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Article
Publication date: 9 March 2015

Mohamed Khalifa, Faisal Khan and Joseph Thorp

– The purpose of this paper is to propose a quantitative model for risk-based maintenance and remaining life assessment for gas turbines.

Abstract

Purpose

The purpose of this paper is to propose a quantitative model for risk-based maintenance and remaining life assessment for gas turbines.

Design/methodology/approach

The proposed model uses historical failure and repair data from the operation of gas turbines. The time to failure of gas turbines is modeled using Weibull distribution.

Findings

The total risk is estimated considering replacement cost, repair cost, operation cost, risk of failure and turbine remaining value after a specified period of time.

Originality/value

The model is an effective tool to make optimal decisions regarding maintenance strategy (repair or replacement) and to assess the remaining life based on a comparison of the total risk. The literature review focusses on developing different models to make risk-based decisions regarding the selection of a maintenance strategy and maintenance interval, however, literature is silent regarding risk-based assessment of the equipment remaining life, which is the focus of present work. The model is tested and applied to ageing gas turbines in a cross-country pipeline.

Details

Journal of Quality in Maintenance Engineering, vol. 21 no. 1
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 4 February 2021

Erkki K. Laitinen

The purpose of this study is to analyze the business-failure-process risk from two perspectives. First, a simplified model of the loss-generation process in a failing firm…

Abstract

Purpose

The purpose of this study is to analyze the business-failure-process risk from two perspectives. First, a simplified model of the loss-generation process in a failing firm is developed to show that the linear system embedded in accounting makes financial ratios to depend linearly on each other. Second, a simplified model of the development of the risk during the failure process is developed to introduce a new concept of failure-process-risk line (FPRL) to assess the systematic failure risk of a firm. Empirical evidence from Finnish firms is used to test two hypotheses.

Design/methodology/approach

This study makes use of simple mathematical modeling to depict the loss-generation process and the development of failure risk during the failure process. Hypotheses are extracted from the mathematical results for empirical testing. Time-series data originally from 13,082 non-failing and 515 failing Finnish are used to test the hypotheses. Analysis of variance F statistics and Mann–Whitney U test are used in testing of the hypotheses.

Findings

The findings show that the linear time-series correlations are generally higher in failing than in non-failing firms because of the loss-generation process. The FPRL depicted efficiently the systematic failure-process risk through the beta coefficient. Beta coefficient efficiently discriminated between failing and non-failing firms. The difference between the last-period risk estimate and FPRL was largely determined by the approximated growth rate of the periodic failure risk.

Research limitations/implications

The loss-generation process is based on a simple cash-based approach ignoring the growth of the firm. In future research, the model could be generalized to a growing firm in an accrual-based framework. The failure-process risk is assumed to grow at a constant rate. In further studies, more general models could be applied. Empirical analyses are based on simple statistical methods and tests. More advanced methods could be used to analyze the data.

Practical implications

This study shows that failure process makes the time-series correlation between financial ratios to increase making their signals of failure consistent and allowing the use of static classification models to assess failure risk. The beta coefficient is a useful tool to reflect systematic failure-process risk. In addition, it can be used in practice to warn a firm about ongoing failure process.

Originality/value

To the best of the author’s knowledge, this is the first study analyzing systematically business-failure-process risk. It is first in introducing a mathematical loss-generation process and the FPRL based on the beta coefficient assessing the systematic failure risk.

Details

Journal of Financial Reporting and Accounting, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-2517

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Article
Publication date: 26 February 2021

Indraneel Das, Dilbagh Panchal and Mohit Tyagi

This paper aims to presents a novel integrated fuzzy decision support system for analyzing the issues related to failure of a milk process plant unit.

Abstract

Purpose

This paper aims to presents a novel integrated fuzzy decision support system for analyzing the issues related to failure of a milk process plant unit.

Design/methodology/approach

Process failure mode effect analysis (PFMEA) approach was implemented to list failure causes under each subsystem/component and fuzzy ratings for three risk criteria, i.e. probability of failure occurrence (O_f), severity (S) and non-detection (O_d) are collected against the listed failure causes through experts feedback. A new doubly technique for order of preference by similarity to ideal solution (DTOPSIS) approach was implemented within fuzzy PFMEA tool for ranking of listed failure causes. The proposed decision support system overcomes the restrictions of classical PFMEA and IF-THEN rule base PFMEA approaches in an effective way.

Findings

Failure causes such as electrical winding failure (RM4), high pressure in plate region (C1), communication problem in supervisory control and data acquisition control (MS3), insulation problem (ST2), lever breakage (B2), gasket problem (D3), formation of holes (PHE5), cavitations (FP7), deposition of milk particle inside the pipeline because of improper cleaning (MHP2) were acknowledged as the most critical one with the application of proposed decision support system.

Research limitations/implications

The analysis results are based on subjective judgments of the experts and therefore correctness of risk ranking results are totally dependent upon the quality of input data/information available from these experts. However, the analyst has taken proper care for considering the vagueness of the raw data by incorporating fuzzy set theory within the proposed decision support system.

Practical implications

The proposed fuzzy decision support system has been presented with its application on milk pasteurization plant of a milk process industry. The analysis based ranking results have been supplied to maintenance manager of the plant and a consent was shown by him with these results. Once the top management of the plant took decision for the implementation of these results, the detailed robustness of the proposed decision support system could be evaluated further.

Social implications

The analysis result would be highly useful for minimizing sudden breakdowns and operational cost of the plant which directly contributes to plant's profitability. With the decrease in the chances of sudden breakdowns there would be high safety for the people working on/off the plant's site. Further, with increase in availability of the considered plant the societal daily demand related to dairy products could be easily fulfilled at reasonable prices.

Originality/value

The performance and proficiency of the proposed decision support system has been evaluated by comparing the ranking results with classical TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approaches based results.

Details

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

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Article
Publication date: 17 March 2021

Samaneh Zolfaghari and Seyed Meysam Mousavi

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the…

Abstract

Purpose

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the safety of patients, so they should be managed thoroughly. It is an intricate multi-attributes decision-making problem with uncertainty. Uncertain information in the form of fuzzy sets theory has been applied widely to describe the different aspects of system uncertainty. This study aims to present a new methodology to manage the healthcare system failures due to the multi-attributes decision-making process.

Design/methodology/approach

This study introduces a new risk evaluation methodology by failure mode and effect analysis (FMEA) and MULTIMOORA method. Group decision-making process in this methodology is presented under uncertain information in the form of interval-valued hesitant fuzzy linguistic sets (IVHFLSs). IVHFLSs encompass both qualitative and quantitative interpretation of experts to reflect their preferences, as well the ability and flexibility of derivation of linguistic information by several linguistic terms increase. To avoid the different ranking order of MULTIMOORA approaches, a new interval multi-approaches multi-attribute methodology, namely, technique of precise order preference (TPOP), is extended to provide precise ranking order.

Findings

The application and precision of proposed integrated IVHFL-MULTIMOORA methodology with TPOP is examined in a case study of healthcare systems. The results indicate the superiority of proposed methodology to prioritize and assess the failures as well as handling system uncertainty.

Originality/value

This study addresses the challenges of an organization to prioritize potential failures by implementing FMEA method. Moreover, this paper contributes to making the manager's ability in decision-making. The value of this study can be discussed in two aspects. First and foremost, this study provides a new FMEA-based methodology to rank failures precisely. The results prove that the proposed methodology is more robust to changes of different ranking order methods, applied by FMEA. On the other hand, using the capability of IVHFLSs allows collecting accurate information in an ambiguous and uncertain environment.

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Article
Publication date: 24 November 2020

Avinash Bagul and Indrajit Mukherjee

This paper attempts to address three key objectives. The primary aim is to enhance sourcing strategy for a centralized and coordinated multitier multiple suppliers…

Abstract

Purpose

This paper attempts to address three key objectives. The primary aim is to enhance sourcing strategy for a centralized and coordinated multitier multiple suppliers networks with uncertain demand and supplier failure risks. The second objective is to enumerate all possible practical supplier(s) failure scenarios and quantify expected loss of demand cost. Finally, the work illustrates statistical experimentation to identify “influential” variables that can significantly impact the expected supply network and loss costs.

Design/methodology/approach

A seven-step solution framework is proposed to derive an optimal sourcing strategy for the specific network configuration with varied supplier failure scenarios. Five distinct models are formulated to address all possible scenarios of supplier failure events. Mixed-integer nonlinear programming technique is used to derive expected supply network cost and loss cost. The solution framework is verified using a real-life case.

Findings

A cross-case analysis indicates that an increase in suppliers' failure risk (SFR) probabilities or customer demand rate increases the expected loss of demand costs for a multitier supply network. Besides, an increase in unit component prices increases the expected supply network cost.

Research limitations/implications

A two-tier automotive supply network for a single product is considered for all case studies.

Practical implications

The enhanced strategy can facilitate practitioners enumerate different supply network failure scenarios and implement the best solution.

Originality/value

There is no evidence of earlier research to derive optimal sourcing strategy for a centralized, coordinated multitier multiple supplier's network, considering demand uncertainties and SFR.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

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Article
Publication date: 10 August 2012

Jakiul Hassan, Faisal Khan and Mainul Hasan

Purpose – The purpose of this paper is to propose a risk‐based approach for spare parts demand forecast and spare parts inventory management for effective allocation of

Abstract

Purpose – The purpose of this paper is to propose a risk‐based approach for spare parts demand forecast and spare parts inventory management for effective allocation of limited resources. Design/methodology/approach – To meet the availability target and to reduce downtime, process facilities usually maintain inventory of spare parts. The maintaining of non‐optimized spare parts inventory claims more idle investment. Even if it is optimized, lack of attention towards the critical equipment spares could threaten the availability of the plant. This paper deals with the various facets of spare parts inventory management, mainly risk‐based spare parts criticality ranking, forecasting, and effective risk reduction through strategic procurement policy to ensure spare parts availability. A risk‐based approach is presented that helps managing spare parts requirement effectively considering the criticality of the components. It also helps ensuring the adequacy of spare parts inventory on the basis of equipment criticality and dormant failure without compromising the overall availability of the plant. Findings – The paper proposes a risk‐based approach that used conjugate distribution technique with the capability to incorporate historical failure rate as well as expert judgment to estimate the future spare demand through posterior demand distribution. The approach continuously updates the prior distribution with most recent observation to give posterior demand distribution. Hence the approach is unique in its kind. Practical implications – Appropriate spare parts unavailability could have great impact on process operation and result in costly downtime of the plant. Following proposed approach the availability target can be achieved in process industry having limited maintenance resources, by forecasting spare parts demand precisely and maintaining inventory in good condition. Originality/value – Adopting the approach proposed in the paper, risk level can be minimized and plant availability can be maximized within the financial constraint. The resources are allocated to the most critical components and thereby increased availability, and reduce risk.

Details

Journal of Quality in Maintenance Engineering, vol. 18 no. 3
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 11 January 2019

Fateme Dinmohammadi

Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces…

Abstract

Purpose

Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces the assets’ lifecycle cost, but also will ensure high standards of safety and comfort for rail passengers and workers. In recent years, the majority of studies have been focused on the application of risk-based tools and techniques to maintenance decision making of railway infrastructure assets (such as tracks, bridges, etc.). The purpose of this paper is to present a risk-based modeling approach for the inspection and maintenance optimization of railway rolling stock components.

Design/methodology/approach

All the “potential failure modes and root causes” related to rolling stock systems are identified from an extensive literature review followed by an expert’s panel assessment. The failure causes are categorized into six groups of electrical faults, structural damages, functional failures, degradation, human errors and natural (external) hazards. Stochastic models are then proposed to estimate the likelihood (probability) of occurrence of a failure in the rolling stock system. The consequences of failures are also modeled by an “inflated cost function” that involves safety-related costs, corrective maintenance and renewal (M&R) costs, the penalty charges due to train delays or service interruptions as well as the costs associated with loss of reputation (or loss of fares) in the case of trip cancellation. Lastly, a time-varying risk-cost function is formulated to determine the optimal frequency of preventive inspection and maintenance actions for rolling stock components.

Findings

For the purpose of clearly illustrating the proposed risk-based inspection and maintenance modeling methodology, a case study of the Class 380 train’s pantograph system from a Scottish train operating company is provided. The results indicate that the proposed model has a substantial potential to reduce the M&R costs while ensuring a higher level of safety and service quality compared to the currently used inspection methodologies.

Practical implications

The railway rolling stocks should be regularly inspected and maintained so as to ensure network availability and reliability, passenger safety and comfort, and operations efficiency. Despite the best efforts of the maintenance staff, it is reported that a considerable amount of maintenance resources (e.g. budget, time, manpower) is wasted due to insufficiency or inefficiency of current periodic M&R interventions. The model presented in this paper helps the maintenance engineers to assess the current maintenance practices and propose or initiate improvement actions when needed.

Originality/value

There are few studies investigating the application of risk-based tools and techniques to inspection and maintenance decision making of railway rolling stock components. This paper presents a modeling approach aimed at planning the preventive repair and maintenance interventions for rolling stock components based on risk measures. The author’s model is also capable of incorporating real measurement information gathered at each inspection epoch to update future inspection plans.

Details

Journal of Quality in Maintenance Engineering, vol. 25 no. 2
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 4 February 2019

Virgo Süsi and Oliver Lukason

The purpose of this study is to find out how corporate governance is interconnected with failure risk in case of small- and medium-sized enterprises (SMEs).

Abstract

Purpose

The purpose of this study is to find out how corporate governance is interconnected with failure risk in case of small- and medium-sized enterprises (SMEs).

Design/methodology/approach

The study is based on Estonian whole population of SMEs, in total 67,058 observations, and data are obtained from Estonian Business Register. Failure risk (FR) is portrayed with a well-known Altman et al. (2017) model, while seven variables reflecting corporate governance (CG) based on previous studies have been selected. As the method, logistic regression (LR) is applied with FR in the binary form as a dependent variable and seven CG variables as independent. The effect of firm size and age is studied with two separate LR models.

Findings

The results indicate that with the growth in manager’s age and the presence of managerial ownership, failure risk reduces. In turn, the presence of larger boards and managers having directorships in other firms leads to higher failure risk. Gender heterogeneity in the board, board tenure length and ownership concentration by means of having a majority owner are not associated with failure risk. The obtained results vary with firm size and age.

Originality/value

Unlike this study, research published on this topic earlier has used a much narrower definition of failure, mostly focused on large and listed companies, been sample based and information about corporate governance variables has often been obtained through questionnaires. All these limitations are relaxed in this population level study.

Details

Management Research Review, vol. 42 no. 6
Type: Research Article
ISSN: 2040-8269

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Article
Publication date: 3 August 2015

Hu-Chen Liu, Jian-Xin You, Xue-Feng Ding and Qiang Su

– The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes.

Abstract

Purpose

The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes.

Design/methodology/approach

A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes.

Findings

A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies.

Practical implications

The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method.

Originality/value

This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

Details

International Journal of Quality & Reliability Management, vol. 32 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

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Article
Publication date: 8 August 2016

Longbiao Li, Suyi Bi and Youchao Sun

– The purpose of this paper is to develop a method to predict the multi-failure risk of aero engine in service and to evaluate the effectiveness of different corrective actions.

Abstract

Purpose

The purpose of this paper is to develop a method to predict the multi-failure risk of aero engine in service and to evaluate the effectiveness of different corrective actions.

Design/methodology/approach

The classification of failure risk level, the determination of hazard ratio and the calculation of risk factor and the risk per flight have been proposed. The multi-failure risk assessment process of aero engine has been established to predict the occurrence of failure event and assess the failure risk level. According to the history aero engine failure data, the multi-failure risk, i.e., overheat, blade wounding, pump failure, blade crack, pipe crack and combustor crack, has been predicted considering with and without corrective action. Two corrective actions, i.e., reduce the maintenance interval and redesign the failure components, were adopted to analyze the decreasing of risk level.

Findings

The multi-failure risk of aero engine with or without corrective action can be determined using the present method. The risk level of combustor crack decreases from high-risk level of 1.18×1e−9 without corrective action to acceptable risk level of 0.954×1e−9 by decreasing the maintenance interval from 1,000 to 800 h, or to 0.912×1e−9 using the redesign combustor.

Research limitations/implications

It should be noted that probability of detection during maintenance actions has not been considered in the present analysis, which would affect the failure risk level of aero engine in service.

Social implications

The method in the present analysis can be adapted to other types of failure modes which may cause significant safety or environment hazards, and used to determine the maintenance interval or choose appropriate corrective action to reduce the multi-failure risk level of aero engine.

Originality/value

The maintenance interval or appropriate corrective action can be determined using the present method to reduce the multi-failure risk level of aero engine.

Details

Multidiscipline Modeling in Materials and Structures, vol. 12 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

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