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Assessment of the impact of maintenance integration within a plant using MFD: A case study
Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.ORCID iD: 0000-0001-5320-1154
Linnaeus University, Faculty of Technology, Department of Mechanical Engineering.ORCID iD: 0000-0001-8205-8289
Linnaeus University, Faculty of Technology, Department of Mechanical Engineering. Linnaeus University, Faculty of Technology, Department of Physics and Electrical Engineering.ORCID iD: 0000-0003-0161-6168
2019 (English)In: Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies: Proceedings of the 12th World Congress on Engineering Asset Management and the 13th International Conference on Vibration Engineering and Technology of Machinery / [ed] Joseph MathewC.W. LimLin MaDon SandsMichael E. CholettePietro Borghesani, Springer, 2019, p. 61-71Conference paper, Published paper (Refereed)
Abstract [en]

In the recent decades the recognition of maintenance as an effective part of the company competitiveness has grown. In order to enhance maintenance performance and its positive impact, integration with the rest of the plant activities should be planned and performed. In this study, Maintenance Function Deployment model was applied on a real data of a case company. The model was used to analyse the company’s production with respect to the business and economic variables. This was done first through finding loss causes of the strategic goals of the case company, then breaking down these causes and their costs into their root causes. Based on economic estimations, the results show that the major root causes behind losses are insufficient training of personnel and lack of maintenance integration. It is concluded that properly considering the integration of maintenance within the company’s activities, reduces loss and improves the company’s performance. Also, that applying MFD eases the identification of the root-causes behind losses as well as quantifying and prioritizing the economic losses. © Springer Nature Switzerland AG 2019.

Place, publisher, year, edition, pages
Springer, 2019. p. 61-71
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Other Mechanical Engineering
Research subject
Technology (byts ev till Engineering), Terotechnology
Identifiers
URN: urn:nbn:se:lnu:diva-82728DOI: 10.1007/978-3-319-95711-1_7Scopus ID: 2-s2.0-85056649730ISBN: 978-3-319-95710-4 (print)ISBN: 978-3-319-95711-1 (print)OAI: oai:DiVA.org:lnu-82728DiVA, id: diva2:1318334
Conference
12th World Congress on Engineering Asset Management (WCEAM, Brisbane, 2 – 4 August 2017
Note

Export Date: 22 May 2019; Book Chapter

Available from: 2019-05-27 Created: 2019-05-27 Last updated: 2024-08-28Bibliographically approved
In thesis
1. On the development of a new digitalised maintenance approach for factories of the future
Open this publication in new window or tab >>On the development of a new digitalised maintenance approach for factories of the future
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over time, maintenance methods have developed following the dynamic manufacturers’ demands. Now, with the coming industrial revolution, new maintenance approaches have to be developed to fulfil the new demands of future industry, as well as to allow companies to benefit from technological advances. Therefore, the research question of this study is: how to develop a maintenance approach for factories of the future? To answer this question, this thesis proposes tools to identify and prioritise maintenance related problems that impact company’s profitability. It explores designing and implementation of a digitalised maintenance approach for future factories. Furthermore, it investigates tools and methods to collect data efficiently by sensors.

The results achieved in this thesis are 1) a mathematical representation and application of a model that identifies and prioritises causes of deficiencies in production processes, 2) a model that identifies and prioritises failures that impact the competitive advantages and profitability of companies, 3) characterisation of a maintenance approach for future factories, 4) frameworks that could be utilised to develop a maintenance approach for future factories, as well as, guidelines that help to design this approach, 5) guidelines for the integration of digitalised maintenance with the database of other working areas, 6) an algorithm for adaptive sampling for sensors, as well as, a proposal for a generic software architecture to facilitate designing, modelling and implementation of adaptive sampling algorithms.

The conclusion of this thesis confirms previous findings that maintenance has an impact on companies’ competitive advantages, other working areas and profitability. To design and implement a maintenance system, its elements should be extracted from the primary objective of maintenance. These elements should be then allocated in a suitable architecture and their mechanism should also be defined. Prior to implementation and integration, mapping the concept design to production problems can be used to examine its performance. An approach to collect data efficiently by sensors is to use adaptive sampling. The developed adaptive algorithm and the reference software framework for adaptive sampling algorithms could be used for this purpose.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2020. p. 83
Series
Linnaeus University Dissertations ; 393
Keywords
failure impact, digitalised maintenance, adaptive sampling
National Category
Reliability and Maintenance
Research subject
Technology (byts ev till Engineering), Terotechnology
Identifiers
urn:nbn:se:lnu:diva-98467 (URN)978-91-89081-94-9 (ISBN)978-91-89081-95-6 (ISBN)
Public defence
2020-11-04, Newton, Växjö, 09:15 (English)
Opponent
Supervisors
Available from: 2020-10-16 Created: 2020-10-14 Last updated: 2025-02-24Bibliographically approved

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Algabroun, HatemAl-Najjar, BasimIngwald, Anders

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