Progressive maintenance policy for multiple repairable systems with imperfect maintenance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Garima Sharma ◽  
Rajiv Nandan Rai
Keyword(s):  
Power Plants ◽  
Maintenance Cost ◽  
Mean Residual Life ◽  
Time Interval ◽  
Imperfect Maintenance ◽  
Repairable Systems ◽  
Maintenance Policy ◽  
Data Set ◽  
Content Type ◽  
Maintenance Policies

PurposeDegradation of repairable components may not be similar after each maintenance activity; thus, the classic (traditional-time based) maintenance policies, which consider preventive maintenance (PM), age-based maintenance and overhauls to be done at fixed time interval, may fail to monitor the exact condition of the component. Thus, a progressive maintenance policy (PMP) may be more appropriate for the industries that deal with large, complex and critical repairable systems (RS) such as aerospace industries, nuclear power plants, etc.Design/methodology/approachA progressive maintenance policy is developed, in which hard life, PM scheduled time and overhaul period of the system are revised after each service activity by adjusting PM interval and mean residual life (MRL) such that the risk of failure is not increased.FindingsA comparative study is then carried out between the classic PM policy and developed PMP, and the improvement in availability, mean time between failures and reduction in maintenance cost is registered.Originality/valueThe proposed PMP takes care of the equipment degradation more efficiently than any other existing maintenance policies and is also flexible in its application as the policy can be continuously amended as per the failure profile of the equipment. Similar maintenance policies assuming lifetime distributions are available in the literature, but to ascertain that the proposed PMP is more suitable and applicable to the industries, this paper uses Kijima-based imperfect maintenance models. The proposed PMP is demonstrated through a real-time data set example.

Availability analysis and maintenance optimization for multiple failure mode systems considering imperfect repair

2021 ◽  
pp. 1748006X2110127
Author(s):  
Qingan Qiu ◽  
Baoliang Liu ◽  
Cong Lin ◽  
Jingjing Wang
Keyword(s):  
Failure Modes ◽  
Maintenance Cost ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Availability Analysis ◽  
Long Run ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Periodic Inspections

This paper studies the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The repair time distribution and maintenance cost are both dependent on the failure modes. We investigate the instantaneous availability and the steady state availability of the system maintained through several imperfect repairs before a replacement is allowed. Analytical expressions for system availability under continuous and periodic inspections are derived respectively. The availability models are then utilized to obtain the optimal inspection and imperfect maintenance policy that minimizes the average long-run cost rate. A numerical example for Remote Power Feeding System is presented to demonstrate the application of the developed approach.

Imperfect maintenance model for estimating aircraft fleet availability

2017 ◽  
Vol 89 (2) ◽  
pp. 338-346 ◽  
Author(s):  
Aleksandar Knezevic ◽  
Ljubisa Vasov ◽  
Slavisa Vlacic ◽  
Cedomir Kostic
Keyword(s):  
Intermediate Level ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Content Type ◽  
Reliability Parameters ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Optimal Maintenance Policy ◽  
Maintenance Model

Purpose The purpose of this paper is to define conditions under which improved availability of fleet of G-4 jet trainers is obtained, and optimization of intermediate-level maintenance through imperfect maintenance model application. This research has been conducted based on available knowledge, and experience gained by performing intermediate-level maintenance of Serbian Air Force aircrafts. Design/methodology/approach Analysis of the data collected from daily maintenance reports, and the analysis of maintenance technology and organization, was performed. Based on research results, a reliability study was performed. Implementation of imperfect maintenance with its models of maintenance policies (especially a quasi-renewal process and its treating of reliability and optimal maintenance) was proposed to define new maintenance parameters so that the greater level of availability could be achieved. Findings The proposed methodology can potentially be applied as a simple tool to estimate the present maintenance parameters and to quickly point out some deficiencies in the analyzed maintenance organization. Validation of this process was done by conducting a reliability case study of G-4 jet trainer fleet, and numerical computations of optimal maintenance policy. Research limitations/implications The methodology of the availability estimation when reliability parameters were not tracked by the maintenance organization, and optimization of intermediate-level maintenance, has so far been applied on G-4 jet trainers. Moreover, it can be potentially applied to other aircraft types. Originality/value Availability estimation and proposed optimization of intermediate maintenance is based on a survey of data for three years of aircraft fleet maintenance. It enables greater operational readiness (due to a military rationale) with possible cost reduction as a consequence but not as a goal.

scholarly journals Age Based Overhaul Policy for Multiple Repairable Systems with Imperfect Maintenance: Case Study of Aero Engines

2020 ◽  
Vol 6 (1) ◽  
pp. 193-206
Author(s):  
Garima Sharma ◽  
Rajiv Nandan Rai
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Spare Parts ◽  
Imperfect Maintenance ◽  
Repairable Systems ◽  
Maintenance Policy ◽  
Estimation Model ◽  
Failure Data ◽  
Area Of Interest ◽  
Aero Engines

Reliability analysis of complex multiple repairable systems (MRS) such as aero engines, rolling stocks and nuclear power plants has always been an area of interest for the research fraternity. An appropriate age based overhaul maintenance policy for such systems can provide impetus to the operations. The paper proposes two different age based maintenance policies; Policy-I and Policy-II, to evaluate the overhaul time of an aero engine, where Policy-I considers MRS with imperfect corrective maintenance (CM), whereas Policy-II examines MRS with both imperfect CM and preventive maintenance (PM). The paper then provides a spare parts estimation model for both the policies. The developed policies and spares parts model are validated by considering field failure data of aero engines as a case and the obtained results are compared with the existing time based maintenance policy used for aero engines. The paper recommends the best policy to be used for MRS in general and the considered case in particular.

An improved imperfect maintenance strategy for multiperiod randomly failing equipment with stochastic repair times

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sofiene Dellagi ◽  
Mohamed Noomane Darghouth
Keyword(s):  
Failure Rate ◽  
Planning Horizon ◽  
Maintenance Cost ◽  
Equipment Failure ◽  
Maintenance Strategy ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Content Type ◽  
Proposed Model ◽  
The Impact

PurposeIn this paper, a maintenance strategy based on improved imperfect maintenance actions with stochastic repair times for multiperiod randomly failing equipment is developed. The main objective is to minimize the total maintenance cost by jointly finding the optimal preventive maintenance (PM) cycle and planning horizon.Design/methodology/approachA model based on the mathematical theory of reliability is developed to minimize the total maintenance cost by jointly finding the optimal couple: PM cycle T* and planning horizon H*. The proposed model aims to characterize the evolutionary impact of imperfect PM actions on the equipment failure rate and the resulting mean number of failures. The conventional threshold accepting (TA) algorithm is implemented to solve the proposed model. A numerical example for a given set of input parameters is presented in order to show the usefulness of the proposed model. A sensitivity analysis of some of the key parameters is performed to demonstrate the coherence of the developed maintenance policy.FindingsThe obtained results showed a sensitive trade-off between PM frequency and the total maintenance cost. Performing PM actions more frequently helps significantly to reduce the expected number of corrective maintenance actions and the corresponding total cost. It has also been found that improving the efficiency of the PM actions allows for maintaining the equipment less frequently by increasing the time between successive PM actions.Research limitations/implicationsGiven the complexity of the objective function to be minimized and the stochastic nature of the model's parameters, the authors limited this study to equally cyclic production periods over the planning horizon.Practical implicationsThe present model aims to provide an integrated maintenance/production comprehensive framework to assist planners in establishing maintenance schedules considering multiperiod randomly failing production systems and the evolutionary impact of imperfect PM actions on the equipment failure rate.Originality/valueContrary to the majority of existing works in the literature dealing with maintenance strategies, the authors consider that repair times are stochastic to provide a more realistic framework. In addition, the developed model considers the impact of imperfect maintenance on the equipment's mean time to failure. Thus, the evolutionary impact of imperfect PM actions on the equipment failure rate and the resulting mean number of failures is characterized. Simultaneously, the production planning horizon along with the length of each PM cycle is optimized in order to minimize the total maintenance cost over the planning horizon.

scholarly journals Integrating Modelling of Maintenance Policies within a Stochastic Hybrid Automaton Framework of Dynamic Reliability

2021 ◽  
Vol 11 (5) ◽  
pp. 2300
Author(s):  
Simone Arena ◽  
Irene Roda ◽  
Ferdinando Chiacchio
Keyword(s):  
Model Systems ◽  
Mitigation Measures ◽  
Repairable Systems ◽  
Maintenance Policy ◽  
Hybrid Automaton ◽  
Dynamic Reliability ◽  
Software Model ◽  
Maintenance Policies ◽  
Mathematical Techniques ◽  
Continuous And Discrete Variables

The dependability assessment is a crucial activity for determining the availability, safety and maintainability of a system and establishing the best mitigation measures to prevent serious flaws and process interruptions. One of the most promising methodologies for the analysis of complex systems is Dynamic Reliability (also known as DPRA) with models that define explicitly the interactions between components and variables. Among the mathematical techniques of DPRA, Stochastic Hybrid Automaton (SHA) has been used to model systems characterized by continuous and discrete variables. Recently, a DPRA-oriented SHA modelling formalism, known as Stochastic Hybrid Fault Tree Automaton (SHyFTA), has been formalized together with a software library (SHyFTOO) that simplifies the resolution of complex models. At the state of the art, SHyFTOO allows analyzing the dependability of multistate repairable systems characterized by a reactive maintenance policy. Exploiting the flexibility of SHyFTA, this paper aims to extend the tools’ functionalities to other well-known maintenance policies. To achieve this goal, the main features of the preventive, risk-based and condition-based maintenance policies will be analyzed and used to design a software model to integrate into the SHyFTOO. Finally, a case study to test and compare the results of the different maintenance policies will be illustrated.

On preventive maintenance policies: a selection framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imad Alsyouf ◽  
Sadeque Hamdan ◽  
Mohammad Shamsuzzaman ◽  
Salah Haridy ◽  
Iyad Alawaysheh
Keyword(s):  
Preventive Maintenance ◽  
Fuzzy Ahp ◽  
Critical Component ◽  
Multi Objective Optimization ◽  
Maintenance Policy ◽  
Coolant Pump ◽  
Content Type ◽  
Multi Objective ◽  
Maintenance Policies ◽  
Preventive Maintenance Policy

PurposeThis paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.Design/methodology/approachThe critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.FindingsFor a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.Research limitations/implicationsOnly three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.Practical implicationsThe proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.Originality/valueThis research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.

The effect of fiscal transparency on government spending efficiency

2019 ◽  
Vol 46 (7) ◽  
pp. 1365-1379 ◽  
Author(s):  
Elina De Simone ◽  
Mariangela Bonasia ◽  
Giuseppe Lucio Gaeta ◽  
Lorenzo Cicatiello
Keyword(s):  
Government Spending ◽  
Financial Management ◽  
Institutional Environment ◽  
Public Spending ◽  
Time Interval ◽  
Data Set ◽  
Content Type ◽  
Fiscal Transparency ◽  
Positive Effects ◽  
Positive Effect

Purpose Making citizens able to monitor and evaluate public spending activities is a fundamental issue in public financial management literature. The purpose of this paper is to analyze whether fiscal transparency, measured by the Open Budget Index, has an effect on public spending performance, measured by the World Economic Forum’s Global Competitiveness Report data. Design/methodology/approach Research methods rely on random-effects panel regression models on a country-level panel data set of 82 world countries observed in the 2008–2015 time interval. Findings Results show that the potential positive effects of fiscal transparency are mediated by the level of democracy of the country. In detail, in democratic countries, a higher degree of disclosure of fiscal information is correlated with a higher efficiency of government spending while, in non-democratic countries, fiscal transparency does not seem to provide any effect. Social implications The results suggest that fiscal transparency can be a powerful device where politicians can be held accountable for their actions, while it could fail to provide positive results where a strong and effective vertical accountability is missing. Originality/value The novelty of the paper is twofold. First, it provides new additional evidence about the positive effect that fiscal transparency has on public spending efficiency by advancing previous research on this topic (Porumbescu, 2017; Montes et al., 2019). Second, the paper investigates conceptually and empirically how the positive effect on public spending efficiency determined by fiscal transparency depends on the degree of democracy present in the institutional environment in which fiscal information disclosure is implemented.

Coloured stochastic Petri nets modelling for the reliability and maintenance analysis of multi-state multi-unit systems

2014 ◽  
Vol 25 (4) ◽  
pp. 476-490 ◽  
Author(s):  
Zhouhang Wang ◽  
Maen Atli ◽  
H. Kondo Adjallah
Keyword(s):  
Petri Nets ◽  
Complex Structure ◽  
Real Life ◽  
Simulation Models ◽  
Decision Makers ◽  
Stochastic Petri Nets ◽  
Repairable Systems ◽  
Content Type ◽  
Markov Graphs ◽  
Maintenance Policies

Purpose – The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs. Design/methodology/approach – The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size. Findings – Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system. Research limitations/implications – The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered. Practical implications – The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies. Originality/value – The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.

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 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.

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