PM even though it is not as planned. The characterization of OM was provided in order to present its theoretical novelty for researchers and practical significance for industries. Practical implications – To date, there is no publication that reviews the OM in-depth and provides clear understanding on the topic. Therefore, this paper aims to show lineage of OM and the current trend in researches. This discussion will pave the way of new research areas on this optimal maintenance policy. Clear definition and principle of OM provided in this paper will trigger interest in its practicality as well as aid industries to understand and conduct OM in operation plant. Originality/value – This paper discussed the available literature about OM in various perspectives and scopes for further understanding of the topic by maintenance management professionals and researchers. Therefore, OM can be widely studied and applied in real industry as it is an effective and optimal maintenance policy.

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.

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