An operating environment-based preventive maintenance decision model

2019 ◽  
Vol 26 (4) ◽  
pp. 592-610
Author(s):  
Aiping Jiang ◽  
Qingxia Li ◽  
Jinyi Yan ◽  
Leqing Huang ◽  
Haining Wu
Keyword(s):  
Reliability Analysis ◽  
Preventive Maintenance ◽  
Decision Model ◽  
Maintenance Cost ◽  
Redundant System ◽  
Content Type ◽  
Multiple Components ◽  
Safety And Reliability ◽  
Optimal Maintenance ◽  
The Cost

Purpose The purpose of this paper is to focus on finding the optimal maintenance interval and the minimum maintenance cost for redundant system, considering environment factors. Design/methodology/approach The authors propose a decision model with environment-based preventive maintenance for the repairable redundant system. Referring to the k-out-of-n model and Proportional Hazard Model, the reliability analysis is completed for the redundant system affected by internal and external issues. Meanwhile, the maintenance cost for the redundant system is divided into two categories: the fixed maintenance cost involving whole system replacement at the time of system failure, and the cost to replace failure components when the system still functions. Findings Upon the required reliability analysis, an optimal maintenance interval that minimizes the average maintenance cost per unit time is identified. The simulation results indicate that the optimal maintenance interval with consideration of environmental factors is significantly shorter than that without consideration of these factors, with the maintenance cost increase within 10 percent. Practical implications The redundant systems have widely been used in industries including the aero craft control system and warship power system. The model could be applied in the more real case considering the types of components and the operation environment, and help production managers better maintain machines by increasing the safety and reliability of the redundant model with the more frequent inspection. Originality/value Previous research of redundant system always focuses on internal degradation, while ignoring the reliability analysis for a redundant system with various multiple components under the influence of environment. However, this work could fill the theoretical gap, i.e. simultaneously consider both environmental and internal factors for a redundant system with non-homogeneous components. Meanwhile, the proposed superior model increases the reliability and safety of the k-out-of-n model with reasonable cost. Production managers could benefit a lot from this as well.

scholarly journals Preventive maintenance of multiple components for hydraulic tension systems

2021 ◽  
Vol 23 (3) ◽  
pp. 489-497
Author(s):  
Hongyan Dui ◽  
Xiaoqian Zheng ◽  
Qian Qian Zhao ◽  
Yining Fang
Keyword(s):  
Working Conditions ◽  
Preventive Maintenance ◽  
Conveyor Belt ◽  
Tension Force ◽  
Maintenance Cost ◽  
Number Of Components ◽  
Multiple Components ◽  
Conveyor Belts ◽  
The Cost

Automatically controlled hydraulic tension systems adjust the tension force of a conveyor belt under different working conditions. Failures of an automatically controlled hydraulic tension system influence the performance of conveyor belts. At present, the maintenance of automatically controlled hydraulic tension systems mainly considers the replacement of components when failures occur. Considering the maintenance cost and downtime, it is impossible to repair all the failed components to improve the hydraulic tension system. One of the key problems is selecting the most valuable components for preventive maintenance. In this paper, preventive maintenance for multiple components in a hydraulic tension system is analyzed. An index is proposed to select more reliable preventive maintenance components to replace the original ones. A case study is given to demonstrate the proposed method. When the cost budget increases, there are three different variations in the number of components for selective preventive maintenance (SPM).

Reliability Analysis Using Deep Learning

2018 ◽  
Author(s):  
Chong Chen ◽  
Ying Liu ◽  
Xianfang Sun ◽  
Shixuan Wang ◽  
Carla Di Cairano-Gilfedder ◽  
...  
Keyword(s):  
Data Mining ◽  
Deep Learning ◽  
Reliability Analysis ◽  
General Principle ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Empirical Results ◽  
Time Between Failures ◽  
Learning Techniques ◽  
Deep Learning Model

Over the last few decades, reliability analysis has gained more and more attention as it can be beneficial in lowering the maintenance cost. Time between failures (TBF) is an essential topic in reliability analysis. If the TBF can be accurately predicted, preventive maintenance can be scheduled in advance in order to avoid critical failures. The purpose of this paper is to research the TBF using deep learning techniques. Deep learning, as a tool capable of capturing the highly complex and nonlinearly patterns, can be a useful tool for TBF prediction. The general principle of how to design deep learning model was introduced. By using a sizeable amount of automobile TBF dataset, we conduct an experiential study on TBF prediction by deep learning and several data mining approaches. The empirical results show the merits of deep learning in performance but comes with cost of high computational load.

Reliability/risk centered cost effective preventive maintenance planning of generating units

2018 ◽  
Vol 35 (9) ◽  
pp. 2052-2079 ◽  
Author(s):  
Umamaheswari E. ◽  
Ganesan S. ◽  
Abirami M. ◽  
Subramanian S.
Keyword(s):  
Preventive Maintenance ◽  
Optimization Technique ◽  
Solution Space ◽  
Fuzzy Decision Making ◽  
Content Type ◽  
Multi Objective ◽  
Statistical Measures ◽  
Highly Nonlinear ◽  
Optimal Maintenance ◽  
Maintenance Schedules

Purpose Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues. Design/methodology/approach The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS. Findings As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique. Originality/value As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.

Optimization of equal-cycle maintenance strategy considering imperfect preventive maintenance

2021 ◽  
pp. 095440892110638
Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Action Unit ◽  
Cost Rate ◽  
Equipment Reliability ◽  
Optimal Maintenance ◽  
Important Means ◽  
Maintenance Decision

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

scholarly journals Optimal maintenance scheduling for local public purpose buildings

2016 ◽  
Vol 34 (2) ◽  
pp. 120-135 ◽  
Author(s):  
Arnt O. Hopland ◽  
Sturla F. Kvamsdal
Keyword(s):  
Local Governments ◽  
Formal Model ◽  
Maintenance Scheduling ◽  
Trade Off ◽  
Content Type ◽  
Maintenance Schedule ◽  
Public Purpose ◽  
Trade Offs ◽  
Optimal Maintenance ◽  
The Cost

Purpose – The purpose of this paper is to set up and analyze a formal model for maintenance scheduling for local government purpose buildings. Design/methodology/approach – The authors formulate the maintenance scheduling decision as a dynamic optimization problem, subject to an accelerating decay. This approach offers a formal, yet intuitive, weighting of an important trade-off when deciding a maintenance schedule. Findings – The optimal maintenance schedule reflects a trade-off between the interest rate and the rate at which the decay accelerates. The prior reflects the alternative cost, since the money spent on maintenance could be saved and earn interests, while the latter reflects the cost of postponing maintenance. Importantly, it turns out that it is sub-optimal to have a cyclical maintenance schedule where the building is allowed to decay and then be intensively maintained before decaying again. Rather, local governments should focus the maintenance either early in the building’s life-span and eventually let it decay toward replacement/abandonment or first let it decay to a target level and then keep it there until replacement/abandonment. Which of the two is optimal depends on the trade-off between the alternative cost and the cost of postponing maintenance. Originality/value – The paper provides a first formal inquiry into important trade-offs that are important for maintenance scheduling of local public purpose buildings.

An integrated space-based building maintenance management model using multi-objective optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huthaifa AL-Smadi ◽  
Abobakr Al-Sakkaf ◽  
Tarek Zayed ◽  
Fuzhan Nasiri
Keyword(s):  
Residential Buildings ◽  
Maintenance Cost ◽  
Content Type ◽  
Fund Allocation ◽  
Building Maintenance ◽  
Window System ◽  
Optimal Maintenance ◽  
Building Condition ◽  
Maintenance Model

PurposeThe purpose of this study is to minimize cost and minimize building condition. Weibull distribution approach was employed to generate deterioration curves over time. The third floor of Concordia University’s Engineering And Visual Arts (EV) Complex in Montreal, Canada, served as a case study to test the maintenance model and determine the optimal maintenance activities to be performed.Design/methodology/approachThis research has demonstrated that there is insufficient fund allocation for the maintenance of non-residential buildings. Therefore, this research focused on designing and developing a maintenance optimization model that provides the type of spaces (architectural system) in a building. Sensitivity analysis was used to calculate weights to validate the model. Particle swarm optimization, based explicitly on multiple objectives, was applied for the optimization problem using MATLAB.FindingsFollowing 100 iterations, 13 non-dominant solutions were generated. Not only was the overall maintenance cost minimized, but the condition of the building was also maximized. Moreover, the condition prediction model demonstrated that the window system type has the most rapid deterioration in educational buildings.Originality/valueThe model is flexible and can be modified by facility managers to align with the required codes or standards.

Optimization of reliability and maintenance of liquefaction system on FLNG terminals using Markov modelling

2014 ◽  
Vol 31 (3) ◽  
pp. 293-310 ◽  
Author(s):  
Samer Gowid ◽  
Roger Dixon ◽  
Saud Ghani
Keyword(s):  
Maintenance Cost ◽  
Production Plant ◽  
Markov Modeling ◽  
Markov Modelling ◽  
Reliability Modeling ◽  
Content Type ◽  
Liquefaction Process ◽  
The Cost ◽  
First Time ◽  
Liquefaction Plant

Purpose – The purpose of this paper is to optimize system redundancy and maintenance intervals of a propane pre-cooled mixed refrigerant (C3MR) liquefaction process on floating liquefied natural gas (FLNG) export platforms. Design/methodology/approach – The reliability modeling is based on the time-dependent Markov approach. Four different system options are studied, with various degree of redundancy. Failures in the liquefaction system usually lead to shutdown the whole LNG production plant. The associated shutdown cost is compared with the cost of introducing redundancy and the cost of onboard maintenance. To ensure a high profitability, a model for maintenance optimization is utilized and applied to the main unit of the C3MR liquefaction system to minimize the onboard maintenance cost. Findings – The results indicated that the introduction of a second liquefaction system (as a standby unit) is the best option for liquefaction plant in terms of reliability and cost. This will substantially reduce the unavailability from 14.7 to 2.19 percent of the total operational hours. Based on the presented system configuration, the annual system profit will increase by 180 million USD if the redundancy is implemented on FLNG export ships. The optimum maintenance intervals of major process components are also calculated to minimize the total cost of maintenance. Originality/value – The originality of this paper lies within the context in investigating the reliability of the C3MR liquefaction system on LNG floating export terminals using Markov modeling for the first time.

Reliability analysis of CNC turning center based on the assessment of trends in maintenance data

2017 ◽  
Vol 34 (9) ◽  
pp. 1616-1638 ◽  
Author(s):  
Rajkumar Bhimgonda Patil ◽  
Basavraj S. Kothavale ◽  
Laxman Yadu Waghmode ◽  
Shridhar G. Joshi
Keyword(s):  
Reliability Analysis ◽  
Goodness Of Fit ◽  
Numerical Control ◽  
Maintenance Cost ◽  
Repairable Systems ◽  
Content Type ◽  
Cnc Turning ◽  
Warranty Period ◽  
Turning Center ◽  
Support Cost

Purpose The paper presents reliability, maintainability and life cycle cost (LCC) analysis of a computerized numerical control (CNC) turning center which is manufactured and used in India. The purpose of this paper is to identify the critical components/subsystems from reliability and LCC perspective. The paper further aims at improving reliability and LCC by implementing reliability-improvement methods. Design/methodology/approach This paper uses a methodology for the reliability analysis based on the assessment of trends in maintenance data. The data required for reliability and LCC analysis are collected from the manufacturers and users of CNC turning center over a period of eight years. ReliaSoft’s Weibull++9 software has been used for verifying goodness of fit and estimating parameters of the distribution. The LCC of the system is estimated for five cost elements: acquisition cost, operation cost, failure cost, support cost and net salvage value. Findings The analysis shows that the spindle bearing, spindle belt, spindle drawbar, insert, tool holder, drive battery, hydraulic hose, lubricant hose, coolant hose and solenoid valve are the components with low reliability. With certain design changes and implementation of reliability-based maintenance policies, system reliability is improved, especially during warranty period. The reliability of the CNC turning center is improved by nearly 45 percent at the end of warranty period and system mean time between failure is increased from 15,000 to 17,000 hours. The LCC analysis reveals that the maintenance cost, operating cost and support costs dominate the LCC and contribute to the tune of 87 percent of the total LCC. Research limitations/implications The proposed methodology provides an excellent tool that can be utilized in industries, where safety, reliability, maintainability and availability of the system play a vital role. The approach may be improved by collecting data from more number of users of the CNC turning centers. Practical implications The approach presented in this paper is generic and can be applied to analyze the repairable systems. A real case study is presented to show the applicability of the approach. Originality/value The proposed methodology provides a practical approach for the analysis of time-to-failure and time-to-repair data based on the assessment of trends in the maintenance data. The methodology helps in selecting a proper approach of the analysis such as Bayesian method, parametric methods and nonparametric methods.

scholarly journals Optimal Maintenance Thresholds to Perform Preventive Actions by Using Multi-Objective Evolutionary Algorithms

2019 ◽  
Vol 9 (15) ◽  
pp. 3068 ◽  
Author(s):  
Aitor Goti ◽  
Aitor Oyarbide-Zubillaga ◽  
Elisabete Alberdi ◽  
Ana Sanchez ◽  
Pablo Garcia-Bringas
Keyword(s):  
Preventive Maintenance ◽  
Manufacturing Industry ◽  
Industrial Revolution ◽  
Preventive Intervention ◽  
Cost Benefit ◽  
Economic Consequences ◽  
Maintenance Cost ◽  
Optimization Approach ◽  
Multi Objective ◽  
Optimal Maintenance

Maintenance has always been a key activity in the manufacturing industry because of its economic consequences. Nowadays, its importance is increasing thanks to the “Industry 4.0” or “fourth industrial revolution”. There are more and more complex systems to maintain, and maintenance management must gain efficiency and effectiveness in order to keep all these devices in proper conditions. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, even though often these programs are complex to manage and understand. For this reason, several research papers propose approaches that are as simple as possible and can be understood by users and modified by experts. In this context, this paper focuses on CBM optimization in an industrial environment, with the objective of determining the optimal values of preventive intervention limits for equipment under corrective and preventive maintenance cost criteria. In this work, a cost-benefit mathematical model is developed. It considers the evolution in quality and production speed, along with condition based, corrective and preventive maintenance. The cost-benefit optimization is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case.

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