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Article
Publication date: 4 September 2017

Miguel Angel Navas, Carlos Sancho and Jose Carpio

The purpose of this paper is to present the results of the application of various models to estimate the reliability in railway repairable systems.

Abstract

Purpose

The purpose of this paper is to present the results of the application of various models to estimate the reliability in railway repairable systems.

Design/methodology/approach

The methodology proposed by the International Electrotechnical Commission (IEC), using homogeneous Poisson process (HPP) and non-homogeneous Poisson process (NHPP) models, is adopted. Additionally, renewal process (RP) models, not covered by the IEC, are used, with a complementary analysis to characterize the failure intensity thereby obtained.

Findings

The findings show the impact of the recurrent failures in the times between failures (TBF) for rejection of the HPP and NHPP models. For systems not exhibiting a trend, RP models are presented, with TBF described by three-parameter lognormal or generalized logistic distributions, together with a methodology for generating clusters.

Research limitations/implications

For those systems that do not exhibit a trend, TBF is assumed to be independent and identically distributed (i.i.d.), and therefore, RP models of “perfect repair” have to be used.

Practical implications

Maintenance managers must refocus their efforts to study the reliability of individual repairable systems and their recurrent failures, instead of collections, in order to customize maintenance to the needs of each system.

Originality/value

The stochastic process models were applied for the first time to electric traction systems in 23 trains and to 40 escalators with ten years of operating data in a railway company. A practical application of the IEC models is presented for the first time.

Details

International Journal of Quality & Reliability Management, vol. 34 no. 8
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 June 2007

Yong Sun, Lin Ma and Joseph Mathew

The purpose of this article is to present a new split system model (SSM) that predicts the reliability of complex systems with multiple preventive maintenance (PM) actions in the…

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Abstract

Purpose

The purpose of this article is to present a new split system model (SSM) that predicts the reliability of complex systems with multiple preventive maintenance (PM) actions in the long term.

Design/methodology/approach

The SSM was developed using probability theory based on the concept of separating repaired and unrepaired components within a system virtually when modelling the reliability of the system after repairs. After theoretical analysis, a case study and Monte Carlo simulation were used to evaluate the effectiveness of the newly developed model.

Findings

The model can be used to determine the remaining life of systems, to show the changes in reliability with PM actions, and to quantify PM intervals after imperfect repairs.

Practical implications

SSM can be used to predict the reliability of complex systems with multiple PM actions, and hence can be used to support asset PM decision making over the whole life of the asset, such as scheduled PM times and spare parts requirements. An asset often has some vulnerable components, i.e. where the lives of these components are much shorter than the rest of the asset. In this case, PM is often conducted on these vulnerable components for maximising the useful life of the asset. The specific formulae derived in this paper can be used to predict the reliability of the asset for this scenario.

Originality/value

The proposed model uses a new concept of split systems to predict the changes of reliability of complex systems with multiple PM actions. Asset managers will find this model to be a useful tool in the optimisation of their asset PM strategies.

Details

Journal of Quality in Maintenance Engineering, vol. 13 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 8 July 2019

Abdul Kareem Lado and V.V. Singh

The purpose of this paper is to covenant with the cost assessment of a complex repairable system, consisting of two subsystems (Subsystem 1 and Subsystem 2) connected in series…

Abstract

Purpose

The purpose of this paper is to covenant with the cost assessment of a complex repairable system, consisting of two subsystems (Subsystem 1 and Subsystem 2) connected in series configuration and being operated by a human operator. Each subsystem has two identical units in parallel configuration and has different types of failure and two types of repairs (general repair and copula repair). Through the transition diagram, the system of first-order partial differential equations is derived and solved using a supplementary variable technique, Laplace transforms. All failures are assumed to follow exponential distribution, whereas repairs follow two types of distributions that are general and Gumbel–Hougaard family copula. In this paper, explicit expressions for reliability, availability, mean time to failure (MTTF) and cost analysis functions have been obtained. In this paper, two types of repairs (copula repair and general repair) have been studied, and it has been concluded that copula repair is more reliable as compared to general repair. Some computations are taken as particular case by evaluating: reliability, availability, MTTF and cost analysis, so as to capture the effect of both failure and repair rates to reliability measures. The results have been shown in tables and graphs. The convincing part has been discussed in last section of this study.

Design/methodology/approach

This paper is focused on the cost assessment of a system consisting two subsystem series configuration. Each subsystem has two identical units in parallel configuration. The performance of the system has been analyzed by supplementary variable techniques and Laplace transforms. Various measures of the reliability have been discussed by evaluations. Software called Maple 13 is used for computations.

Findings

In this research paper, the authors have evaluated the operational cost and incurred profit of the system together with other reliability measures for various situations and different types of failures and two types of repairs using Gumbel–Hougaard family copula distribution.

Research limitations/implications

The present research focuses on the series and parallel configured complex systems that is used everywhere in industry and other sectors. The authors main aim is to claim that repair through the joint probability distribution copula is far better than general repair. Copula repair for a completely failed system is more beneficial for industrial system operations that will increase profit to the industrial sector.

Practical implications

The authors have observed that when repair follows general distribution the values of reliability obtained of the system are less compared to the those obtained when the authors apply copula repair, a joint probability distribution. It is a clear implication for industrial sector and organization to use the policy for a better generate revenue.

Social implications

According to the best of authors’ knowledge, there is no social implication as this study is meant for reliability section. The study in management and case study matters is considered to have social implication.

Originality/value

This research is the original work of authors. Nothing has been copied from any paper or book. The references are cited according to the relevance of study.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 10
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 August 2019

Amit Kumar, Vinod Kumar and Vikas Modgil

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm…

Abstract

Purpose

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability.

Design/methodology/approach

In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance.

Findings

In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently.

Research limitations/implications

There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone.

Originality/value

The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 26 July 2021

Garima Sharma and Rajiv Nandan Rai

Degradation of repairable components may not be similar after each maintenance activity; thus, the classic (traditional-time based) maintenance policies, which consider preventive…

Abstract

Purpose

Degradation 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/approach

A 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.

Findings

A 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/value

The 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.

Article
Publication date: 30 March 2010

Komal, S.P. Sharma and Dinesh Kumar

The puprose of this paper is to analyse the stochastic behavior of an industrial system using a novel hybridized technique NGABLT. The forming unit of a paper mill situated in…

Abstract

Purpose

The puprose of this paper is to analyse the stochastic behavior of an industrial system using a novel hybridized technique NGABLT. The forming unit of a paper mill situated in north India producing approximately 200 tons of paper per day has been considered for analysis. The authors have made efforts to incorporate vague, ambiguous, imprecise and conflicting information quantified by fuzzy numbers.

Design/methodology/approach

Field data for repairable industrial systems are in the form of failures and repair rates are vague, ambiguous, qualitative and imprecise in nature. Using the data, system stochastic behavior in terms of six well‐known reliability indices is analysed considering some desired degree of accuracy. A practical case of forming unit in a paper mill is considered to compute the reliability indices by using NGABLT technique. Sensitive of system behavior is analysed through surface plots by taking different combinations of reliability indices. The findings have been supplied to the nearby industry for future course of action in maintenance.

Findings

The behavior analysis results computed by NGABLT technique have reduced region of prediction in comparison of existing Lambda‐Tau technique region i.e. uncertainties involved in the analysis are reduced. It may be a more useful tool to assess the current system condition and to improve the system performance.

Originality/value

The authors have suggested a hybridized technique for analyzing the stochastic behavior of the repairable industrial system by computing its reliability indices.

Details

Journal of Quality in Maintenance Engineering, vol. 16 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 21 August 2009

Komal, S.P. Sharma and Dinesh Kumar

The purpose of this paper is to present a hybridized technique for analyzing the behavior of an industrial system stochastically utilizing vague, imprecise, and uncertain data…

Abstract

Purpose

The purpose of this paper is to present a hybridized technique for analyzing the behavior of an industrial system stochastically utilizing vague, imprecise, and uncertain data. The press unit of a paper mill situated in a northern part of India, producing 200 tons of paper per day, has been considered to demonstrate the proposed approach. Sensitivity analysis of system's behavior has also been done.

Design/methodology/approach

In the proposed approach, two important tools namely traditional Lambda‐Tau technique and genetic algorithm have been hybridized to build genetic algorithms‐based Lambda‐Tau (GABLT) technique to analyze the behavior of complex repairable industrial systems stochastically up to a desired degree of accuracy. This technique has been demonstrated by computing six well‐known reliability indices used for behavior analysis of the considered system in more promising way.

Findings

The behavior analysis results computed by GABLT technique have reduced region of prediction in comparison of existing Lambda‐Tau technique region, i.e. uncertainties involved in the analysis are reduced. Thus, it may be a more useful analysis tool to assess the current system conditions and involved uncertainties. The paper suggested an approach to improve the system's performance.

Originality/value

The paper suggests a hybridized technique for analyzing the stochastic behavior of an industrial subsystem by computing six well‐known reliability indices in the form of fuzzy membership function.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 2 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 29 November 2018

Hamed Fazlollahtabar and Seyed Taghi Akhavan Niaki

The purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of…

Abstract

Purpose

The purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of the availability of standby autonomous robots for reducing and preventing down-times of advanced production systems, which imposes a considerable loss, the present research tries to introduce a practical model for the determination of the required number of autonomous robots.

Design/methodology/approach

Most of the available research on the estimation of the required standby components based on the reliability characteristics of components has not considered the environmental factors influencing the reliability characteristics. Therefore, such estimations are not accurate enough. In contrast, this paper focuses on the influence of the environmental and human factors (e.g. the operators’ skill) on the robot reliability characteristics.

Findings

A model based on the Weibull renewal process combined with the cold standby strategy is developed for reliability evaluation of the system. The effectiveness of the proposed integrated reliability evaluation model is worked out in some cases.

Originality/value

Determining a required number of robots is an important issue in availability and utilization of a complex robotic production system. In an advanced production system, while the estimation process of a required number of robots can be performed through different approaches, one of the realistic estimation methods is based on the system’s reliability that takes into consideration the system operating environment. To forecast the required number of robots for an existing production system, in some cases, the assumption of a constant failure rate does not differ much from the assumption of a non-constant failure rate and can be made with an acceptable error.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 10
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 January 2022

Abbas Bin Jibril, V.V. Singh and Dilip Kumar Rawal

The purpose of this paper is to deliberate the system reliability of a system in combination of three subsystems in a series configuration in which all three subsystems function…

Abstract

Purpose

The purpose of this paper is to deliberate the system reliability of a system in combination of three subsystems in a series configuration in which all three subsystems function under a k-out-of-n: G operational scheme. Based on computed results, it has been demonstrated that copula repair is better than general repair for system better performance. The supplementary variable approach with implications of copula distribution has been employed for assessing the system performance.

Design/methodology/approach

Probabilistic assessment of complex system consisting three subsystems, multi-failure threats and copula repair approach is used in this study. Abbas Jubrin Bin, V.V. Singh, D.K. Rawal, in this research paper, have analyzed a system consisting of three subsystems in a series configuration in which all three subsystems function under a k-out-of-n: G operational scheme. The supplementary variable approach with implications of copula distribution has been employed for assessing the system performance. Based on computed results, it has been demonstrated that copula repair is better than general repair for system better performance.

Findings

In this analysis, four different cases of availability are analysed for Gumbel–Hougaard family copula and also four cases for general repair with similar failure rates are studied. The authors found that when failure rates increase, the system availability decreases, and when the system follows copula repair distribution, the system availability is better than general repair.

Research limitations/implications

This research may be implemented in various industrial systems where the subsystems are configured under k-out-of-n: G working policy. It is also advisable that copula repair is highly recommended for best performances from the system. On the basis of mean time to system failure (MTSF) computations, the failure rate which affects system failure more needs to be controlled by monitoring, servicing and replacing stratagem.

Practical implications

This research work has great implications in various industrial systems like power plant systems, nuclear power plant, electricity distributions system, etc. where the k-out-of-n-type of system operation scheme is validated for system operations with the multi-repair.

Originality/value

This work is a new work by authors. In the previously available technical analysis of the system, the researchers have analyzed the repairable system either supplementary variable approach, supplementary variable and system which have two subsystems in a series configuration. This research work analyzed a system with three subsystems with a multi-repair approach and supplementary variables.

Details

International Journal of Quality & Reliability Management, vol. 40 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 19 September 2019

Afshin Yaghoubi, Seyed Taghi Akhavan Niaki and Hadi Rostamzadeh

The purpose of this paper is to derive a closed-form expression for the steady-state availability of a cold standby repairable k-out-of-n system. This makes the availability…

Abstract

Purpose

The purpose of this paper is to derive a closed-form expression for the steady-state availability of a cold standby repairable k-out-of-n system. This makes the availability calculation much easier and accurate.

Design/methodology/approach

Assuming exponential distributions for system failure and repair, the Markov method is employed to derive the formula.

Findings

The proposed formula establishes an easier and faster venue and provides accurate steady-state availability.

Research limitations/implications

The formula is valid for the case when the probability density function of the component failure and the repair is exponential.

Originality/value

The Markov method has never been used in the literature to derive the steady-state availability of a cold standby repairable k-out-of-n: G system.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

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