Optimum Maintenance Strategy of a Repairable System Under Long-Term Free Preventive Maintenance Warranty with Predicted Maintenance

2016 ◽  
Vol 23 (04) ◽  
pp. 1650016 ◽  
Author(s):  
Gwo-Liang Liao
Keyword(s):  
Preventive Maintenance ◽  
Repairable System ◽  
System Failure ◽  
Maintenance Strategy ◽  
Imperfect Maintenance ◽  
Maintenance Time ◽  
Special Cases ◽  
Periodic Maintenance ◽  
Time Periodic

In this paper, the optimum user’s maintenance strategy of a repairable system for free preventive maintenance (PM) warranty policy is proposed. This study considers predicted maintenance due to the system failure is likely occurring and requires repair during periodic maintenance time. Periodic maintenance can be classified as one of three types — imperfect PM, perfect PM and predicted maintenance. The probability that periodic maintenance is perfect PM or predicted maintenance depends on the number of imperfect maintenance operations conducted since the previous renewal cycle. The sellers offer free perfect and imperfect PM warranty. An optimal periodic maintenance time is determined by minimizing the total cost. Some special cases, implemented with machine learning and human learning, are given to demonstrate the feasibility of the proposed strategy. A numerical example is given.

scholarly journals A Hybrid Simulation Study to Determine an Optimal Maintenance Strategy

2020 ◽  
Vol 19 (2) ◽  
pp. 91
Author(s):  
Ig. Jaka Mulyana ◽  
Ivan Gunawan ◽  
Yunia Vera Angelia ◽  
Dian Trihastuti
Keyword(s):  
Simulation Study ◽  
Preventive Maintenance ◽  
Hybrid Simulation ◽  
Process Industry ◽  
Maintenance Cost ◽  
Time Interval ◽  
Maintenance Strategy ◽  
System Perspective ◽  
Maintenance Time ◽  
Reliability Indicator

With the increasing complexity of the process industry, having excellent maintenance management is essential for manufacturing industries. Various parts that interact and interdependent with each other make a well-planned maintenance strategy is one of the major challenges facing by industry. The whole system could be interrupted just simply because of the failure of a component.  Therefore, a review of a maintenance strategy must be done from a system perspective. It is suggested that the optimal preventive maintenance time interval is not only determined by the lowest maintenance cost of each machine but also its impact on the whole system. Two main indicators that can accommodate the system perspective are reliability and revenue. A large number of machines and the array of machines can be synthesized in the reliability indicator. Moreover,  the creation of maximum revenue is always the main goal for a business. The best maintenance strategy will be determined from the revenue obtained by a process industry. The process industry discussed in this study is a flour mill which is very well known in Surabaya. This study applied a hybrid simulation to solve this problem. Monte Carlo simulation was used to observe the machine individually and the results are reviewed using the application of System Dynamics. Three improvement scenarios were proposed in this simulation study. Scenario 2 was chosen as the best scenario because it was able to generate the highest revenue at the end of the period. Scenario 2 recommends setting the preventive maintenance time interval considering resource availability.

Optimal imperfect maintenance strategy for leased equipment

2016 ◽  
Vol 178 ◽  
pp. 57-64 ◽  
Author(s):  
A. Ben Mabrouk ◽  
A. Chelbi ◽  
M. Radhoui
Keyword(s):  
Maintenance Strategy ◽  
Imperfect Maintenance

Preventive maintenance optimization for repairable products considering two-dimensional warranty and customer satisfaction

2018 ◽  
Vol 233 (4) ◽  
pp. 553-566
Author(s):  
Yukun Wang ◽  
Yiliu Liu ◽  
Aibo Zhang
Keyword(s):  
Customer Satisfaction ◽  
Preventive Maintenance ◽  
Product Performance ◽  
Maintenance Optimization ◽  
Two Dimensional ◽  
Maintenance Strategy ◽  
Minimal Repair ◽  
Proposed Model ◽  
Useful Life ◽  
Practical Implications

Customer satisfaction with a purchased product is closely related to the product performance within the warranty region and even the performance during the remainder of its useful life. Every satisfied customer may boost the future sales of the same product with positive evaluations and recommendations to others, and thus will create more profits for the manufacturer. During the useful life of the product, the expected cost to the manufacturer normally depends on the warranty policy, product reliability and specific servicing strategies implemented. In this article, considering the effect of customer satisfaction on the manufacturer’s incurred cost, we investigate a periodic and imperfect preventive maintenance strategy for repairable products sold with a two-dimensional warranty policy. The customer satisfaction is measured with the probability of the customer making a repeat purchase from the same manufacturer. In the proposed model, the number of preventive maintenance actions and corresponding maintenance level are jointly derived with the objective of minimizing the expected total cost per product to the manufacturer. The performance of the proposed preventive maintenance strategy is compared with that of minimal repair corrective maintenance strategy in a numerical example, so as to illustrate its applicability. In addition, some practical implications from a detailed sensitivity analysis are elaborated.

scholarly journals Preventive Maintenance Strategy for Train Doors Based on the Competitive Weibull Theory

2020 ◽  
Author(s):  
deqiang he ◽  
Xiaozhen Zhang ◽  
Yanjun Chen ◽  
Jian Miao ◽  
Congbo Li ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Preventive Maintenance ◽  
Estimation Method ◽  
Weibull Model ◽  
Urban Rail Transit ◽  
Fuzzy Cluster ◽  
Rail Transit ◽  
Maintenance Strategy ◽  
Actual Situation ◽  
Urban Rail

Abstract In view of the problems of over-maintenance and under-maintenance in the current urban rail transit maintenance strategy and the reliability of single processing of fault data, which is often inconsistent with the actual situation, an incomplete preventive maintenance strategy based on the competitive Weibull model is proposed in this paper. To make the fault mechanism processing method for urban rail vehicles more accurate, fault feature attributes and fault information sequences are introduced to classify fault data. Fuzzy cluster analysis of vehicle fault data can be performed using the formula of the competitive Weibull model, and parameter estimation of the reliability model can be performed by combining it with the graph parameter estimation method. In addition, the fault rate increase factor and service age reduction factor are introduced into the maintenance strategy, and the optimal preventive maintenance cycle and maintenance times are obtained by combining maintenance and replacement according to reliability. A quantum-genetic intelligent algorithm is used to optimize the model-solving process. Finally, the maintenance of urban rail transit train doors is taken as an example. The results of this study show that compared with the traditional maintenance strategy, the reliability of the proposed maintenance strategy is closer to the actual situation. At the same time, the proposed maintenance strategy can effectively reduce the number of parked vehicles, reduce maintenance costs, and ensure the safety of train operation, maintenance economy and performance of tasks.

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