scholarly journals Optimal Age-Based Preventive Maintenance Policy for a System Subject to Cumulative Damage Degradation and Random Shocks

2021 ◽  
Vol 10 (8) ◽  
pp. 79-86
Author(s):  
W. A. Akpan ◽  
A. A. Okon ◽  
E. J. Awaka-Ama
Keyword(s):  
Preventive Maintenance ◽  
Cumulative Damage ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Shock Duration ◽  
Time Interval ◽  
Maintenance Policy ◽  
Accelerated Life ◽  
Random Shock ◽  
Random Shocks

This research investigates the problem of cumulative degradation and random shocks a system like a centrifugal pump may experience during normal and adverse operating conditions. An accelerated life testing method was employed to determine the degradation of the pump under cumulative damage degradation and random shocks conditions. An age- Based policy was used to determine the optimum time interval that will minimize the total expected cost of the system. The random shock increases the number of failures and hence reduces the reliability of the system. The total expected preventive maintenance cost obtained varies from N1700.00 (One thousand seven hundred naira) to N16,000.00 (sixteen thousand naira), depending on the shock and shock duration. The methodology presented is useful and thus recommended for use to study cumulative damage degradation and random shocks for similar systems.

Penentuan Interval Waktu Pemeliharaan Pencegahan pada Peralatan Sub-Unit RKC 3 di PTX Pabrik Tuban

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Fesa Putra Kristianto ◽  
Bobby O.P. Soepangkat
Keyword(s):  
Preventive Maintenance ◽  
Operating Time ◽  
Maintenance Cost ◽  
Time Interval ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Total Labor ◽  
Finish Mill ◽  
Unit Plant ◽  
Reliability And Availability

PT X Tuban Plant has four plants (unit), namely Tuban I, Tuban II, Tuban III and Tuban IV. Each unit plant has three sub units, i.e., Crusher Operations Sub-Unit, Raw Mill, Kiln and Coal Mill (RKC) Sub-Unit and Finish Mill Sub-Unit. RKC 3 Sub-Unit in Tuban III has the highest number of equipment downtime and production loss. Therefore, it was necessary to optimize the time interval of preventive maintenance ( ) and total labor force as part of the company maintenance policy, would also fulfill the required reliability and availability of RKC 3 Sub-Unit. There were two steps in determining Tp optimum. The first step was to obtain the best distribution of the time between failures (TBF) and time to repair (TTR). The next step was to iterate the operating time (Ti) and Tp to determine the minimum preventive maintenance cost rate, reliability and maintainability.This iteration was applied to sub-units of RKC 3 that possesses a series system. Tp at the lowest rate of maintenance costs was the optimum Tp. The optimum Tp for RKC 3 Sub-Unit is 3743,28 hour. The preventive maintenance cost rate for optimum Tp is Rp33.100/hour and the reliability and availability of sub unit are 96,7% and 99,86% respectively.Keywords: reliability, availability, preventive maintenance cost rate, and preventive maintenance

scholarly journals ON PREVENTIVE MAINTENANCE POLICY FOR WAVE DISSIPATING BLOCKS COVERING CAISSON BREAKWATER

2018 ◽  
pp. 72
Author(s):  
Takao Ota ◽  
Hiroyuki Kawamura ◽  
Yoshiharu Matsumi ◽  
Junji Koyanagi ◽  
Takashi Satow
Keyword(s):  
Mathematical Model ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Reliability Engineering ◽  
Coastal Structures ◽  
Service Period ◽  
Caisson Breakwater ◽  
External Forces ◽  
Preventive Maintenance Policy

The infrastructures are required to keep a certain level of performance during the duration of service. Because the performance of the infrastructures including harbor and coastal structures deteriorates due to aging and damage that is caused by the action of external forces, it is necessary to perform appropriate maintenance. Satow et al. (2009) proposed a mathematical model for the preventive maintenance of wave dissipating blocks based on the method of the reliability engineering. They also derived the expected maintenance cost over the in service period and the optimal preventive maintenance policy. In this study, the optimal threshold for preventive maintenance to minimize the expected maintenance cost is determined for the wave dissipating blocks covering caisson breakwater by using the above model.

Optimal Preventive Maintenance Policy Under a Budget Constraint

2008 ◽  
Author(s):  
Inderjeet Singh ◽  
Elmira Popova ◽  
Ernie Kee
Keyword(s):  
Preventive Maintenance ◽  
Real Data ◽  
Integer Program ◽  
South Texas ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Data Set ◽  
Finite Time Horizon ◽  
Preventive Maintenance Policy ◽  
Operating Company

We design an optimal preventive maintenance policy for a system of N items that minimizes the total expected maintenance cost. We assume that the budget for preventive maintenance is limited and constrained. The problem has a finite time horizon and we consider constant inter-preventive maintenance times for every item. The resulting nonlinear optimization problem is reformulated as a binary integer program and computation results are presented on a real data set from South Texas Project Nuclear Operating Company in Bay City, Texas, USA.

scholarly journals Optimizing preventive maintenance policy: A data-driven application for a light rail braking system

2017 ◽  
Vol 231 (5) ◽  
pp. 534-545 ◽  
Author(s):  
Francesco Corman ◽  
Sander Kraijema ◽  
Milinko Godjevac ◽  
Gabriel Lodewijks
Keyword(s):  
Preventive Maintenance ◽  
Data Driven ◽  
Sequential Optimization ◽  
Maintenance Cost ◽  
Light Rail ◽  
Maintenance Policy ◽  
Maintenance Costs ◽  
Braking System ◽  
Optimal Maintenance Policy ◽  
Preventive Maintenance Policy

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

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 Integration of maintenance systems

2018 ◽  
Vol 211 ◽  
pp. 03010
Author(s):  
S H Sarje
Keyword(s):  
Preventive Maintenance ◽  
Hazard Rate ◽  
Reduction Factor ◽  
Maintenance Cost ◽  
Cost Ratio ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Maintenance System ◽  
Reliability Centered Maintenance ◽  
High Flexibility

Excellence in maintenance is imperative in highly competitive market because it resulted into minimum maintenance cost, high equipment effectiveness, maximum reliability of the system, high quality of the products, low delivery time, high flexibility, safety etc. Any maintenance system such as Total Productive Maintenance (TPM) or Reliability Centered Maintenance (RCM) or Condition Based Maintenance (CBM) alone cannot achieve the excellence in maintenance but its integration may do. In this paper, an integration of TPM, RCM and CBM is proposed with a maintenance policy to take advantage of their respective strengths. A continuously monitored system subject to degradation due to the imperfect maintenance, where a hybrid hazard rate based on the concept of age reduction factor and hazard rate increase factor to predict the evolution of the system reliability in different maintenance cycles has been assumed.A quantitative decision making model for an integrated maintenance system is derived in order to assess the performance of the proposed maintenance policy. Numerical examples of calculation of optimal preventive maintenance age x and preventive maintenance number N* for the given cost ratio of corrective replacement and predictive preventive maintenance are given.

scholarly journals DYNAMIC ANALYSIS OF A MULTIVARIATE REWARD PROCESS DEFINED ON THE UMCP WITH APPLICATION TO OPTIMAL PREVENTIVE MAINTENANCE POLICY PROBLEMS IN MANUFACTURING

2013 ◽  
Vol 27 (2) ◽  
pp. 187-208
Author(s):  
Jia-Ping Huang ◽  
Ushio Sumita
Keyword(s):  
Preventive Maintenance ◽  
Manufacturing System ◽  
Counting Process ◽  
Time Interval ◽  
Counting Processes ◽  
Maintenance Policy ◽  
Reward Process ◽  
Probabilistic Flow ◽  
Policy Problems ◽  
Preventive Maintenance Policy

The unified multivariate counting process (UMCP), previously studied by the same authors, enables one to describe most of the existing counting processes in terms of its components, thereby providing a comprehensive view for such processes often defined separately and differently. The purpose of this paper is to study a multivariate reward process defined on the UMCP. By examining the probabilistic flow in its state space, various transform results are obtained. The asymptotic behavior, as t→∞, of the expected univariate reward process in a form of a product of components of the multivariate reward process is studied. As an application, a manufacturing system is considered, where the cumulative profit given a preventive maintenance policy is described as a univariate reward process defined on the UMCP. The optimal preventive maintenance policy is derived numerically by maximizing the cumulative profit over the time interval [0, T].

scholarly journals Reliability assessment for systems suffering competing degradation and random shocks under fuzzy environment

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041988108
Author(s):  
Hongping Yu ◽  
Mao Tang
Keyword(s):  
Fuzzy Numbers ◽  
Epistemic Uncertainty ◽  
Operating Time ◽  
Reliability Assessment ◽  
Cumulative Damage ◽  
Fuzzy Environment ◽  
Random Shock ◽  
Comparative Results ◽  
Random Shocks ◽  
Internal Degradation

Reliability assessment of multi-component systems under competing degradation and random shocks has been intensively investigated in recent years. In most cases, the parameters associated with competing degradation and random shocks are represented by crisp values. However, due to insufficient data and vague judgments from experts, it may produce epistemic uncertainty with those parameters and they are befitting to be described as fuzzy numbers. In this article, the internal degradation is treated as a continuous monotonically increasing random process with respect to operating time, whereas the amount of cumulative damage produced by each external random shock is modeled by a geometric process. As components in a system suffer the same environmental condition, an external random shock will produce different amounts of cumulative damage to each component simultaneously. Each component fails when either the internal degradation or cumulative damage from the random shocks, whichever comes first, exceeds its corresponding random thresholds. Moreover, the parameters associated with the internal degradation and the random shocks are represented by triangular fuzzy numbers. The fuzzy reliability functions of components and the entire system are evaluated by a set of optimization models. A multi-component system, together with some comparative results, is presented to illustrate the implementation of the proposed method.

scholarly journals An Optimal Preventive Maintenance Policy for a Solar Photovoltaic System

2020 ◽  
Vol 12 (10) ◽  
pp. 4266 ◽  
Author(s):  
Amir Baklouti ◽  
Lahcen Mifdal ◽  
Sofiene Dellagi ◽  
Anis Chelbi
Keyword(s):  
Preventive Maintenance ◽  
Operating Time ◽  
Optimal Number ◽  
Photovoltaic System ◽  
Maintenance Cost ◽  
Solar Photovoltaic ◽  
Solar Panels ◽  
Maintenance Policy ◽  
Electrical Wiring ◽  
Solar Photovoltaic System

In this paper, we develop a preventive maintenance (PM) strategy for a solar photovoltaic system composed of solar panels functioning as a series system. The photovoltaic system is considered in a failed state whenever its efficiency drops below a predefined threshold or any electrical wiring element is damaged. In such a situation of failure, a minimal repair is performed. The proposed PM strategy suggests systematically replacing n panels with their respective wiring system every time units T over a finite operating time span H. The panels to be preventively replaced are selected by the maintenance agent after an on-site overall assessment of all panels, making sure every time not to replace panels previously replaced during a given replacement cycle of all panels of the system. An analytical model is proposed in order to simultaneously determine the optimal PM period, T, and the optimal number of solar panels, n, to be replaced at each PM. This is done by modeling and minimizing the expected total maintenance cost over the finite operating time horizon H. A numerical example is presented to illustrate the use of the proposed modelling approach and to discuss the obtained results. The latter provide the optimal solutions (T*, n*) for different combinations of input parameters. They also show the economic relevance of the proposed PM strategy through estimation of the economic gain when comparing the situations with and without preventive maintenance.

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