Pub Date : 2022-01-24DOI: 10.1108/jqme-06-2021-0052
Laura Isabel Alvarez Quiñones, Carlos Arturo Lozano-Moncada, Diego Alberto Bravo Montenegro
PurposeThe purpose of this paper is to describe a methodology that has been set up to schedule predictive maintenance of distribution transformers at Cauca Department (Colombia) using machine learning.Design/methodology/approachThe proposed methodology relies on classification predictive model that finds the minimal number of distribution transformers prone to failure. To verify this, the model was implemented and tested with real data in Cauca Department Colombia.FindingsThe implementation of the methodology allows a saving of 13% in corrective maintenance expenses for the year 2020.Originality/valueThe proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for distribution transformers.
{"title":"Machine learning for predictive maintenance scheduling of distribution transformers","authors":"Laura Isabel Alvarez Quiñones, Carlos Arturo Lozano-Moncada, Diego Alberto Bravo Montenegro","doi":"10.1108/jqme-06-2021-0052","DOIUrl":"https://doi.org/10.1108/jqme-06-2021-0052","url":null,"abstract":"PurposeThe purpose of this paper is to describe a methodology that has been set up to schedule predictive maintenance of distribution transformers at Cauca Department (Colombia) using machine learning.Design/methodology/approachThe proposed methodology relies on classification predictive model that finds the minimal number of distribution transformers prone to failure. To verify this, the model was implemented and tested with real data in Cauca Department Colombia.FindingsThe implementation of the methodology allows a saving of 13% in corrective maintenance expenses for the year 2020.Originality/valueThe proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for distribution transformers.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49194505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-17DOI: 10.1108/jqme-07-2021-0058
A. Saihi, M. Ben-Daya, R. As'ad
PurposeMaintenance is a critical business function with a great impact on economic, environmental and social aspects. However, maintenance decisions' planning has been driven by merely economic and technical measures with inadequate consideration of environmental and social dimensions. This paper presents a review of the literature pertaining to sustainable maintenance decision-making models supported by a bibliometric analysis that seeks to establish the evolution of this research over time and identify the main research clusters.Design/methodology/approachA systematic literature review, supported with a bibliometric and network analysis, of the extant studies is conducted. The relevant literature is categorized based on which sustainability pillar, or possibly multiple ones, is being considered with further classification outlining the application area, modeling approach and the specific peculiarities characterizing each area.FindingsThe review revealed that maintenance and sustainability modeling is an emerging area of research that has intensified in the last few years. This fertile area can be developed further in several directions. In particular, there is room for devising models that are implementable, based on reliable and timely data with proven tangible practical results. While the environmental aspect has been considered, there is a clear scarcity of works addressing the social dimension. One of the identified barriers to developing applicable models is the lack of the required, accurate and timely data.Originality/valueThis work contributes to the maintenance and sustainability modeling research area, provides insights not previously addressed and highlights several avenues for future research. To the best of the authors' knowledge, this is the first review that looks at the integration of sustainability issues in maintenance modeling and optimization.
{"title":"Maintenance and sustainability: a systematic review of modeling-based literature","authors":"A. Saihi, M. Ben-Daya, R. As'ad","doi":"10.1108/jqme-07-2021-0058","DOIUrl":"https://doi.org/10.1108/jqme-07-2021-0058","url":null,"abstract":"PurposeMaintenance is a critical business function with a great impact on economic, environmental and social aspects. However, maintenance decisions' planning has been driven by merely economic and technical measures with inadequate consideration of environmental and social dimensions. This paper presents a review of the literature pertaining to sustainable maintenance decision-making models supported by a bibliometric analysis that seeks to establish the evolution of this research over time and identify the main research clusters.Design/methodology/approachA systematic literature review, supported with a bibliometric and network analysis, of the extant studies is conducted. The relevant literature is categorized based on which sustainability pillar, or possibly multiple ones, is being considered with further classification outlining the application area, modeling approach and the specific peculiarities characterizing each area.FindingsThe review revealed that maintenance and sustainability modeling is an emerging area of research that has intensified in the last few years. This fertile area can be developed further in several directions. In particular, there is room for devising models that are implementable, based on reliable and timely data with proven tangible practical results. While the environmental aspect has been considered, there is a clear scarcity of works addressing the social dimension. One of the identified barriers to developing applicable models is the lack of the required, accurate and timely data.Originality/valueThis work contributes to the maintenance and sustainability modeling research area, provides insights not previously addressed and highlights several avenues for future research. To the best of the authors' knowledge, this is the first review that looks at the integration of sustainability issues in maintenance modeling and optimization.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41590590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-21DOI: 10.1108/jqme-06-2021-0051
M. Kans, Anders Ingwald
PurposeThe purpose is to describe new business opportunities within the Swedish railway industry and to support the development of business models that corresponds with the needs and requirements of Industry 4.0, here denoted as Service Management 4.0.Design/methodology/approachThe study is an in-depth and descriptive case study of the Swedish railway system with specific focus on a railway vehicle maintainer. Public reports, statistics, internal documents, interviews and dialogues forms the basis for the empirical findings.FindingsThe article describes the complex business environment of the deregulated Swedish railway industry. Main findings are in the form of identified business opportunities and new business model propositions for one of the key actors, a vehicle maintainer.Originality/valueThe article provides valuable understanding of business strategy development within complex business environments and how maintenance related business models could be developed for reaching Service Management 4.0.
{"title":"Service-based business models in the Swedish railway industry","authors":"M. Kans, Anders Ingwald","doi":"10.1108/jqme-06-2021-0051","DOIUrl":"https://doi.org/10.1108/jqme-06-2021-0051","url":null,"abstract":"PurposeThe purpose is to describe new business opportunities within the Swedish railway industry and to support the development of business models that corresponds with the needs and requirements of Industry 4.0, here denoted as Service Management 4.0.Design/methodology/approachThe study is an in-depth and descriptive case study of the Swedish railway system with specific focus on a railway vehicle maintainer. Public reports, statistics, internal documents, interviews and dialogues forms the basis for the empirical findings.FindingsThe article describes the complex business environment of the deregulated Swedish railway industry. Main findings are in the form of identified business opportunities and new business model propositions for one of the key actors, a vehicle maintainer.Originality/valueThe article provides valuable understanding of business strategy development within complex business environments and how maintenance related business models could be developed for reaching Service Management 4.0.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42496648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-17DOI: 10.1108/jqme-12-2019-0118
Farouq Alhourani, Jean C. Essila, Bernie Farkas
PurposeThe purpose of this paper is to develop an efficient and effective preventive maintenance (PM) plan that considers machines’ maintenance needs in addition to their reliability factor.Design/methodology/approachSimilarity coefficient method in group technology (GT) philosophy is used. Machines’ reliability factor is considered to develop virtual machine cells based on their need for maintenance according to the type of failures they encounter.FindingsUsing similarity coefficient method in GT philosophy for PM planning results in grouping machines based on their common failures and maintenance needs. Using machines' reliability factor makes the plan more efficient since machines will be maintained at the same time intervals and when their maintenance is due. This helps to schedule a standard and efficient maintenance process where maintenance material, tools and labor are scheduled accordingly.Practical implicationsThe proposed procedure will assist maintenance managers in developing an efficient and effective PM plans. These maintenance plans provide better inventory management for the maintenance materials and tools needed using the developed virtual machine cells.Originality/valueThis paper presents a new procedure to implement PM using the similarity coefficient method in GT. A new similarity coefficient equation that considers machines reliability is developed. Also a clustering algorithm that calculates the similarity between machine groups and form virtual machine cells is developed. A numerical example adopted from the literature is solved to demonstrate the proposed heuristic method.
{"title":"Preventive maintenance planning considering machines’ reliability using group technology","authors":"Farouq Alhourani, Jean C. Essila, Bernie Farkas","doi":"10.1108/jqme-12-2019-0118","DOIUrl":"https://doi.org/10.1108/jqme-12-2019-0118","url":null,"abstract":"PurposeThe purpose of this paper is to develop an efficient and effective preventive maintenance (PM) plan that considers machines’ maintenance needs in addition to their reliability factor.Design/methodology/approachSimilarity coefficient method in group technology (GT) philosophy is used. Machines’ reliability factor is considered to develop virtual machine cells based on their need for maintenance according to the type of failures they encounter.FindingsUsing similarity coefficient method in GT philosophy for PM planning results in grouping machines based on their common failures and maintenance needs. Using machines' reliability factor makes the plan more efficient since machines will be maintained at the same time intervals and when their maintenance is due. This helps to schedule a standard and efficient maintenance process where maintenance material, tools and labor are scheduled accordingly.Practical implicationsThe proposed procedure will assist maintenance managers in developing an efficient and effective PM plans. These maintenance plans provide better inventory management for the maintenance materials and tools needed using the developed virtual machine cells.Originality/valueThis paper presents a new procedure to implement PM using the similarity coefficient method in GT. A new similarity coefficient equation that considers machines reliability is developed. Also a clustering algorithm that calculates the similarity between machine groups and form virtual machine cells is developed. A numerical example adopted from the literature is solved to demonstrate the proposed heuristic method.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42460845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-16DOI: 10.1108/jqme-11-2020-0118
Sudhir Chaurey, S. D. Kalpande, R.C. Gupta, L. K. Toke
PurposeThe purpose of this paper is to carry out the literature search on manufacturing organizations and total productive maintenance (TPM). This research aims at studying TPM attributes and barriers in line with the TPM framework for effective implementation of TPM. This study identifies the barriers in TPM implementation and the critical success factors (CSFs) for effective TPM implementation.Design/methodology/approachIn this manuscript, the study of TPM in the manufacturing sector has been considered a broad area of the research and emphasis on the TPM literature review, which primarily relates to the contribution of manufacturing sector and employment availability. Next sections covers TPM history, importance, justification, pillars, obstacles and TPM implementation procedure and models. Thereafter author identified the gaps in existing literature.FindingsThe existing literature shows that very few TPM implementation models are available for the manufacturing sector. The study also found that there is no systematically conducted large-scale empirical research which deals with TPM implementation. In order to bridge this gap, an investigation into the successful implementation of TPM in is truly needed. The finding of the literature shows that there is a need of TPM model specially developed for the manufacturing sector. The identified critical factors derived from the extensive literature review help to overcome the barriers for effective TPM implementation.Research limitations/implicationsThis review study is limited to Indian manufacturing industries. The identified TPM CSFs are based on the TPM pillars and their sub-factors. This cross-sectional study was based on the existing TPM model.Practical implicationsThis paper can increase the significance of TPM strategy, which could help managers of organizations to have a better understanding of the benefits of implementing TPM and therefore enable patient satisfaction within their organizations.Originality/valueThe literature review covers methodical identification of TPM barriers and critical factors for maintenance performance improvements. It allows the practitioners to apply these identified CSFs for TPM implementation to achieve an improvement in industrial performance and competitiveness.
{"title":"A review on the identification of total productive maintenance critical success factors for effective implementation in the manufacturing sector","authors":"Sudhir Chaurey, S. D. Kalpande, R.C. Gupta, L. K. Toke","doi":"10.1108/jqme-11-2020-0118","DOIUrl":"https://doi.org/10.1108/jqme-11-2020-0118","url":null,"abstract":"PurposeThe purpose of this paper is to carry out the literature search on manufacturing organizations and total productive maintenance (TPM). This research aims at studying TPM attributes and barriers in line with the TPM framework for effective implementation of TPM. This study identifies the barriers in TPM implementation and the critical success factors (CSFs) for effective TPM implementation.Design/methodology/approachIn this manuscript, the study of TPM in the manufacturing sector has been considered a broad area of the research and emphasis on the TPM literature review, which primarily relates to the contribution of manufacturing sector and employment availability. Next sections covers TPM history, importance, justification, pillars, obstacles and TPM implementation procedure and models. Thereafter author identified the gaps in existing literature.FindingsThe existing literature shows that very few TPM implementation models are available for the manufacturing sector. The study also found that there is no systematically conducted large-scale empirical research which deals with TPM implementation. In order to bridge this gap, an investigation into the successful implementation of TPM in is truly needed. The finding of the literature shows that there is a need of TPM model specially developed for the manufacturing sector. The identified critical factors derived from the extensive literature review help to overcome the barriers for effective TPM implementation.Research limitations/implicationsThis review study is limited to Indian manufacturing industries. The identified TPM CSFs are based on the TPM pillars and their sub-factors. This cross-sectional study was based on the existing TPM model.Practical implicationsThis paper can increase the significance of TPM strategy, which could help managers of organizations to have a better understanding of the benefits of implementing TPM and therefore enable patient satisfaction within their organizations.Originality/valueThe literature review covers methodical identification of TPM barriers and critical factors for maintenance performance improvements. It allows the practitioners to apply these identified CSFs for TPM implementation to achieve an improvement in industrial performance and competitiveness.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44843104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1108/jqme-05-2021-0038
M. Suresh, R. Dharunanand
PurposeThis paper intends to discover, analyze and construct a model that may be used to measure the interactions between major factors which are identified by expert opinion and literature review for sustainable maintenance specific to manufacturing industries using the total interpretive structural modeling (TISM) approach.Design/methodology/approachIn total, 12 factors were acknowledged from the literature review and the opinions of experts from manufacturing industries. Scheduled interviews with the employees were conducted by using the questionnaire which is developed from the identified 12 factors in order to find the interrelationships among these factors. The TISM approach is used for analyzing factors' interrelationships. The Matrice d'Impacts Croises Multiplication Appliques a un Classement (MICMAC) approach is used to identify the key factors which influence sustainable maintenance.FindingsThis paper found 12 factors that have ascendancy over the sustainable maintenance practices in the industry by reviewing the literature and consulting industry experts to realize the linkage between the factors. The results found that availability rate, adopting government policies, training and education are key factors that influence sustainable maintenance.Practical implicationsThe proposed model would be valuable for experts to understand the factors influencing sustainable maintenance in the industry. This model can be used by an organization's maintenance managers to implement sustainable maintenance practices in their plants.Originality/valueThis study analyzes the interrelationship between factors influencing sustainable maintenance in manufacturing industries, which is a new effort in this domain of practice.
{"title":"Factors influencing sustainable maintenance in manufacturing industries","authors":"M. Suresh, R. Dharunanand","doi":"10.1108/jqme-05-2021-0038","DOIUrl":"https://doi.org/10.1108/jqme-05-2021-0038","url":null,"abstract":"PurposeThis paper intends to discover, analyze and construct a model that may be used to measure the interactions between major factors which are identified by expert opinion and literature review for sustainable maintenance specific to manufacturing industries using the total interpretive structural modeling (TISM) approach.Design/methodology/approachIn total, 12 factors were acknowledged from the literature review and the opinions of experts from manufacturing industries. Scheduled interviews with the employees were conducted by using the questionnaire which is developed from the identified 12 factors in order to find the interrelationships among these factors. The TISM approach is used for analyzing factors' interrelationships. The Matrice d'Impacts Croises Multiplication Appliques a un Classement (MICMAC) approach is used to identify the key factors which influence sustainable maintenance.FindingsThis paper found 12 factors that have ascendancy over the sustainable maintenance practices in the industry by reviewing the literature and consulting industry experts to realize the linkage between the factors. The results found that availability rate, adopting government policies, training and education are key factors that influence sustainable maintenance.Practical implicationsThe proposed model would be valuable for experts to understand the factors influencing sustainable maintenance in the industry. This model can be used by an organization's maintenance managers to implement sustainable maintenance practices in their plants.Originality/valueThis study analyzes the interrelationship between factors influencing sustainable maintenance in manufacturing industries, which is a new effort in this domain of practice.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42037195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-30DOI: 10.1108/jqme-03-2021-0022
Mohamed Attia, J. Sinha
PurposeThe purpose of this paper is to analyze the reliability of the quantitative risk model used for planning inspection and maintenance activities. The objective is to critically discuss the factors that contribute to the probability and consequence of failure calculations.Design/methodology/approachThe case study conducted using one of the most widely deployed risk models in the oil and gas industry where a full assessment was performed on an offshore gas producing platform.FindingsThe generic failure frequencies used as the basis for calculating the probability of failure are set at a value representative of the refining and petrochemical industry's failure data. This failure database does not cover offshore. The critical discussion indicated the lack of basis of the coefficient of variances, prior probabilities and conditional probabilities. Moreover, the risk model does not address the distribution of thickness measurements, corrosion rates and inspection effectiveness, whereas only overall deterministic values are used; this requires judgment to determine these values. Probabilities of ignition, probabilities of delayed ignition and other probabilities in Level 1 event tree are found selected based on expert judgment for each of the reference fluids and release types (i.e. continuous or instantaneous). These probabilities are constant and independent of the release rate or mass and lack of constructed model. Defining the release type is critical in the consequence of the failure methodology, whereas the calculated consequences differ greatly depending on the type of release, i.e. continuous or instantaneous. The assessment results show that both criteria of defining the type of release, i.e. continuous or instantaneous, do not affect the calculations of flammable consequences when the auto-ignition likely is zero at the storage temperature. While, the difference in the resulted toxic consequence was more than 31 times between the two criteria of defining the type of release.Research limitations/implicationsThere is a need to revamp this quantitative risk model to minimize the subjectivity in the risk calculation and to address the unique design features of offshore platforms.Originality/valueThis case study critically discuss the risk model being widely applied in the O&G industry and demonstrates to the end-users the subjectivity in the risk results. Hence, be vigilant when establishing the risk tolerance/target for the purpose of inspection and maintenance planning.
{"title":"Reliability of quantitative risk analysis through an industrial case study","authors":"Mohamed Attia, J. Sinha","doi":"10.1108/jqme-03-2021-0022","DOIUrl":"https://doi.org/10.1108/jqme-03-2021-0022","url":null,"abstract":"PurposeThe purpose of this paper is to analyze the reliability of the quantitative risk model used for planning inspection and maintenance activities. The objective is to critically discuss the factors that contribute to the probability and consequence of failure calculations.Design/methodology/approachThe case study conducted using one of the most widely deployed risk models in the oil and gas industry where a full assessment was performed on an offshore gas producing platform.FindingsThe generic failure frequencies used as the basis for calculating the probability of failure are set at a value representative of the refining and petrochemical industry's failure data. This failure database does not cover offshore. The critical discussion indicated the lack of basis of the coefficient of variances, prior probabilities and conditional probabilities. Moreover, the risk model does not address the distribution of thickness measurements, corrosion rates and inspection effectiveness, whereas only overall deterministic values are used; this requires judgment to determine these values. Probabilities of ignition, probabilities of delayed ignition and other probabilities in Level 1 event tree are found selected based on expert judgment for each of the reference fluids and release types (i.e. continuous or instantaneous). These probabilities are constant and independent of the release rate or mass and lack of constructed model. Defining the release type is critical in the consequence of the failure methodology, whereas the calculated consequences differ greatly depending on the type of release, i.e. continuous or instantaneous. The assessment results show that both criteria of defining the type of release, i.e. continuous or instantaneous, do not affect the calculations of flammable consequences when the auto-ignition likely is zero at the storage temperature. While, the difference in the resulted toxic consequence was more than 31 times between the two criteria of defining the type of release.Research limitations/implicationsThere is a need to revamp this quantitative risk model to minimize the subjectivity in the risk calculation and to address the unique design features of offshore platforms.Originality/valueThis case study critically discuss the risk model being widely applied in the O&G industry and demonstrates to the end-users the subjectivity in the risk results. Hence, be vigilant when establishing the risk tolerance/target for the purpose of inspection and maintenance planning.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46432934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-23DOI: 10.1108/jqme-05-2021-0035
A. Al-Refaie, Hiba Almowas
PurposeThis research developed and examined a mathematical model for concurrent corrective and preventive maintenance policy of a system of series configuration.Design/methodology/approachA mathematical model was developed to maximize availability, and maximal net revenues, and minimal cost. Different probability distributions for time to failure and time to repair were considered. The model was then implemented on a real case study, which was studied under corrective maintenance policy and concurrent corrective and preventive policy.FindingsA comparison between results at current policy (90 days) and optimal period of corrective and preventive policy was conducted. It was found that availability, profit was increased from 94.4% and $20.091 – 96.5% and $24.803, respectively. Further, the cost was reduced from $1104.8 to $797.22.Research limitations/implicationsThe proposed optimization model can be adopted in planning maintenance activities for a single machine as well as for a system of series configuration machines under various probability distributions.Practical implicationsThe proposed model can significantly enhance performance of the production as well as maintenance systems. In addition, the developed model may support maintenance engineering in effective management of maintenance resources and the performance of its activities.Originality/valueThis research considers a mathematical model with multi-objective functions and distinct probability distributions for time-to-failure for a system of series machines. Moreover, appropriate approximation solution was deployed to find integral of some functions. Finally, it provides maintenance planning for a single machine or a series of machines.
{"title":"Multi-objective maintenance planning under preventive maintenance","authors":"A. Al-Refaie, Hiba Almowas","doi":"10.1108/jqme-05-2021-0035","DOIUrl":"https://doi.org/10.1108/jqme-05-2021-0035","url":null,"abstract":"PurposeThis research developed and examined a mathematical model for concurrent corrective and preventive maintenance policy of a system of series configuration.Design/methodology/approachA mathematical model was developed to maximize availability, and maximal net revenues, and minimal cost. Different probability distributions for time to failure and time to repair were considered. The model was then implemented on a real case study, which was studied under corrective maintenance policy and concurrent corrective and preventive policy.FindingsA comparison between results at current policy (90 days) and optimal period of corrective and preventive policy was conducted. It was found that availability, profit was increased from 94.4% and $20.091 – 96.5% and $24.803, respectively. Further, the cost was reduced from $1104.8 to $797.22.Research limitations/implicationsThe proposed optimization model can be adopted in planning maintenance activities for a single machine as well as for a system of series configuration machines under various probability distributions.Practical implicationsThe proposed model can significantly enhance performance of the production as well as maintenance systems. In addition, the developed model may support maintenance engineering in effective management of maintenance resources and the performance of its activities.Originality/valueThis research considers a mathematical model with multi-objective functions and distinct probability distributions for time-to-failure for a system of series machines. Moreover, appropriate approximation solution was deployed to find integral of some functions. Finally, it provides maintenance planning for a single machine or a series of machines.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46593776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1108/jqme-04-2021-0028
Nilesh Pancholi, Hiren Gajera, Darshit R. Shah
PurposeThe purpose of this paper is to explore the possibilities of improving the quality of existing maintenance task of the atomizer of milk powder manufacturing unit of a dairy plant. Looking to the past business volume and expected growth, the milk powder manufacturing unit forms a noticeable sector of processing plant. The lack of quality in maintenance standards leads to reliability losses of about 20–25% with low productivity and profit. Such facts and challenges of keeping the system in ready-state motivate a definite maintenance plan to be modeled based on a live failure analysis to be executed during shutdown or scheduled period.Design/methodology/approachThe deliverables are achieved by collecting the historical failure data i.e. downtime and failure frequencies; from January 2020 to July 2020 at Dudhsagar dairy, Gujarat, India. Reliability modeling is done in a view to understand the failure pattern behavior of the milk powder manufacturing unit. The atomizer is discriminated as a critical component based on these data and their functional failures, failure causes, effects and repercussions of failures with existing control and maintenance practices has been modeled based on live shop-floor study. Scores are assigned on 1 to 10 levels by analyzing attributes effects from lowest to highest concern respectively for every modes of failure through realistic brain-storming among maintenance team by incorporating some advanced attributes like maintainability, economic safety, economic cost and spares with basic criteria in this study. The maintainability criticality index (MCI) is narrated by these score values through multi-attribute decision-making (MADM) based failure analysis models like Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).FindingsThe primary findings of this research work are to propose improvements in the quality of the maintenance plan of critical component like; atomizer of a milk powder manufacturing unit which is commonly representing critical component in a major range of industrial processes. The case study recommended four silent maintenance strategies i.e. scheduled maintenance scheduled discard, scheduled failure finding and redesign as a qualified maintenance plan for the atomizer based on MCI and rankings of its potential failure causes. The results are helpful in upgrading quality standards for the maintenance activities of a process industry of alike or of dissimilar kinds in accordance with the failure analysis.Originality/valueOriginality mainly consists of investigating the scope of enhancing the existing maintenance practices through actual failure analysis with the help of TOPSIS. The criteria employed in this study are probability of chances of failure, degree of detectability and degree of severity as basic criteria along with some advanced criteria like; maintainability, spare parts, economic cost, economic safety are selected based on the outcome of shop-floor study and reli
目的探讨提高某乳品厂奶粉生产装置雾化器现有维修任务质量的可能性。从过去的业务量和预期增长来看，奶粉生产单位是加工厂中一个引人注目的部门。维修标准缺乏质量导致可靠性损失约20-25%，生产率和利润低。这些保持系统处于就绪状态的事实和挑战，促使我们根据停机或计划期间执行的实时故障分析，制定明确的维护计划。设计/方法/途径通过收集历史故障数据(即停机时间和故障频率)来实现可交付成果;2020年1月至2020年7月，在印度古吉拉特邦的Dudhsagar奶牛场。建立了可靠性模型，以了解奶粉生产单元的失效模式行为。基于这些数据，雾化器被区分为一个关键部件，它们的功能故障、故障原因、影响和故障的影响都是基于现场车间研究的现有控制和维护实践建模的。通过实际的维护团队头脑风暴，将可维护性、经济安全性、经济成本、备件等高级属性与本研究的基本标准结合，从关注度最低到关注度最高，对每种故障模式分别进行属性效应分析，并给出1 - 10个等级的评分。通过基于多属性决策(MADM)的故障分析模型，如TOPSIS (technical for Order of Preference by Similarity to Ideal Solution)，将可维护性临界指数(MCI)表示为这些评分值。本研究工作的主要发现是提出了关键部件维修计划质量的改进方案，如;奶粉生产单位的雾化器，通常代表主要工业过程中的关键部件。案例研究推荐了四种无声维护策略，即定期维护，定期丢弃，定期故障发现和重新设计，作为基于MCI及其潜在故障原因排名的合格维护计划。研究结果有助于根据故障分析提高过程工业类似或不同类型维修活动的质量标准。原创性/价值原创性主要包括在TOPSIS的帮助下，通过实际故障分析，调查现有维修实践的改进范围。本研究采用的标准是失败的机会概率、可检测程度和严重程度作为基本标准，以及一些高级标准，如;根据车间研究结果和可靠性建模，选择可维护性、备件、经济成本、经济安全性。记录了奶粉生产单位过去的显著故障统计数据(停机时间，故障频率)，并根据可靠性对这些数据进行分析，以提取一个说明性组件，即雾化器。
{"title":"Improving quality of maintenance task for milk powder manufacturing unit through TOPSIS","authors":"Nilesh Pancholi, Hiren Gajera, Darshit R. Shah","doi":"10.1108/jqme-04-2021-0028","DOIUrl":"https://doi.org/10.1108/jqme-04-2021-0028","url":null,"abstract":"PurposeThe purpose of this paper is to explore the possibilities of improving the quality of existing maintenance task of the atomizer of milk powder manufacturing unit of a dairy plant. Looking to the past business volume and expected growth, the milk powder manufacturing unit forms a noticeable sector of processing plant. The lack of quality in maintenance standards leads to reliability losses of about 20–25% with low productivity and profit. Such facts and challenges of keeping the system in ready-state motivate a definite maintenance plan to be modeled based on a live failure analysis to be executed during shutdown or scheduled period.Design/methodology/approachThe deliverables are achieved by collecting the historical failure data i.e. downtime and failure frequencies; from January 2020 to July 2020 at Dudhsagar dairy, Gujarat, India. Reliability modeling is done in a view to understand the failure pattern behavior of the milk powder manufacturing unit. The atomizer is discriminated as a critical component based on these data and their functional failures, failure causes, effects and repercussions of failures with existing control and maintenance practices has been modeled based on live shop-floor study. Scores are assigned on 1 to 10 levels by analyzing attributes effects from lowest to highest concern respectively for every modes of failure through realistic brain-storming among maintenance team by incorporating some advanced attributes like maintainability, economic safety, economic cost and spares with basic criteria in this study. The maintainability criticality index (MCI) is narrated by these score values through multi-attribute decision-making (MADM) based failure analysis models like Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).FindingsThe primary findings of this research work are to propose improvements in the quality of the maintenance plan of critical component like; atomizer of a milk powder manufacturing unit which is commonly representing critical component in a major range of industrial processes. The case study recommended four silent maintenance strategies i.e. scheduled maintenance scheduled discard, scheduled failure finding and redesign as a qualified maintenance plan for the atomizer based on MCI and rankings of its potential failure causes. The results are helpful in upgrading quality standards for the maintenance activities of a process industry of alike or of dissimilar kinds in accordance with the failure analysis.Originality/valueOriginality mainly consists of investigating the scope of enhancing the existing maintenance practices through actual failure analysis with the help of TOPSIS. The criteria employed in this study are probability of chances of failure, degree of detectability and degree of severity as basic criteria along with some advanced criteria like; maintainability, spare parts, economic cost, economic safety are selected based on the outcome of shop-floor study and reli","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47308823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1108/jqme-12-2020-0121
Eduardo Vaz, José Carlos Vieira De Sá, Gilberto Santos, Florbela Correia, P. Ávila
PurposeThe purpose of this paper is to assess the impact of a maintenance philosophy, Total Productive Maintenance (TPM), on the operational performance of the Portuguese industry, identifying how it enables the systematic reduction of waste in maintenance.Design/methodology/approachA structured questionnaire was constructed and sent to 472 Portuguese enterprises, having obtained a sample constituted of 84 valid answers. With a five-point Likert scale, it was possible to assess the impact of the TPM on five operational performance dimensions, being them: quality, flexibility, productivity, safety and costs.FindingsIt was found that the planned maintenance, together with education and training are the practices with the highest degree of implementation in the Portuguese industry, exceeding 70% for both. The productivity is the dimension with a higher degree of impact from the implementation of TPM and costs the dimension that suffered a lesser impact.Practical implicationsThis paper shows and analyses the current state of TPM implementation in the Portuguese industry and it will be useful for maintenance professionals, researchers and others concerned with maintenance, in order to understand the effects of TPM implementation on the operational performance of the Portuguese industries.Originality/valueThe findings from this paper will be valuable for professionals who desire and are looking forward to implement an effective maintenance approach in the maintenance management system, in order to achieve the excellence in maintenance.
{"title":"The value of TPM for Portuguese companies","authors":"Eduardo Vaz, José Carlos Vieira De Sá, Gilberto Santos, Florbela Correia, P. Ávila","doi":"10.1108/jqme-12-2020-0121","DOIUrl":"https://doi.org/10.1108/jqme-12-2020-0121","url":null,"abstract":"PurposeThe purpose of this paper is to assess the impact of a maintenance philosophy, Total Productive Maintenance (TPM), on the operational performance of the Portuguese industry, identifying how it enables the systematic reduction of waste in maintenance.Design/methodology/approachA structured questionnaire was constructed and sent to 472 Portuguese enterprises, having obtained a sample constituted of 84 valid answers. With a five-point Likert scale, it was possible to assess the impact of the TPM on five operational performance dimensions, being them: quality, flexibility, productivity, safety and costs.FindingsIt was found that the planned maintenance, together with education and training are the practices with the highest degree of implementation in the Portuguese industry, exceeding 70% for both. The productivity is the dimension with a higher degree of impact from the implementation of TPM and costs the dimension that suffered a lesser impact.Practical implicationsThis paper shows and analyses the current state of TPM implementation in the Portuguese industry and it will be useful for maintenance professionals, researchers and others concerned with maintenance, in order to understand the effects of TPM implementation on the operational performance of the Portuguese industries.Originality/valueThe findings from this paper will be valuable for professionals who desire and are looking forward to implement an effective maintenance approach in the maintenance management system, in order to achieve the excellence in maintenance.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46675103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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