for Journals by Title or ISSN
for Articles by Keywords
help
  Subjects -> ENGINEERING (Total: 2266 journals)
    - CHEMICAL ENGINEERING (190 journals)
    - CIVIL ENGINEERING (183 journals)
    - ELECTRICAL ENGINEERING (99 journals)
    - ENGINEERING (1195 journals)
    - ENGINEERING MECHANICS AND MATERIALS (391 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (64 journals)
    - MECHANICAL ENGINEERING (89 journals)

ENGINEERING (1195 journals)

The end of the list has been reached or no journals were found for your choice.
Journal Cover Journal of Quality in Maintenance Engineering
  [SJR: 0.503]   [H-I: 37]   [5 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1355-2511
   Published by Emerald Homepage  [335 journals]
  • Maintenance backlog for improving Integrated Planning
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose The aim of this article is to develop a novel model for maintenance backlog of physical assets and structure it in a framework for Integrated Planning. Design/methodology/approach Reliability theory principles for modelling maintenance backlog are used. Furthermore, to structure a framework for Integrated Planning, literature study combined with earlier case studies are used. Findings The framework for Integrated Planning facilitates the model of maintenance backlog. In addition to providing real-time diagnosis indicators, maintenance backlog is regarded as valuable information for decision support in Integrated Planning. Originality/value Development of maintenance backlog applied to Integrated Planning.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:20Z
      DOI: 10.1108/JQME-01-2016-0002
       
  • Structured maintenance engineering policy development based on a
           production machine process perspective
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose The current study presents the development of a maintenance engineering policy in the context of a decision support model based on a production machine process perspective. Design/methodology/approach The structure of the policy is called the maintenance decision support (MDS) model, which consists of three steps; initial setup, deterioration monitoring, and decision making. A detail presentation of each step of the proposed model together with a real case example from the pulp manufacturing industry proves the applicability of the model. Findings Validation of the proposed MSD model is as follow. In Task 1 of Step 1, the cutting, sealing, and perforating line processes are classified as critical machining process (CMP). The analysis of Task 2 of Step 1 found that cutting knife, bearing, and motor are classified as the components that most possibly contribute to cutting appearance quality. In Task 3 of Step 1 found that that cutting knife is classified as an MSC with non-repairable and single-component type characteristics. The result of Step 2 suggested that at 29 hours of operating time the decision of do-something is suggested. In the following step (Step 3), for the case of the cutting knife, which has been classified as a non-repairable type component; and, thus, the decision to perform preventive replacement of cutting knife is recommended to be carried out at 29 hours of operating time. Research limitations/implications The uniqueness of the model is that it systematically considers different machinery component(s) characteristics to make maintenance decisions, including single- and multiple-component cases, repairable and non-repairable types, and functional or/and physical failure types. Practical implications The proposed MDS model provides a systematic guideline for identifying, evaluating, and monitoring, which makes related maintenance decisions. Three significant maintenance decisions can be determined based on the proposed MDS model, which includes an appropriate time to perform maintenance, correct maintenance actions to be performed, and the right component required for maintenance (for multi component cases). Originality/value One of the vital elements in considering the production machine process perspective towards development of MDS model is the important needs to use product output/quality characteristics for machine deterioration monitoring and decision making processes.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:19Z
      DOI: 10.1108/JQME-03-2016-0009
       
  • Development of strategic asset management planning in the petroleum
           industry
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose Due to the certain risk carried in offshore petroleum installations, the integrity of these installations needs to be maintained at all times. Thus, asset integrity management (AIM) needs to be formulated and monitored to achieve the integrity objective. This paper studies the practices and progression of strategic AIM planning in the petroleum industry. Design/methodology/approach The paper is written based on a literature study, observations, and data collected from industry practitioners through an online questionnaire and interviews to study the AIM practices in their organization. Validation of the results is performed through respondents´ reviews and cross-referencing with existing literature and supplemental data. Findings The paper identifies, analyses and validates the work structure in formulating an AIM strategic plan. Research limitations/implications Even though the research focuses on the AIM practices of offshore petroleum installations, the result can be implemented in similar fields. Originality/value Researchers or practitioners can benefit from the knowledge gained of current practices and the presented work structure in establishing an AIM strategic plan.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:18Z
      DOI: 10.1108/JQME-04-2016-0016
       
  • Preventive Maintenance (PM) planning: a review
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose The purpose of this review paper is to provide comprehensive information on PM planning and methods used in the industry in order to achieve an effective maintenance system. Design/methodology/approach The literature review is organized in a way that provides the general overview of the researches done in the PM. This paper discusses the literatures that had been reviewed on four main topics, which are the holistic view of maintenance policies, PM planning, PM planning concept and PM planning-based in developing optimal planning in executing PM actions. Findings Preventive Maintenance (PM) policy is one of the original proactive techniques that has been used since the start of researches on maintenance system. Review of methods presented in this paper shows that most researches analyse effectiveness using artificial intelligence (AI), simulation, mathematical formulation, matrix formation, critical analysis and multi criteria method. While in practice, PM activities were either planned based on cost, time or failure. Research trends on planning and methods for PM show that the variation of approaches used over the year from early 90s until today. Practical implications Research about PM is known to be extensively conducted and majority of companies applied the policy in their production line. However, most analysis and method suggested in published literatures were done based on mathematical computation rather than focusing on solution to real problems in the industry. This normally would lead to the problems in understanding by the practitioner. Therefore, this paper presented researches on PM planning and suggested on the methods that are practical, simple and effective for application in the real industry. Originality/value The originality of this paper comes from its detail analysis of PM planning in term of its research focus and also direction for application. Extensive reviews on the methods adopted in relation to PM planning based on the planning-based such as cost-based, time-based and failure-based were also provided.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:17Z
      DOI: 10.1108/JQME-04-2016-0014
       
  • Prognosis of degradation based on a new dynamic method for Remaining
           Useful Life prediction
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose The purpose of this paper is to create a new method of prognosis based on Remaining Useful Life (RUL) prediction for degradation assessment. Design/methodology/approach In the present paper we describe a new method of prognosis to improve the accuracy of forecasting the system state. This framework of forecasting integrates the model-based information and the hybrid approach, which employs the structured residuals in the first part and the Particle Filter in the second part. Findings The performance of the suggested fusion framework is employed to predict the RUL of battery pack in Hybrid Electric Vehicle (HEV). The results show that the proposed method is plausible due to the good prediction of RUL, and can be effectively applied to many systems for prognosis. Originality/value In this study we illustrate how the suggested method can provide an accurate prediction of the RUL over conventional data-driven methods without physical model and classical Particle Filter with a single damage model.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:16Z
      DOI: 10.1108/JQME-03-2016-0012
       
  • Understand what your maintenance service partners value
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose The study aims at identifying what is currently valued in maintenance services. The study first conceptualizes the value construct through an examination of its elements, including both financial and non-financial elements, and secondly provides insight into its actors’ (i.e. customer companies, service providers, equipment providers) attitudes towards value creation. Design/methodology/approach The study uses data collected from maintenance service professionals by an online survey. First an explorative factor analysis is conducted to examine the value construct. After this cluster analysis is conducted to define the actors. Findings The empirical findings suggest seven main elements that capture maintenance service value: relationship synergies, reliability of the service partner, development, availability, service solutions and problem solving ability, EHSQ (environment, health, safety and quality), and adaptability to suit different situations. Further analysis reveals that the actors can be divided into three main strategy types: basic, quality- and collaboration -oriented partners. Originality/value In previous studies the comprehensive nature of maintenance service value has received less attention, and the literature has focused on the technical and financial aspects. This paper provides a new conceptualization of the value creating elements, including also non-financial elements, and offers an integrated measure for the actors to identify the comprehensive value construct around maintenance services. In addition, the findings show that the actors in the field still have varying strategies when considering value creation. Communication and mutual understanding of the value creating elements are important so that right services are carried out and developed with the right partners.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:14Z
      DOI: 10.1108/JQME-08-2016-0035
       
  • Identification of problems in maintenance operations and comparison with
           manufacturing operations: a review
    • Abstract: Journal of Quality in Maintenance Engineering, Volume 23, Issue 2, May 2017.
      Purpose In present context of globalization, maintenance of production systems is very important. A lot of organizations are facing a lot of problems in maintenance management. Therefore the purpose of this paper is to identify the main problems in maintenance operations and compare these problems with manufacturing as found in the literature for effective maintenance. Design/methodology/approach To identify the main problems in maintenance operations and to compare them with those in manufacturing operations, a large quantity of published literature was studied. The paper systematically categorizes the published literature and then analyzes and reviews it theoretically. Findings Lack of top management support, lack of measurement of overall equipment effectiveness (OEE), lack of strategic planning and implementation, and many more problems are biggest problems in the maintenance operations as well as manufacturing operations. These have emerged as top problems in implementation of effective maintenance strategies in industries. Research limitations/implications From findings we can conclude that for good maintenance, top management is supposed to be supportive in taking different initiatives. Industrial organizations should focus on improving overall performance of machines identified as OEE rather than only productivity of machines. This paper will be extremely useful for the researchers, maintenance professionals and others concerned with maintenance to understand the significance of maintenance problems in industries. Originality/value These findings will be highly useful for professionals from manufacturing sector in implementing effective maintenance strategy in the maintenance management system.
      Citation: Journal of Quality in Maintenance Engineering
      PubDate: 2017-03-23T12:33:13Z
      DOI: 10.1108/JQME-06-2016-0027
       
  • 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
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
Home (Search)
Subjects A-Z
Publishers A-Z
Customise
APIs
Your IP address: 54.224.204.189
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016