• Journal of Applied Reliability
• /
• v.11 no.2
• /
• pp.167-176
• /
• 2011

This paper introduces models for preventive maintenance policies and considers periodic preventive maintenance policy with minimal repair when the failure of system occurs. It is assumed that minimal repairs do not change the failure rate of the system. The failure rate under prevention maintenance received an effect by a previously prevention maintenance and the slope of failure rate increases the model where it considered. Also the start point of failure rate under prevention maintenance considers the degradation of system and that it increases quotient, it assumed. Per unit time it bought an expectation cost from under this prevention maintenance policy. We obtain the optimal periodic time and the number for the periodic preventive maintenance by using Nakagawa's Algorithm, which minimizes the expected cost per unit time.

• Journal of the military operations research society of Korea
• /
• v.24 no.1
• /
• pp.98-109
• /
• 1998

This study develops a maintenance strategy for a reparable 2-unit standby system. The maintenance strategy implies the waiting time to call the repair facility when the unit-1 fails. Almeida and Souza set up the multi-attribute utility function consisting of system availability and repair cost for several maintenance strategies and decide the optimal maintenance strategy that maximize the expected value of the utility function. We decide the optimal maintenance strategy satisfying the following two criteria about the utility function : maximum variance using Almeida and Souza's utility function. It both criteria are not satisfied at the same time for every strategies, the strategy maximizing the lower confidence limit for expected utility function is regarded as an optimal one.

• International Journal of Highway Engineering
• /
• v.19 no.3
• /
• pp.65-70
• /
• 2017

PURPOSES : Pavement Management System contains the data that describe the condition of the road. Under limited budget, the data can be utilized for efficient plans. The objective of this research is to develop a mixed integer program model that maximizes remaining durable years (or Lane-Kilometer-Years) in road maintenance planning. METHODS : An optimization model based on a mixed integer program is developed. The model selects a cluster of sectors that are adjacent to each other according to the road condition. The model also considers constraints required by the Seoul Metropolitan Facilities Management Corporation. They select two lanes at most not to block the traffic and limit the number of sectors for one-time construction to finish the work in given time. We incorporate variable cost constraints. As the model selects more sectors, the unit cost of the construction becomes smaller. The optimal choice of the number of sectors is implemented using piecewise linear constraints. RESULTS : Data (SPI) collected from Pavement Management System managed by Seoul Metropolitan City are fed into the model. Based on the data and the model, the optimal maintenance plans are established. Some of the optimal plans cannot be generated directly in existing heuristic approach or by human intuition. CONCLUSIONS:The mathematical model using actual data generates the optimal maintenance plans.

• Journal of the military operations research society of Korea
• /
• v.26 no.1
• /
• pp.70-88
• /
• 2000

In this research we consider a statistical model to estimate the optimal maintenance manpower of aircraft which we use at present. We design a multiple regression model, apply to three types of aircraft to estimate the optimal maintenance manpower of aircraft. This paper provides reasonable results about maintenance manpower of aircraft, and contributes accomplishment of mission for air and air support operations.

• International Journal of Reliability and Applications
• /
• v.12 no.1
• /
• pp.41-48
• /
• 2011

This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.2
• /
• pp.367-377
• /
• 2006

This paper develops a periodic preventive maintenance(PM) policy following the expiration of warranty. Two types of warranty are considered: renewing warranty and non-renewing warranty. Also, we consider the situation where each PM cost is an increasing function of the PM effect. We determine the optimal number of PM's before replacing the system by a new one and the optimal length of period for the periodic PM following the expiration of warranty. Explicit solutions to determine the optimal periodic PM are presented for the Weibull distribution case.

• Journal of Korean Society for Quality Management
• /
• v.31 no.3
• /
• pp.193-204
• /
• 2003

In this paper, we consider a periodic preventive maintenance(PM) policy in which each PM reduces the hazard rate but remains the pattern of hazard rate unchanged. And the system undergoes only minimal repairs at failures between PM's. The expected cost rate per unit time is obtained. The optimal number N of PM and the optimal period x, which minimize the expected cost rate per unit time are discussed. Explicit solutions for the optimal periodic PM are given for the Weibull distribution case.

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.6
• /
• pp.785-793
• /
• 1999

There are two kinds of method in ship maintenance. One is the corrective maintenance and the other is the preventive maintenance. For these maintenances recently the stochastic techniques are widely used to keep the maximum availibility and the optimal maintenance period minimizing a given cost function. Thus this paper suggest a method to decide the optimal policy of ship's maintenances by using dynamic programming and the effectiveness of the method is verified through several examples in which failure rates and maintenance data of ship's machineries and parts are given.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.61 no.2
• /
• pp.67-73
• /
• 2012

This paper proposes optimal maintenance strategies for power distribution systems that involve the use of the reliability-centered maintenance (RCM) method. We developed an improved decision model based on the Markov process. This model can obtain the optimal inspection interval and maintenance method based on the total expected cost. We used ordinal optimization for solving the optimal problem. Optimal maintenance strategies were presented by applying the developed method to the RBTS model. A B/C analysis proved that these strategies offer maximum benefit-to-cost.

• Journal of Applied Reliability
• /
• v.16 no.3
• /
• pp.224-230
• /
• 2016

Purpose: Military maintenance involves corrective and preventive actions carried out to keep a system in or restore it to a predetermined condition. This research develops an optimal maintenance cycle for aviation oil testing equipment with acceptable reliability level and minimum maintenance cost. Methods: The optimal maintenance policy in this research aims to satisfy the desired reliability level at the lowest cost. We assume that the failure process of equipment follows the power law non-homogeneous Poisson process model and the maintenance system is a minimal repair policy. Estimation and other statistical procedures (trend test and goodness of fit test) are given for this model. Results: With time varying failure rate, we developed reliability-based maintenance cost optimization model. This model will reduce the ownership cost through adopting a proactive reliability focused maintenance system. Conclusion: Based on the analysis, it is recommended to increase the current maintenance cycle by three times which is 0.5 year to 1.5 years. Because of the system's built-in self-checking features, it is not expected to have any problems of preventative maintenance cycle.