Industrial maintenance decision-making: A systematic literature review

Ruschel, Edson; Santos, Eduardo Alves Portela; Loures, Eduardo de Freitas Rocha

doi:10.1016/j.jmsy.2017.09.003

Cited by 137 publications

(73 citation statements)

References 155 publications

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“…This research shall be based on a Systematic Literature Review, or SLR. Thus, the sections and the review methodology shall be designed according to the SLR method, as highlighted in [66][67][68][69][70]. In conducting this research, requirements such as thoroughness and depth were deemed as important to this research.…”

Section: Review Methodologymentioning

confidence: 99%

“…The SLR has been proposed as a detailed type of research which takes into consideration the broad foundation [16], as well as being transparent, explanatory, heuristic [67], context-sensitive, and able to achieve evidence-informed reviews and decisions [66]. Thus, the need for an SLR in the review of data-driven circular approaches in manufacturing for digital technologies is predicated on the view that SLR can help this research identify research trends, future work in the area, and the tools used in solving the problems being addressed [68]. Figure 2 on the next page describes the systematic literature review phases.…”

Section: Review Methodologymentioning

confidence: 99%

“…These keywords and search arguments are developed from the scoping study of the research, and the literature is consulted and finally agreed upon by the research team. As corroborated in [68], it is an iterative process that requires protocol refinement for approval. This is shown in Figure 4.…”

Section: Review Methodologymentioning

confidence: 99%

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Digitisation and the Circular Economy: A Review of Current Research and Future Trends

et al. 2018

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Since it first appeared in literature in the early nineties, the Circular Economy (CE) has grown in significance amongst academic, policymaking, and industry groups. The latest developments in the CE field have included the interrogation of CE as a paradigm, and its relationship with sustainability and other concepts, including iterative definitions. Research has also identified a significant opportunity to apply circular approaches to our rapidly changing industrial system, including manufacturing processes and Industry 4.0 (I4.0) which, with data, is enabling the latest advances in digital technologies (DT). Research which fuses these two areas has not been extensively explored. This is the first paper to provide a synergistic and integrative CE-DT framework which offers directions for policymakers and guidance for future research through a review of the integrated fields of CE and I4.0. To achieve this, a Systematic Literature Review (SLR; n = 174) of the empirical literature related to digital technologies, I4.0, and circular approaches is conducted. The SLR is based on peer-reviewed articles published between 2000 and early 2018. This paper also summarizes the current trends in CE research related to manufacturing. The findings confirm that while CE research has been on the increase, research on digital technologies to enable a CE is still relatively untouched. While the “interdisciplinarity” of CE research is well-known, the findings reveal that a substantial percentage is engineering-focused. The paper concludes by proposing a synergistic and integrative CE-DT framework for future research developed from the gaps in the current research landscape.

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Section: Review Methodologymentioning

confidence: 99%

Section: Review Methodologymentioning

confidence: 99%

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Digitisation and the Circular Economy: A Review of Current Research and Future Trends

et al. 2018

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“…In manufacturing, industrial production managers are responsible for continuously detecting and responding to problems in operational control, while also improving production by deciding how equipment, personnel, and planning are combined (Lim, 2014;Ruschel et al, 2017;Sánchez-Márquez et al, 2018) -increasing efficiency is a constant process of finding inefficiencies demanding intelligent action. Operational control in manufacturing offers several paradigmatic cases from equipment, personnel, and planning; typically, system components interact in non-obvious ways and frequently, only a subset of the whole system can be optimized (Pawlak, 2016;Lawrence, 1995).…”

Section: Introductionmentioning

confidence: 99%

Decision Support Visualization Approach in Textile Manufacturing a Case Study From Operational Control in Textile Industry

Varela¹,

Amaral²,

Pereira³

et al. 2019

IJQR

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Decision support visualization tools provide insights for solving problems by displaying data in an interactive, graphical format. Such tools can be effective for supporting decision-makers in finding new opportunities and in measuring decision outcomes. In this study, was used a visualization tool capable of handling multivariate time series for studying a problem of operational control in a textile manufacturing plant; the main goal was to identify sources of inefficiency in the daily production data of three machines. A concise rule-based model of the inefficiency measures (i.e. quantitative measures were transformed into categorical variables) was developed and then performed an in-depth visual analysis using a particular technique, the categorical time series plots stacked vertically. With this approach were identified a wide array of production inefficiency patterns, which were difficult to identify using standard quantitative reporting -temporal pattern of best and worst performing machines -and critically, along with most important sources of inefficiency and some interactions between them were revealed. The case study underlying this work was further contextualized within the state of the art, and demonstrates the effectiveness of adequate visual analysis as a decision support tool for operational control in manufacturing.

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“…The authors propose a replacement policy to maximize reliability in a mission-based system. On the basis of the same concepts,Poór et al (2014) 186 consider the key role of machine and plant maintenance in terms of facility management (FM) for manufacturing companies.As affirmed by ViswanathDhanisetty et al (2018), the existing literature shows a wide variety of examples making use of MCDM methods as supporting tools to manage maintenance decision making processes Ruschel et al (2017). lead a systematic review focused on the vast amount of decision-making models adopted in the literature and aimed at enhancing the following areas: maintenance management, maintenance planning, maintenance policy selection, maintenance efficiency analysis, equipment lifecycle management, process monitoring analysis, machine health prognosis, reliability analysis, system and component degradation, maintenance outsourcing, joint optimization, multi-level system integration, multi-state system optimization, risk and consequence analysis, maintenance cost estimation, and inspection and maintenance intervals.…”

mentioning

confidence: 99%

Multi-criteria decision methods to support the maintenance management of complex systems

Carpitella¹

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A thesis under a co-tutelle agreement between UNIPA and UPV within their respective programmes of doctorates in "PROF. ALFREDO PERIS (UPV) THE TUTORS PROF. ANTONELLA CERTA (UNIPA) PROF. JULIO BENÍTEZ (UPV) PROF. JOAQUÍN IZQUIERDO (UPV)To my father, my mother and Nino The rock upon which I stand ACKNOWLEDGMENTS Three years ago I undertook a long and difficult, but beautiful journey, called a double PhD. It has been so challenging and undoubtedly the most important personal achievement of my whole life so far. I compared myself with something I thought was much bigger than me. Actually, in order to accomplish it successfully, I just needed to fully involve my heart. I did it without saving my strengths. What I have learnt during my doctorate will remain with me forever. Not only did I further develop my professional skills and my attitude to scientific research, but above all I made real my passion for discovery. Discovering the world, meeting new people, appreciating diversity, considering various manners of working and living, learning new languages, facing my weaknesses and getting over them. All of the things listed above unquestionably influenced my personal development. And personal growth is an endless process. It goes without saying that this doctoral thesis is the result of all my efforts and love. I dedicate it… To my father and my mother, the most important people in my life. I wish I could be even half as good person and engineer as they are. All that I am I owe to my parents. To my brother Nino, who is for me the best example of courage and who has had right answers to my doubts since we were just children. To my grandma Wilma, a great woman to whom I owe most of my personality. To all my family, especially to my grandparents Maria and Mario, and to my cousins/sisters Paola, Luisa and Carla. To Antonella and Joaquín, my "academic parents" and continuous sources of inspiration, who have transmitted me all their passion for this incredible job and taken care of my personal and professional growth in every possible way. They made my horizon larger and pushed me to continuously challenge myself. I consider them as a true family, more life-mentors rather than professors, and I will be always aware of the fundamental part they play in my life. To Julio, who has been indispensable to carry out this thesis and carefully followed all the stages of its development, with endless competence and kindness. It has been a true privilege to work with such a source of knowledge as Julio is. To Professor Giacomo Galante, who first believed in me when I was an undergraduate student and, after having supervised my master thesis, introduced me to the University world. To Professor Mario Enea, who kindly and fully supported me during the whole duration of my doctorate studies. To Manu and Idel, who treat me as I was their little sister, giving me a lot of attention and dedicating a lot of their priceless time (days, weeks, months) to teach me loads of things. They guided me across unforgettable and thought-provoking internat...

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Industrial maintenance decision-making: A systematic literature review

Cited by 137 publications

References 155 publications

Digitisation and the Circular Economy: A Review of Current Research and Future Trends

Digitisation and the Circular Economy: A Review of Current Research and Future Trends

Decision Support Visualization Approach in Textile Manufacturing a Case Study From Operational Control in Textile Industry

Multi-criteria decision methods to support the maintenance management of complex systems

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