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Article
Publication date: 15 March 2021

Sofiene Dellagi and Mohamed Noomane Darghouth

In this paper, a maintenance strategy based on improved imperfect maintenance actions with stochastic repair times for multiperiod randomly failing equipment is developed…

Abstract

Purpose

In 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/approach

A 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.

Findings

The 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/implications

Given 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 implications

The 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/value

Contrary 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.

Details

Journal of Quality in Maintenance Engineering, vol. 28 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 1 August 2004

John Lau, Nick Hoo, Rob Horsley, Joe Smetana, Dongkai Shangguan, Walter Dauksher, Dave Love, Irv Menis and Bob Sullivan

Temperature cycling tests, and statistical analysis of the results, for various high‐density packages on printed‐circuit boards with Sn‐Cu hot‐air solder levelling…

Abstract

Temperature cycling tests, and statistical analysis of the results, for various high‐density packages on printed‐circuit boards with Sn‐Cu hot‐air solder levelling, electroless nickel‐immersion gold, and organic solder preservative finishes are investigated in this study. Emphasis is placed on the determination of the life distribution and reliability of the lead‐free solder joints of these high‐density package assemblies while they are subjected to temperature cycling conditions. A data acquisition system, the relevant failure criterion, and the data extraction method will be presented and examined. The life test data are best fitted to the Weibull distribution. Also, the sample mean, population mean, sample characteristic life, true characteristic life, sample Weibull slope, and true Weibull slope for some of the high‐density packages are provided and discussed. Furthermore, the relationship between the reliability and the confidence limits for a life distribution is established. Finally, the confidence levels for comparing the quality (mean life) of lead‐free solder joints of high‐density packages are determined.

Details

Soldering & Surface Mount Technology, vol. 16 no. 2
Type: Research Article
ISSN: 0954-0911

Keywords

Article
Publication date: 26 September 2008

Carlos Manuel Inácio da Silva, Carlos Manuel Pereira Cabrita and João Carlos de Oliveira Matias

The purpose of this paper is to emphasize that the choice of the most appropriate maintenance model and policies is the best way to reduce significantly the maintenance…

2294

Abstract

Purpose

The purpose of this paper is to emphasize that the choice of the most appropriate maintenance model and policies is the best way to reduce significantly the maintenance costs as well as to optimize the useful Key Performance Indicators – failure rates, reliability, mean time between failures, mean time to repair, and equipment availabilities.

Design/methodology/approach

In order to implement the Asset Effectiveness Optimization AEO as well as the Overall Equipment Effectiveness OEE, improving productivity in a complex food‐products plant, the paper presents a theoretical and experimental study related to the maintenance costs directly associated with the equipment used in production tasks.

Findings

The developed tool is an efficient method of calculating the maintenance costs and allows one by means of computational simulation to define the most advisable maintenance policy. On the other hand, the proposed relationships are universal and could be used as an economic evaluation indicator for other industries and equipment.

Research limitations/implications

Further research should include the application of the proposed methodology to the similar equipment of other food‐products plants as well as to other different equipment in order to create benchmarking procedures. This generator of technical information is the most appropriate method of optimizing maintenance key performance indicators.

Practical implications

As is well known, equipment availability must be as close to 100 per cent as possible, in order to avoid non‐planned breakdowns with the consequent production losses. Then it is important to adopt the most advisable maintenance policies and practices, the proposed methodology being an efficient tool for evaluating the maintenance performance and, in addition, for optimizing procedures.

Originality/value

The proposed methodology represents an efficient way to evaluate the maintenance performance as well as to choose better maintenance policies and practices in order to reduce costs and increase maintenance key performance indicators.

Details

Journal of Quality in Maintenance Engineering, vol. 14 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 13 August 2019

Liling Ge and Yingjie Zhang

The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales…

Abstract

Purpose

The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system.

Design/methodology/approach

The paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation.

Findings

The proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study.

Research limitations/implications

The case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed.

Practical implications

So far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision.

Originality/value

The multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.

Details

Engineering Computations, vol. 37 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 25 May 2020

Gerald Kenechukwu Inyiama and Sunday Ayoola Oke

Downtime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control…

Abstract

Purpose

Downtime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control process plants. Notwithstanding, the impacting nature of process equipment failure on the operating hours in bottling plants remains inadequately examined. In this paper, the cause-and-effect analysis was used to establish the root cause of the downtime problem and Pareto analysis employed to justify the greatest opportunities for improvement in reducing downtime and increasing reliability levels. Weibull analysis is then conducted on the industrial setting. Novel aspect ratios are proposed.

Design/methodology/approach

Using the Weibull failure function of machines as a principal facilitator to produce failure predictions, the downtime behaviour of a process plant was modelled and tested with practical data from a bottling process plant. This research was conducted in a Nigerian process bottling plant where historical data were examined.

Findings

The analysis of the results shows the following principal outcome: First, the machines with the highest and least downtime values are 2 and 5, respectively, with correspondingly mean values of 22.83 and 4.39 h monthly. Second, the total downtime 92.05 and 142.14 h for the observed and target downtime, with a coefficient of determination of 0.5848 was recorded. Third, as month 1 was taken as the base period (target), all the machines, except M5 had accepted performance, indicating proper preventive maintenance plan execution for the bottling process plant. Availability shows a direct relationship between the failure and uptime of the machines and the downtime impacts on production. Two machines had random failure pattern and five machines exhibited a wear-out failure pattern and probably due to old age and wear of components in the machines.

Originality/value

The major contribution of the paper is the Weibull modelling in a unique application to a bottling plant to avoid current practices that use reliability software that is not easily accessible.

Details

International Journal of Quality & Reliability Management, vol. 38 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 2 May 2019

Hasnida Ab-Samat and Shahrul Kamaruddin

Opportunistic maintenance (OM) policy is a prospective maintenance approach that instigates for a more effective and optimized system. The purpose of this paper is to

Abstract

Purpose

Opportunistic maintenance (OM) policy is a prospective maintenance approach that instigates for a more effective and optimized system. The purpose of this paper is to provide the steps and methods used in model development processes for the application of the OM policy.

Design/methodology/approach

Dubbed as opportunistic principle toward optimal maintenance system (OPTOMS) for OM policy toward optimal maintenance system, the model is devised as a decision support system model and contains five phases. The motivation and focus of the model resolve around the need for a practical framework or model of maintenance policy for the application in an industry. In this paper, the OPTOMS model was verified and validated to ensure that the model is applicable in the industry and robust as a support system in decision making for the optimal maintenance system.

Findings

From the verification steps conducted in a case study company, it was found that the developed model incorporated simple but practical tools like check sheet, failure mode and effect analysis (FMEA), control chart that has been commonly used in the industry.

Practical implications

This paper provides the general explanations of the developed model and tools used for each phase in implementing OM to achieve an optimal maintenance system. Based on a case study conducted in a semiconductor company, the OPTOMS model can align and prepare the company in increasing machine reliability by reducing machine downtime.

Originality/value

The novelty of this paper is based on the in-depth discussion of all phases and steps in the model that emphasize on how the model will become practical theories in conducting an OM policy in a company. The proposed methods and tools for data collection and analysis are practical and commonly used in the industry. The framework is designed for practical application in the industry. The users would be from the Maintenance and Production Department.

Details

Journal of Quality in Maintenance Engineering, vol. 26 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 1 May 1998

Kyoumars Bahrami‐Ghasrchami, J.W.H. Price and J. Mathew

For manufacturing systems which are in continuous operation and subject to breakdown, inspection can be an appropriate maintenance strategy. In this situation, inspection…

524

Abstract

For manufacturing systems which are in continuous operation and subject to breakdown, inspection can be an appropriate maintenance strategy. In this situation, inspection can reduce down‐time and increase system reliability. In this paper two main ideas are proposed. In the first, an inspection effect function is introduced which modifies the traditional system failure rate distribution. This modification involves a formula which demonstrates the effect of inspection frequency and inspection effectiveness on system failure rate distribution. It is then argued that under inspection policy the system’s traditional failure rate is necessarily affected by these factors. The second idea presents a maintenance model in which the system is interrupted in its time to failure by inspections. Optimisation of this model determines an optimal inspection frequency which minimises the system’s total down‐time. Thus, it is shown that by optimising inspection frequency system availability can be increased.

Details

International Journal of Quality & Reliability Management, vol. 15 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 June 1997

Weishing Chen and Tai‐Hsi Wu

Studies a non‐homogeneous Poisson process software reliability model with failure rate based on Zipf’s law. Discusses the rate function, mean value function and the…

Abstract

Studies a non‐homogeneous Poisson process software reliability model with failure rate based on Zipf’s law. Discusses the rate function, mean value function and the estimation of parameters. The proposed model can be used to analyse the reliability growth. The results of applying the proposed model and Duane model to several actual failure data sets show that the model with failure rate observed from Zipf’s law can fit not only in operating software but also in testing software. The result also indicates that the proposed model has better long‐term predictive capability than the Duane model for failure data sets with power law’s failure rates

Details

International Journal of Quality & Reliability Management, vol. 14 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 7 March 2022

Nzita Alain Lelo, P. Stephan Heyns and Johann Wannenburg

Industry decision makers often rely on a risk-based approach to perform inspection and maintenance planning. According to the Risk-Based Inspection and Maintenance…

Abstract

Purpose

Industry decision makers often rely on a risk-based approach to perform inspection and maintenance planning. According to the Risk-Based Inspection and Maintenance Procedure project for the European industry, risk has two main components: probability of failure (PoF) and consequence of failure (CoF). As one of these risk drivers, a more accurate estimation of the PoF will contribute to a more accurate risk assessment. Current methods to estimate the PoF are either time-based or founded on expert judgement. This paper suggests an approach that incorporates the proportional hazards model (PHM), which is a statistical procedure to estimate the risk of failure for a component subject to condition monitoring, into the risk-based inspection (RBI) methodology, so that the PoF estimation is enhanced to optimize inspection policies.

Design/methodology/approach

To achieve the overall goal of this paper, a case study applying the PHM to determine the PoF for the real-time condition data component is discussed. Due to a lack of published data for risk assessment at this stage of the research, the case study considered here uses failure data obtained from the simple but readily available Intelligent Maintenance Systems bearing data, to illustrate the methodology.

Findings

The benefit of incorporating PHM into the RBI approach is that PHM uses real-time condition data, allowing dynamic decision-making on inspection and maintenance planning. An additional advantage of the PHM is that where traditional techniques might not give an accurate estimation of the remaining useful life to plan inspection, the PHM method has the ability to consider the condition as well as the age of the component.

Research limitations/implications

This paper is proposing the development of an approach to incorporate the PHM into an RBI methodology using bearing data to illustrate the methodology. The CoF estimation is not addressed in this paper.

Originality/value

This paper presents the benefits related to the use of PHM as an approach to optimize the PoF estimation, which drives to the optimal risk assessment, in comparison to the time-based approach.

Details

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

Keywords

Article
Publication date: 18 May 2021

Pavel Jahoda and Radim Bris

The paper aims to explore unavailability of dormant systems that are under both preventive and corrective maintenance. Preventive maintenance is considered as a failure

Abstract

Purpose

The paper aims to explore unavailability of dormant systems that are under both preventive and corrective maintenance. Preventive maintenance is considered as a failure based maintenance model, where full renew is realized at the occurrence of every nth failure. It proposes the imperfect corrective maintenance model, where each restoration process deteriorates the system lifetime, probability distribution of which is gradually changed via increasing failure rate.

Design/methodology/approach

Basic reliability mathematics necessary for unavailability quantification of a system which undergoes a real aging process with maintenance has been derived proceeding from renewal theory. New renewal cycle was defined to cover the real aging process and the expectation of its length was determined. All events resulting in the failure of studied system were explored to determine their probabilities. An integral equation where the unavailability function characterizing studied system is its solution was derived.

Findings

Preventive maintenance is closely connected with the occurrence of the nth failure, which starts its renew. The number n can be considered as a parameter which significantly influences the unavailability course. The paper shows that the real aging process characterized by imperfect repairs can significantly increase the unavailability courses in contrast with theoretical aging. This is true for both monitored and dormant systems.

Originality/value

Although mathematical methods used in this article were inspired and influenced by the work of reference (van der Weide and Pandey, 2015), derivation of final formulas for unavailability quantification considering the new renewal cycle is original. Idea of the real aging process is new as well. This paper fulfils an identified need to manage the maintenance of realistically aging systems.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

1 – 10 of over 100000