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Journal Cover Journal of Quality in Maintenance Engineering
  [SJR: 0.503]   [H-I: 37]   [4 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1355-2511
   Published by Emerald Homepage  [335 journals]
  • Total Productive Maintenance and manufacturing performance improvement
    • First page: 2
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose The purpose of this paper is to examine the multidimensionality of Total Productive Maintenance (TPM) and its relationship with manufacturing performance improvement in the Malaysian manufacturing sector. Specifically, this study evaluates the contribution of each TPM success factors in improving manufacturing performance. Design/methodology/approach Data from 89 employees who participated in the survey were used to test the proposed research framework. A structured questionnaire adopted from Ahuja and Khamba (2006) was used to assess the Malaysian context. Findings The analytical results reveal that traditional maintenance initiatives and TPM implementation initiatives significantly affect manufacturing performance, but not top management leadership and maintenance organisation. Top management roles and commitment are critical in the early stage to determine the master plan and initiate the implementation of the whole programme. However, traditional maintenance and TPM implementation initiatives gradually enable engagement, proper planning, right execution and continuous improvement, ultimately improving the manufacturing performance indicators significantly. The findings further unveil that TPM is not sustainable in Malaysia’s manufacturing organisations in the long run. Research limitations/implications - Practical implications This analysis is vital for senior managers of manufacturing organisations that have implemented TPM or are considering introducing TPM in their organisations. Originality/value This study contributes to the literature by examining beyond the introduction and stabilisation phase of TPM to provide an insight of whether TPM is sustainable in the long run.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-24T11:49:34Z
      DOI: 10.1108/JQME-07-2015-0033
       
  • Risk assessment of mining projects in Ghana
    • First page: 22
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose The main purpose of this study is to assess the critical risk factors affecting mining projects in Ghana Design/methodology/approach A purposive sampling approach was used in selecting the respondents for the study. These were practitioners working on mining projects in Ghana Findings The study identified 22 risk factors contributing to mining project failure in Ghana. The five most critical mining project risk factors based on both probability of occurrence and impact were: (1) Unstable commodity prices, (2) Inflation/Exchange rate, (3) Land degradation, (4) High cost of living and (5) Government bureaucracy for obtaining licenses. Mitigation measures for addressing the identified risk factors were identified. Research limitations/implications This paper is limited to data collected from practitioners working on mining projects. Due to geographic and logistical constraints, the study did not include the perception of local communities in quantifying the risk factors Practical implications This paper has documented the critical risk factor affecting the mining industry in Ghana. Though the identified risk types are also prevalent in other sectors of the construction industry, the key findings of this paper emphasize the need for a comprehensive risk management culture in the mining sector. From an academic research perspective, the paper contributes to a conceptual risk assessment framework. Originality/value The information gathered through this research can be utilized in identifying and understanding risks during the early stages of mining project implementation.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-24T11:49:36Z
      DOI: 10.1108/JQME-09-2015-0044
       
  • Overall equipment effectiveness of tyre curing press: a case study
    • First page: 39
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose The purpose of this study is to formulate a benchmark to increase the tyre curing press production rate while minimizing tyre curing press downtime and maintenance cost with the help of maintenance management technique based on overall equipment effectiveness (OEE). Design/methodology/approach The methodology is based on determining overall equipment effectiveness of tyre curing press before and after rectifying the causes of failures. Failure mode and effect analysis (FMEA) technique is used to find out the root causes of repetitive failures in tyre curing press by using risk priority number (RPN). Findings Significant change in the value of OEE is observed after rectifying the repetitive failures which were determined using failure mode and effect analysis technique (FMEA). Thus, it is concluded that the OEE and FMEA assists in improving industrial performance and competitiveness of the production equipment studied. Research limitations/implications This study is limited to determine the OEE of single equipment only not the whole production system. Manufacturing facilities are dependent on the operating environment therefore comparison of two different manufacturing plants based on OEE value would not be justified. Practical implications This study can be applied in any tyre manufacturing industry in order to take competitive benefits like reduction in equipment downtime, increased production and reduction in maintenance cost. Originality/value The angle, from which the paper approaches the bottleneck problem in a tyre production line, is original for the studied company and shows positives results. It allows the company to apply the same approach in their other production equipment, lines and factories to achieve an improvement in industrial performance and competitiveness.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-25T12:03:26Z
      DOI: 10.1108/JQME-06-2015-0021
       
  • Mapping the research approach of asset management studies in the petroleum
           industry
    • First page: 57
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose The purpose of this paper is to study the current research approaches in asset management (AM), to evaluate some of the prevalent research methods in AM studies and to summarize the result into a building-block research that may provide design guidelines in AM studies. Design/methodology/approach AM publications were selected for this study using by online search engines and the publications were classified based on the appropriate research approaches. The results will be discussed and a suitable building-block research for AM studies will be constructed based on the identified research approaches. Findings The paper identifies, analyses and validates the research-approaches found in a sample of online AM publications. The research-approaches and their associated methods will be discussed to develop understanding of the context of these approaches in AM research. Research limitations/implications The paper limit the study in publications within the AM field in the petroleum industry. However, the research methods that are presented covers the most common research methods found in publications. Thus, although the sample of publications may not represent the entire population, the same approach and result can be used in similar topics and conditions. Originality/value Researchers or practitioners can benefit from the building blocks of research to develop a research design for AM studies. Moreover, the paper also provides information on common research methods and data gathering techniques that can be used for similar studies.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-25T12:03:25Z
      DOI: 10.1108/JQME-07-2015-0031
       
  • Agent-based modeling of availability for complex multiple units systems
    • First page: 71
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose The purpose of the study is to propose an availability modeling method of Complex Multiple Units System (CMUS) based on the multi-agent technique. Design/methodology/approach Based on the multi-agent technique, this paper describes the availability model structure for CMUS and develops agent-based models of components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff, as well as the communication method among the different agents. On the basis of the agent-based availability modeling theory, the availability simulation scheme of CMUS is given using Matlab. Thus, the availability modeling theory of CMUS and its simulation method are developed. To demonstrate the applicability of the proposed availability modeling method, a numerical example is given. Findings The proposed agent-based modeling method is applicable to availability modeling of CMUS, including the modeling of component failure, maintenance tools/fields/staff, maintenance policy, and structural/economic dependence among components. Practical implications As a bottom-top, modular, expandable, and reusable modeling theory, the agent-based modeling method might be useful for availability modeling of different CMUSs in reality. Originality/value The multi-agent technique is introduced into availability modeling of multi-component systems in this paper. Thus, it is possible to model failure of many components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff together for availability analysis of complex systems of equipment.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-25T12:03:27Z
      DOI: 10.1108/JQME-06-2013-0033
       
  • Health monitoring impact on non-repairable component supply methods
    • First page: 82
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose From on-board automotive diagnostics to real-time aircraft state of health, the implementation of health monitoring and management systems are an increasing trend. Further, reductions in operating budgets are forcing many companies and militaries to consider new operating and support environments. Combined with longer service lives for aircraft and other systems, maintenance and operations processes must be reconsidered. The majority of research efforts focus on health monitoring techniques and technologies, leaving others to determine the maintenance and logistics impact on the systems. Design/methodology/approach This research analyzes the impact of a health monitoring system on a squadron of aircraft. Flight, maintenance and logistics operations are stochastically modeled to determine the impact of program decisions on supply metrics. An Arena discrete event simulation is utilized to conduct this research on 20 components on each of the 12 aircraft modeled. Costs and availability are recorded for comparison across three sparing scenarios to include economic order quantity for baseline and health monitoring cases and a just-in-time health monitoring set of simulations. Findings Data are presented for economic order quantity and just-in-time supply methods. A comparison of health monitoring enabled supply to current methods shows cost savings and availability gains. The different methodologies are compared and discussed as a trade-space for programmatic decisions. Originality/value This work demonstrates the ability of health monitoring systems and condition based maintenance to affect supply ordering decisions. The development of trade-spaces within operating environments is demonstrated along with the ability to conduct cost benefit analyses.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-25T12:03:30Z
      DOI: 10.1108/JQME-08-2015-0036
       
  • Optimal CBM policy with two sampling intervals
    • First page: 95
      Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 1, March 2017.
      Purpose In this study, we propose a novel condition-based maintenance (CBM) policy with two sampling intervals for a system subject to stochastic deterioration described by the Cox's proportional hazards model (PHM). Design/methodology/approach Unlike the previous CBM policies widely discussed in the literature which use sequential or periodic monitoring, we propose a new sampling strategy based on two sampling intervals. From the economic point of view, when the sampling is costly, it is advantageous to monitor the system less frequently when it is in a healthy state, and more frequently when it deteriorates and enters the unhealthy state. In this paper, the new or renewed system is monitored using a longer sampling interval. When the esti- mated hazard function of the system exceeds a warning limit, the observations are taken more frequently, i.e., the sampling interval changes to a shorter one. Preventive mainte- nance is performed when either the hazard function exceeds a maintenance threshold or the system age exceeds a pre-determined age. A more expensive corrective maintenance is performed upon system failure. The proposed model is formulated in the semi-Markov decision process framework (SMDP). Findings The optimal maintenance policy is found and a computational algorithm based on policy iteration for SMDP is developed to obtain the control thresholds as well as the sampling intervals minimizing the long-run expected average cost per unit time. Research limitations/implications A numerical example is presented to illustrate the whole procedure. The newly proposed maintenance policy with two sampling intervals outperforms previously developed maintenance policies using PHM. The paper compares the proposed model with a single sampling interval CBM model and well-known age-based model. Formulas for the conditional reliability function and the mean residual life are also derived for the proposed model. Sensitivity analysis has been performed to study the effect of the changes in the Weibull parameters on the average cost. Practical implications The results show that considerable cost savings can be obtained by implementing the maintenance policy developed in this paper. Originality/value Unlike the previous CBM policies widely discussed in the literature which use sequential or periodic monitoring, we propose a new sampling strategy based on two sampling intervals. The proposed model is formulated and the optimal policy which outperforms previous policies is found in the semi-Markov decision process framework (SMDP). Formulas for the conditional reliability function and the mean residual life are also derived.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-01-25T12:03:26Z
      DOI: 10.1108/JQME-07-2015-0030
       
  • Problem-Solving Approaches in Maintenance Cost Management: A Literature
           Review
    • First page: 334
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose The purpose of this paper is to investigate the use of problem-solving approaches in maintenance cost management (MCM). In particular, the paper aims to examine characteristics of MCM models and to identify patterns for classification of problem-solving approaches. Design/methodology/approach This paper reflects an extensive and detailed literature survey of 68 (quantitative or qualitative) cost models within the scope of MCM published in the period from 1969 to 2013. The reviewed papers have been critically examined and classified based on implementing a morphological analysis which employs 8 criteria and associated expressions. In addition, the survey identified two main perspectives of problem-solving, first synoptic/incremental, second heuristics/meta-heuristics. Findings The literature survey revealed the patterns for classification of the MCM models, especially the characteristics of the models for problem-solving in association with the type of modelling, focus of purpose, extent and scope of application, and reaction and dynamics of parameters. Majority of the surveyed approaches is mathematical respectively synoptic. Incremental approaches are much less and only few are combined (i.e. synoptic and incremental). A set of features is identified for proper classification, selection and coexistence of the two approaches. Research limitations/implications This paper provides a basis for further study of heuristic and meta-heuristic approaches to problem-solving. Especially the coexistence of heuristic, synoptic and incremental approaches needs to be further investigated. Practical implications The detected dominance of synoptic approaches in literature - especially in the case of specific application areas - contrasts to some extent to the needs of maintenance managers in practice. Hence the findings of this paper particularly address the need for further investigation on combining problem-solving approaches for improving planning, monitoring and controlling phases of MCM. Continuous improvement of MCM, especially problem-solving and decision-making activities, is tailored to the use of maintenance knowledge assets. In particular, maintenance management systems and processes are knowledge-driven. Thus, combining problem-solving approaches with knowledge management (KM) methods is of interest, especially for continuous learning from past experiences in MCM. Originality/value This paper provides a unique study of 68 problem-solving approaches in MCM, based on a morphological analysis. Hence suitable criteria and their expressions are provided. The paper reveals the opportunities for further interdisciplinary research in the maintenance cost lifecycle.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:49Z
      DOI: 10.1108/JQME-04-2015-0012
       
  • Total Productive Maintenance, Total Quality Management and operational
           performance: An empirical study of Indian pharmaceutical industry
    • First page: 353
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose This study investigates the impact of Total Productive Maintenance (TPM) and Total Quality Management (TQM) practices on operational performance and their inter-relationship. Design/methodology/approach The present study includes three main constructs namely TPM, TQM and operational performance of pharmaceutical industry. Under TPM, four constructs namely Disciplined Maintenance, Information Tracking, Housekeeping and Operator Involvement has been considered with the help of literature. In TQM, four constructs namely Quality Data and Reporting, Product Innovation, Research and Development Management and Technology Management has been considered. Out of 410 Indian pharmaceutical plants contacted for survey, 254 responses have been used in the study for analysis. The factor analysis, path model and structural equation modelling has been used to analyze the proposed framework. The results for alternate models has been studied, interpreted and reported. Finally the direct and indirect effect of TPM and TQM on operational performance has been tested and checked for proving and disproving the hypotheses. Findings TPM practices have a significant impact on plant level operational performance. When TPM and TQM practices are coming together to achieve operational performance, then TPM is having strong influence on operational performance. TQM is having significant support from TPM to achieve operational performance. TPM impact TQM and TQM in turn helps to achieve operational performance. TPM practices impact significantly research and development, product innovation and technology management, whereas quality data and reporting is the least contributor towards TQM. This may help industry to understand implications of implementation of TPM and TQM to achieve plant level operational performance. TPM will help to reduce the cost of quality in terms of reduced scrap and less defective products. Practical implications The present study provides the useful insights to practicing managers. In literature it has been mentioned that TQM helps in TPM implementation. In practice TPM plays a great role to achieve quality in processes and therefore in products. In turn quality products, with reduced work in process inventory, less defective products and reduced scrap helps to achieve the operational performance at plant level. TPM practices will help the organization to improve the pace of product innovation and improvement in productivity, which is critical to pharmaceutical industry. The continuous monitoring of TPM practices can help organizations to run day to day operations and maintenance requirement of each machine over a specified period of time. Originality/value The present study diagnose the inter-dimensional linkage between TPM, TQM and operational performance. The pharmaceutical industry is complex system of advance equipment’s and processes. After human resources, the health of machines/equipment’s describe the strength of an organization. The machines require the regular maintenance to produce the products with desired specifications. The specifications in medicines and very tight, which can be achieved only if machines/testing equipment’s are updated and maintained regularly. The TPM practices will helps the plants to achieve the operational performance by having quality in processes.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:55Z
      DOI: 10.1108/JQME-10-2015-0048
       
  • Improvement maintenance implementation based on downtime analysis approach
    • First page: 378
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose Improvement maintenance’s aim is identifying and implementing improvement action on equipment in service. This work proposes an approach based on downtime’s analysis to raise up equipment’s performance, such us reliability, maintainability, availability, and safety. Steps of this approach will be illustrated by industrial applications. Design/methodology/approach Furthermore, it proposes an approach based on a combination of several methods (FMECA, cause and effect diagrams, ABC analysis, 5W, RCA method, ..).This approach is based on the downtime analysis and lead to improve maintenance’s performance and equipment’s reliability, maintainability, availability and safety. Those objectives have a strong correlation with the downtime. Findings this approach led to apply easily improvement maintenance by using known methods. In the industrial application, this approach helps us to choose the good solution with the better life durance . Practical implications After following the steps simulated by the proposed approach, actions and concrete measures will be deducted and illustrated by the industrial’s application. Originality/value At present, there is not an explicit improvement maintenance, to lead to specific maintenance actions on equipment in service, in order to improve the maintenance function goals.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:51Z
      DOI: 10.1108/JQME-12-2013-0081
       
  • Effects of condition-based maintenance on costs caused by unscheduled
           maintenance of aircraft
    • First page: 394
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose This paper analyses the effects of condition-based maintenance based on unscheduled maintenance delays that were caused by ATA chapter 21 (air conditioning). The goal is to show the introduction of condition monitoring in aircraft systems Design/methodology/approach The research was done using the Airbus In-Service database to analyse the delay causes, delay length and to check if they are easy to detect via condition monitoring or not. These results were then combined with delay costs. Findings Analysis shows that about 80% of the maintenance actions that cause departure delays can be prevented when additional sensors are introduced. With already existing sensors it is possible to avoid about 20% of the delay causing maintenance actions. Research limitations/implications The research is limited on the data of the Airbus In-Service Database and on ATA chapter 21 (air conditioning). Practical implications The research shows that delays can be prevented by using existing sensors in the air-conditioning system for condition monitoring. More delays can be prevented by installing new sensors. Originality/value The research focuses on the effect of the air-conditioning system of an aircraft on the delay effects and the impact of condition monitoring on delays.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:53Z
      DOI: 10.1108/JQME-12-2015-0062
       
  • Availability forecast of mining equipment
    • First page: 418
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose This study presents a methodology for forecasting the availability off-highway trucks used in a fleet for large transport operations of ore and sterile rock from an open pit mine. Design/methodology/approach This methodology enables the estimation of the number of hours of preventive and corrective maintenance required, which are used to predict truck availability. We used historical data for our maintenance strategy based on the hours of operation. Findings These data are statistically analyzed to obtain the key quantities and statistical models required to project availability and to develop equipment replacement plans. Originality/value A methodology for forecasting availability to assets in open pit mining industry was implemented.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:52Z
      DOI: 10.1108/JQME-12-2015-0067
       
  • Reliability centered maintenance actions prioritization using fuzzy
           inference systems
    • First page: 433
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose Deploying an effective maintenance strategy across an organization stands out as an essential risk mitigation measure that plays a critical role towards improving the reliability and availability of production facilities. This article proposes a simple, yet well-structured approach towards prioritizing maintenance actions as part of a reliability centered maintenance implementation plan, and selecting the most important subset of those actions subject to time and budget constraints. Design/methodology/approach A comprehensive RCM actions prioritization methodology is proposed using four criteria: severity, benefit to cost ratio, customer satisfaction, and easiness of action implementation. The method utilizes fuzzy inference system (FIS) to incorporate subject matter experts’ feedback into the decision making process. The output of the FIS, which takes the form of a numerical weight that assesses the relative importance of each criterion, is then fed into a binary integer program (BIP) that selects the optimal maintenance actions out of a set of possible actions. Findings The implementation of the developed methodology is demonstrated using a real life example of a hydraulic brake system circuit that is used in construction equipment. The computational results illustrate the validity of the proposed approach and indicate that the selection of which maintenance actions to carry out is impacted by the relative importance (i.e. weight) of the considered criteria. Originality/value The work presented in this paper provides the decision makers with a systematic procedure that helps in selecting the most relevant maintenance actions instead of making the selection in a complete ad-hoc manner or based merely on subjective opinions.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:51Z
      DOI: 10.1108/JQME-07-2015-0029
       
  • Optimal periodic inspection policy for systems generating environmental
           damage over a finite time horizon
    • First page: 453
      Abstract: Journal of Quality in Maintenance Engineering, Volume 22, Issue 4, October 2016.
      Purpose We consider systems that generate damage to environment as they get older and degrade. The purpose of this study is to develop an optimal condition-based maintenance strategy for such systems in situations where they have a finite operational time requirement. We determine simultaneously the optimal number of inspections and the threshold level of environmental damage which minimize the total expected cost over the considered finite time horizon. Design/methodology/approach The environmental degradation level is monitored through periodic inspections. We model the environmental degradation process due to the equipment’s degradation by the Wiener process. A mathematical model and a numerical procedure are developed. Numerical calculations are performed and the influence of the variation of key parameters on the optimal solution is investigated. Findings Numerical tests indicate that as the cost of the penalty related to the generation of an excess damage to environment increases, inspections should become more frequent and the threshold level should be lowered in order to favor preventive actions reducing the probability to pay the penalty. Research limitations/implications Given the complexity of the cost function to be minimized, it is difficult to derive analytically the optimal solution. A numerical procedure is designed to obtain the optimal condition-based maintenance policy. Also, the developed model is based on the assumption that the degradation follows a process with stationary independent increments. This may not be appropriate for all types of degradation processes. Practical implications The proposed optimal maintenance policy may be relevant and very useful in the perspective of green operations. In fact, this paper offers to decision-makers a comprehensive approach to implement a green maintenance policy and to rapidly understand the net effect of the maintenance policy with respect to environmental regulation requirements. Originality/value The main contribution consists in the modeling and optimization of the condition-based maintenance policy over a finite time horizon. Indeed, existing condition-based maintenance models over an infinite time horizon are not applicable for systems with a finite operational time requirement.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2016-08-23T11:27:54Z
      DOI: 10.1108/JQME-09-2015-0045
       
 
 
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