• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.17 no.30
• /
• pp.73-79
• /
• 1994

This paper propose Adaptive Maintenance as a new type of maintenance for machine failures which are unpredictable. A purpose of adpative maintenance is to decrease inconsistency. In order to pick up some of problems the traditional maintenance policy, We discussed Time Based Maintenance(TBM) and Condition Based Maintenance(CBM) with Bath-Tub Curve. By using Machine Condition Diagnosis Technique (CDT), Monitored condition maintenance deals with the dynamic decision making for diagnosis procedures at maintenance and caution level. Adaptive Maintenance is a powerful tool for Total Production Maintenance(TPM).

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.11a
• /
• pp.618-629
• /
• 2006

This Paper is about optimizing preventive maintenance period of connected (r,s) out of(m,n) : F lattice system that one of multi-component system, (m,n) matrix failure of whole system is occurrence when parts that belong in (r,s) matrix part procession of parts arranged with procession are breakdown all. The preventive maintenance about system is very important viewing from system reliability and operational expense viewpoint. Preventive maintenance that misses a time calls big loss by system failure and expense of frequent full equipment is paid excessively in preventive maintenance itself but expense is paid much in preventive maintenance itself and whole expense escalation can be achieved preferably. Through this research, reliability model is constructed that do expense by smallest under full equipment policy chosen through comparison of each full equipment policy and preventive maintenance expense full equipment cycle and r ,s value are made using simulated annealing algorithm and simulated annealing algorithm that converge fast in multi-component system certified most suitable to optimization decision

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.3
• /
• pp.689-696
• /
• 2007

This paper considers a Bayesian approach to determine an optimal PM policy with random maintenance quality. Thus, we assume that the quality of a PM action is a random variable following a probability distribution. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal PM policy. Finally, the numerical examples are presented for illustrative purpose.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.6
• /
• pp.1557-1564
• /
• 2016

Recently, an extended warranty of a system following the expiration of the basic warranty is becoming increasingly popular to the user. In this respect, we suggest a two stage maintenance policy under the non-renewing warranty from the user's point of view in this paper. In the first stage, the user has to decide whether or not to purchase the extended warranty period. And, in the second stage, the optimal replacement period following the expiration of the warranty is determined. Under the extended warranty, the failed system is minimally repaired by the manufacturer at no cost to the user. We utilize the expected cost from the user's perspective to determine the optimal two stage maintenance policy. Finally, a few numerical examples are given for illustrative purpose.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.17 no.32
• /
• pp.233-242
• /
• 1994

This study deals with the derivative adverse minimum for inferiority system depends on continuose operating under infinite planning horizon. This planning will be accomplished by maintenance limit renewal policy in consideration of opportunity cost which affects system by failure during operation periods and expected cost under nomal operation states. By the results, we will be expected incresing total efficiency for the system by optimal renewal policy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.2
• /
• pp.81-86
• /
• 2014

In this paper, a jointly optimal group replacement and spare provisioning policy is presented. Most maintenance policies assume that the spare inventory is always available, but in practice the maintenance schedule is affected by the availability of spare inventory. We present a maintenance-inventory model which jointly optimizes the group replacement interval and spare ordering quantity. Group replacement policy is used when a group of units are put in operation simultaneously. The operating fleet is replaced altogether at a predetermined number of units are failed. A sufficient level of spare inventory is carried to perform a number of group replacement. A cost rate expression which considers the group maintenance cost and inventory holding cost is derived and a heuristic method for searching the optimum value of decision variables is suggested. Numerical examples demonstrate the analytical results and the performance of the presented model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.2
• /
• pp.632-637
• /
• 2014

In this paper the concept of the performance-based logistics (PBL) support for weapon systems is discussed and an enhancement is studied such that prior to the Operational phase, the development of the PBL can begin from the Engineering & Manufacturing Development (EMD) phase together with multiple performance indices considered. The genetic algorithm should be considered for the complex system to solve the maintenance policy optimization. In particular, the requirement of repair level analysis model is developed based on reflecting the PBL concept. To decide the maintenance policy prior to Operational phase in accordance with customer requirements, the PIDO(Process Integration and Design Optimization) technique useful in choosing the performance indices and changing the constraints was used. The genetic algorithm of PIDO tool, like PIAnO and ModelCenter, was verified that it could be applied to optimize the maintenance policy.

• Journal of Korean Society for Quality Management
• /
• v.49 no.3
• /
• pp.299-312
• /
• 2021

Purpose: We provide a condition-based maintenance policy where a surrogate variable is used for monitoring system performance. We constructed a risk function by taking into account the risk and losses accompanied with erroneous decisions. Methods: Assuming a unique degradation process for the performance variable and its specific relationship with the surrogate variable, the maintenance policy is determined. A risk function is developed on the basis of producer's and consumer's risks accompanied with each decision. With a strategic safety factor considered, the optimal threshold value for the surrogate variable is determined based on the risk function. Results: The condition-based maintenance is analyzed from the point of risk. With an assumed safety consideration, the optimal threshold value of the surrogate variable is provided for taking a maintenance action. The optimal solution cannot be obtained in a closed form. An illustrative numerical example and solution is provided with a source code of R program. Conclusion: The study can be applied to situation where a sensor signal is issued if the system performance begins to degrade gradually and reaches eventually its functional failure. The study can be extended to the case where two or more performance variables are connected to a same surrogate variable. Also estimation of the distribution parameters and risk coefficients should be further studied.

• Proceedings of the Korean Reliability Society Conference
• /
• 2000.11a
• /
• pp.335-342
• /
• 2000

Preventive maintenance(PM) is an action taken on a repairable system while it is still operating, which needs to be carried out in order to keep the system at the desired level of successful operation. The PM improves the reliability of the system by predicting the possible failures and thereby preventing such failures from its occurrence. In this paper, we develop the optimal preventive maintenance policies based on the aperiodic PM model. We investigate an aperiodic preventive maintenance policy and propose several optimal PM policies which minimize the expected cost over an infinite time span. Park, Jung and Yum(2000) determine the optimal period and the optimal number of PMs based on Canfield's(1986) periodic model. Our techniques to derive the optimal preventive maintenance policies based on our aperiodic PM model is similar to those in Park, Jung and Yum(2000), which can be considered as the special case of our results.