• Title/Summary/Keyword: optimal maintenance

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Management System for Improving RAM of Equipment in Container Terminals (컨테이너 터미널 장비의 RAM 향상을 위한 관리 시스템)

  • Yun, Won-Young;Kim, Gui-Rae;Ha, Young-Ju;Son, Bum-Shin;Kim, Hey-Jeong
    • IE interfaces
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    • v.19 no.3
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    • pp.245-254
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    • 2006
  • Equipments in container terminal have a lot of parts, and an equipment breakdown affects the productivity of terminal. In this paper, we develop a maintenance management system for improving reliability, availability and maintainability of equipments in container terminals. The developed system consists of five modules : equipment structure module, equipment operation management module, maintenance control module, spare part control module and data analysis module. The system supports reliability engineers to manage and improve RAM of equipments in container terminals. For example, FMEA, failure state analysis and life distribution parameters estimation are easily or automatically done by the system. This system also provides optimal preventive maintenance intervals by simulation and optimal yearly PM schedules for equipments in container terminal are recommended.

Burn-in When Repair Costs Vary With Time

  • Na, Myung-Hwan;Lee, Sangyeol
    • Journal of Korean Society for Quality Management
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    • v.31 no.1
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    • pp.142-147
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    • 2003
  • Burn-in is a widely used method to eliminate the initial failures. Preventive maintenance policy such as block replacement with minimal repair at failure is often used in field operation. In this, paper burn-in and maintenance policy are taken into consideration at the same time. The cost of a minimal repair is assumed to be a non-decreasing function of its age. The problems of determining optimal burn-in times and optimal maintenance policy are considered.

A Study on Determining the Optimal Replacement Interval of the Rolling Stock Signal System Component based on the Field Data (필드데이터에 의한 철도차량 신호장치 구성품의 최적 교체주기 결정에 관한 연구)

  • Byoung Noh Park;Kyeong Hwa Kim;Jaehoon Kim
    • Journal of the Korean Society of Safety
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    • v.38 no.2
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    • pp.104-111
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    • 2023
  • Rolling stock maintenance, which focuses on preventive maintenance, is typically implemented considering the potential harm that may be inflicted to passengers in the event of failure. The cost of preventive maintenance throughout the life cycle of a rolling stock is 60%-75% of the initial purchase cost. Therefore, ensuring stability and reducing maintenance costs are essential in terms of economy. In particular, private railroad operators must reduce government support budget by effectively utilizing railroad resources and reducing maintenance costs. Accordingly, this study analyzes the reliability characteristics of components using field data. Moreover, it resolves the problem of determining an economical replacement interval considering the timing of scrapping railroad vehicles. The procedure for determining the optimal replacement interval involves five steps. According to the decision model, the optimal replacement interval for the onboard signal device components of the "A" line train is calculated using field data, such as failure data, preventive maintenance cost, and failure maintenance cost. The field data analysis indicates that the mileage meter is 9 years, which is less than the designed durability of 15 years. Furthermore, a life cycle in which the phase signal has few failures is found to be the same as the actual durability of 15 years.

Developing a Non-Periodic Preventive Maintenance Model Guaranteeing the Minimum Reliability (최소 신뢰도를 보장하는 비 주기적 예방보전 모형 개발)

  • Lee, Juhyun;Ahn, Suneung
    • Journal of Applied Reliability
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    • v.18 no.2
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    • pp.104-113
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    • 2018
  • Purpose: This paper proposes the non-periodic preventive maintenance policy based on the level of cumulative hazard intensity. We aim to construct a cost-effectiveness on the proposed model with relaxing the constraint on reliability. Methods: We use the level of cumulative hazard intensity as a condition variable, instead of reliability. Such a level of cumulative hazard intensity can derive the reliability which decreases as the frequency of preventive maintenance action increases. We also model the imperfect preventive maintenance action using the proportional age setback model. Conclusion: We provide a numerical example to illustrate the proposed model. We also analyze how the parameters of our model affect the optimal preventive maintenance policy. The results show that as long as high reliability is guaranteed, the inefficient preventive maintenance action is performed reducing the system operation time. Moreover, the optimal value of the proposed model is sensitive to changes in preventive maintenance cost and replacement cost.

Preventive maintenance model following the expiration of NFRRW (비재생무료교체-수리보증이 종료된 이후의 예방보전모형)

  • Jung, Ki-Mun
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.4
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    • pp.775-784
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    • 2011
  • In this paper, we consider the periodic preventive maintenance model for repairable system following the expiration of non-renewing free replacement-repair warranty (NFRRW). Under this preventive maintenance model, we derive the expressions for the expected cycle length, the expected total cost and the expected cost rate per unit time. Also, we determine the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for Weibull distribution case.

Optimal Reliability Strategy for k-out-of-n System Considering Redundancy and Maintenance (중복설계 및 예방정비를 고려한 수리가능 k-out-of-n 시스템 신뢰도 최적화 전략)

  • Lee, Youn-Ho;Jung, Kwang-Kyun;Yoon, Tae-Dong;Kwon, Ki-Sang
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.1
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    • pp.118-127
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    • 2014
  • The configuration such as series, parallel and k-out-of-n of a repairable system directly affects its reliability. The maintenance strategy can also affect the overall performance of the system. The objective of this work is to investigate the possible trade-off between the configuration of a repairable k-out-of-n system and its maintenance strategy. The redundancy is considered to be the design decision variables, whereas the preventive maintenance period is considered to be the maintenance decision variables. The optimization model is used to minimize the overall life cycle cost associated with the system, considering constraint on reliability. Finally, genetic algorithm is used to find the optimal values for the decision variables. The result is compared with optimal values for considering redundancy and maintenance respectively.

Preventive Maintenance Model after Minimal Repair Warranty (최소수리보증 이후의 예방보전모형)

  • Jung, Ki-Mun
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.865-877
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    • 2010
  • This paper considers the periodic preventive maintenance model for a repairable system following warranty expiration. We consider three types of warranty policies: free repair warranty, pro-rata repair warranty, and combination repair warranty. Under these preventive maintenance models, we derive the expressions for the expected cycle length, the total expected cost, and the expected cost rate per unit time. In addition, we explain the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for a Weibull distribution case.

Machine Maintenance Policy Using Partially Observable Markov Decision Process

  • Pak, Pyoung Ki;Kim, Dong Won;Jeong, Byung Ho
    • Journal of Korean Society for Quality Management
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    • v.16 no.2
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    • pp.1-9
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    • 1988
  • This paper considers a machine maintenance problem. The machine's condition is partially known by observing the machine's output products. This problem is formulated as an infinite horizon partially observable Markov decison process to find an optimal maintenance policy. However, even though the optimal policy of the model exists, finding the optimal policy is very time consuming. Thus, the intends of this study is to find ${\varepsilon}-optimal$ stationary policy minimizing the expected discounted total cost of the system, ${\varepsilon}-optimal$ policy is found by using a modified version of the well-known policy iteration algorithm. A numerical example is also shown.

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Numerical Experiments for the Stress-Reducing Preventive Maintenance Model (수치실험을 통한 스트레스 감소 예방보수모형의 고찰)

  • Park, Jong Hun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.3
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    • pp.41-52
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    • 2020
  • This paper investigates the stress-reducing preventive maintenance model through numerical experiments. The preventive maintenance model is used to analyze the relationship between related conditions and variables to gain insight into the efficient operation of the system when performing preventive maintenance in real-world situations. Various preventive maintenance models have been developed over the past decades and their complexity has increased in recent years. Increasing complexity is essential to reflect reality, but recent models can only be interpreted through numerical experiments. The stress-reducing preventive maintenance is a newly introduced preventive maintenance concept and can only be interpreted numerically due to its complexity, and has received little attention because the concept is unfamiliar. Therefore, for information purposes, this paper investigates the characteristics of the stress-reducing preventive maintenance and the relationship between parameters and variables through numerical experiments. In particular, this paper is focusing on the economic feasibility of stress-reducing preventive maintenance by observing changes in the optimal preventive maintenance period in response to changes in environmental stress and the improvement factor. As a result, when either the environmental stress or the improve effect of stress-reducing preventive maintenance is low, it is not necessary to carry out the stress-reducing preventive maintenance at excessive cost. In addition, it was found that the age reduction model is more economical than the failure rate reduction model.