scholarly journals Condition-based Maintenance Optimization for Gamma Deteriorating Systems under Performance-Based Contracting

2021 ◽  
Author(s):  
Xi Zhu ◽  
Liang Wen ◽  
Juan Li ◽  
Mingchang Song ◽  
Qiwei Hu
Keyword(s):  
Optimization Problems ◽  
Degradation Process ◽  
Condition Based Maintenance ◽  
Maintenance Cost ◽  
Particle Swarm Algorithm ◽  
Maintenance Optimization ◽  
Corrective Maintenance ◽  
Inspection Interval ◽  
Proposed Model ◽  
Deteriorating Systems

Abstract As a new form of support contract, performance-based contracting (PBC) has been extensively adopted in industry and manufacturing recent years. However, maintenance optimization problems under PBC have not received enough attention. In order to further expand the application of PBC in the field of maintenance optimization, we investigate the condition-based maintenance (CBM) optimization for gamma deteriorating systems under PBC. Considering the repairable single-component system subject to the gamma degradation process, this paper proposes a CBM optimization model with an objective of maximizing the profit and improving system performance at a lower cost under PBC. In the proposed CBM model, first inspection interval is considered to reduce the inspection frequency and the cost. Then, a particle swarm algorithm (PSO) and related solution procedure are presented in order to solve the multiple decision variables in our proposed model. Finally, a numerical example is provided to illustrate the applicability and effectiveness of our proposed model. Through comparing the proposed policy with the conventional one, the superiority of our proposed policy is proved, which can bring more profits to providers and improve performance. Sensitivity analysis is conducted to investigate the effect of corrective maintenance cost and time required for corrective maintenance to optimization policy. Comparative study is given to illustrate the necessity of distinguishing first inspection interval and repeat inspection interval.

scholarly journals Condition-based Maintenance Optimization for Gamma Deteriorating Systems under Performance-based Contracting

2021 ◽  
Author(s):  
Xi Zhu ◽  
Liang Wen ◽  
Juan Li ◽  
Mingchang Song ◽  
Qiwei Hu
Keyword(s):  
Optimization Problems ◽  
Low Cost ◽  
Condition Based Maintenance ◽  
Maintenance Cost ◽  
Particle Swarm Algorithm ◽  
Maintenance Optimization ◽  
Corrective Maintenance ◽  
Cost Rate ◽  
Inspection Interval ◽  
Deteriorating Systems

Abstract With the further development of service-oriented, performance-based contracting (PBC) has been widely adopted in industry and manufacturing. However, maintenance optimization problems under PBC have not received enough attention. To further extend the scope of PBC’s application in the field of maintenance optimization, we investigate the condition-based maintenance (CBM) optimization for gamma deteriorating systems under PBC. Considering the repairable single-component system subject to the gamma degradation process, this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC. In the proposed CBM model, the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate. Then, a particle swarm algorithm (PSO) and related solution procedure are presented to solve the multiple decision variables in our proposed model. In the end, a numerical example is provided so as to demonstrate the superiority of the presented model. By comparing the proposed policy with the conventional ones, the superiority of our proposed policy is proved, which can bring more profits to providers and improve performance. Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy. A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.

scholarly journals Effective time interval for railway track geometry inspection

2020 ◽  
Vol 53 (1) ◽  
pp. 53-65 ◽  
Author(s):  
Ahmad Kasraei ◽  
Jabbar Ali Zakeri
Keyword(s):  
Decision Making ◽  
Railway Track ◽  
Sensitivity Analyses ◽  
Maintenance Cost ◽  
Time Interval ◽  
Maintenance Policy ◽  
Corrective Maintenance ◽  
Track Geometry ◽  
Inspection Interval ◽  
Geometry Inspection

A proper decision-making scheme for track geometry maintenance requires a knowledge of the real condition of track geometry. Therefore, the track must be inspected by measurement cars at different time intervals. The frequency of track geometry inspection plays a crucial role in decision-making and has always been a big concern for infrastructure managers. The inspection interval should be chosen properly, it means that the small period can decrease the capacity of line and affect the operation of network and the big period can result in low quality of track and in some cases derailments and possible loss of human lives. The aim of this paper is to determine the effective inspection interval such that the total maintenance cost is minimized. In the proposed cost model, the costs of inspection, preventive maintenance, corrective maintenance and the penalty for exceeding the corrective maintenance level are considered. A case study is performed on a real dataset collected from a railway line in Iran. The standard deviation of longitudinal level is considered to measure track geometry degradation. A widely applied linear model is used to model track geometry degradation over time. Monte Carlo technique is used to simulate the track geometry behavior under various track geometry inspection intervals. In addition, a set of sensitivity analyses are carried out to assess the effect of various inspection intervals on different terms of maintenance cost. The results indicate that not only can substantial costs be saved by setting effective inspection intervals, but also the time during which the track suffers from bad conditions is dramatically reduced. The result of this study has shown the appropriate inspection interval for the studied case can result in 13.6 percent decrease in maintenance cost in comparison with the current maintenance policy. Besides, it would lead to more reliable railway track by preventing the system exceed the corrective threshold.

scholarly journals A condition-based maintenance model with past-dependent imperfect preventive repairs for continuously deteriorating systems

2019 ◽  
Vol 234 (2) ◽  
pp. 333-358 ◽  
Author(s):  
Khac Tuan Huynh ◽  
Antoine Grall
Keyword(s):  
Special Kind ◽  
Condition Based Maintenance ◽  
Maintenance Cost ◽  
Engineering Practice ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Cost Rate ◽  
The One ◽  
Maintenance Model ◽  
Deteriorating Systems

Most condition-based imperfect maintenance models developed over the last few decades are memoryless in the sense that maintenance efficiency is completely [Formula: see text]-independent of previous interventions. However, many maintenance activities exhibit their past dependency in engineering practice, and this significant property should not be ignored in maintenance modeling. In this spirit, our aim is to develop a condition-based maintenance model for continuously deteriorating systems subject to a special kind of past-dependent imperfect repairs. Such a repair can put the system back to a deterioration level better than the one at just before the current repair, but worse than the one reached at the last repair. Besides, inspection and replacement are memoryless actions available for the system. They result in different effects on the system deterioration and incur different costs. To achieve high economic performances in the long term, these actions are coordinated into a control-limit deterioration-based maintenance policy. Its long-run maintenance cost rate is analytically evaluated using the semi-regenerative process theory. Numerous sensitivity studies to maintenance costs and to system characteristics give a thorough understanding about the policy behavior. Furthermore, comparisons with more classical policies justify the importance of incorporating the past dependency in maintenance modeling.

scholarly journals Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Ágota Bányai ◽  
Tamás Bányai ◽  
Béla Illés
Keyword(s):  
Black Hole ◽  
Supply Chain ◽  
Optimization Problems ◽  
Optimization Method ◽  
Chain Model ◽  
Supply Chain Optimization ◽  
Proposed Model ◽  
Supply Chain Model ◽  
Supply Model ◽  
Black Hole Algorithm

The globalization of economy and market led to increased networking in the field of manufacturing and services. These manufacturing and service processes including supply chain became more and more complex. The supply chain includes in many cases consignment stores. The design and operation of these complex supply chain processes can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on metaheuristic algorithms. This research proposes an integrated supply model based on consignment stores. After a careful literature review, this paper introduces a mathematical model to formulate the problem of consignment-store-based supply chain optimization. The integrated model includes facility location and assignment problems to be solved. Next, an enhanced black hole algorithm dealing with multiobjective supply chain model is presented. The sensitivity analysis of the heuristic black hole optimization method is also described to check the efficiency of new operators to increase the convergence of the algorithm. Numerical results with different datasets demonstrate how the proposed model supports the efficiency, flexibility, and reliability of the consignment-store-based supply chain.

scholarly journals Filling machine preventive maintenance using age replacement method in PT Lucas Djaja

2018 ◽  
Vol 154 ◽  
pp. 01056
Author(s):  
Fifi Herni Mustofa ◽  
Ria Ferdian Utomo ◽  
Kusmaningrum Soemadi
Keyword(s):  
Maintenance Cost ◽  
Time To Failure ◽  
High Failure Rate ◽  
Corrective Maintenance ◽  
Replacement Method ◽  
Critical Components ◽  
Age Replacement ◽  
Engine Maintenance ◽  
A Company ◽  
Mean Time

PT Lucas Djaja is a company engaged in the pharmaceutical industry which produce sterile drugs and non-sterile. Filling machine has a high failure rate and expensive corrective maintenance cost. PT Lucas Djaja has a policy to perform engine maintenance by way of corrective maintenance. The study focused on the critical components, namely bearing R2, bearing 625 and bearing 626. When the replacement of the failure done by the company is currently using the formula mean time to failure with the result of bearing R2 at point 165 days, bearing 625 at a point 205 days, and bearing 626 at a point 182 days. Solutions generated by using age replacement method with minimization of total maintenance cost given on the bearing R2 at a point 60 days, bearing 625 at the point of 80 days and bearing 626 at a point 40 days.

scholarly journals Bivariate Nonlinear Diffusion Degradation Process Modeling via Copula and MCMC

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Huibing Hao ◽  
Chun Su
Keyword(s):  
Nonlinear Diffusion ◽  
Goodness Of Fit ◽  
Real Data ◽  
Degradation Process ◽  
Copula Function ◽  
Assessment Method ◽  
Unknown Parameters ◽  
Degradation Data ◽  
Proposed Model ◽  
Frank Copula

A novel reliability assessment method for degradation product with two dependent performance characteristics (PCs) is proposed, which is different from existing work that only utilized one dimensional degradation data. In this model, the dependence of two PCs is described by the Frank copula function, and each PC is governed by a random effected nonlinear diffusion process where random effects capture the unit to unit differences. Considering that the model is so complicated and analytically intractable, Markov Chain Monte Carlo (MCMC) method is used to estimate the unknown parameters. A numerical example about LED lamp is given to demonstrate the usefulness and validity of the proposed model and method. Numerical results show that the random effected nonlinear diffusion model is very useful by checking the goodness of fit of the real data, and ignoring the dependence between PCs may result in different reliability conclusion.

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.

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