https://www.mdu.se/

mdh.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Perspectives on Smart Maintenance Technologies – A Case Study in Large Manufacturing Companies
Mälardalens universitet, Akademin för innovation, design och teknik, Innovation och produktrealisering. Mälardalen Industrial Technology Center AB, Sweden.ORCID-id: 0000-0002-4543-0069
Mälardalens universitet, Akademin för innovation, design och teknik, Innovation och produktrealisering.ORCID-id: 0000-0002-7494-1474
Mälardalens universitet, Akademin för innovation, design och teknik, Innovation och produktrealisering. Volvo Construction Equipment, Sweden.ORCID-id: 0000-0002-0729-0122
2022 (engelsk)Inngår i: Advances in Transdisciplinary Engineering / [ed] Amos H.C. Ng, Anna Syberfeldt, Dan Högberg, Magnus Holm, IOS Press, 2022, Vol. 21, s. 255-266Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The manufacturing industry faces significant technical challenges due to the industry 4.0 technologies, which play an essential role in maintenance development. Maintenance in industry 4.0, also named smart maintenance, maintenance 4.0, predictive maintenance, etc., is boosted using industry 4.0 technologies, such as Industrial Internet of Things (IIoT), Big Data and Analytics, Cloud Computing, Augmented Reality (AR), Additive Manufacturing (AM), etc. Previous research presents several smart maintenance technologies, but the manufacturing industry still finds it challenging to implement the technologies cost-effectively. One problem is that there is insufficient research on how smart maintenance technologies can be implemented cost-effectively and add value to the manufacturing industry. Therefore, this paper aims to explore perspectives on smart maintenance technologies: 1) if there are any implemented smart maintenance technologies, 2) in what context, 3) added values, 4) challenges, 5) opportunities, 6) advantages, and 7) disadvantages with the technologies. This paper presents the results of a case study based on an online open questionnaire with respondents working in maintenance organizations in large manufacturing companies. 

sted, utgiver, år, opplag, sider
IOS Press, 2022. Vol. 21, s. 255-266
Emneord [en]
Smart Maintenance, Maintenance 4.0, Predictive Maintenance, Industry 4.0
HSV kategori
Forskningsprogram
innovation och design
Identifikatorer
URN: urn:nbn:se:mdh:diva-58298DOI: 10.3233/ATDE220145Scopus ID: 2-s2.0-85132808966ISBN: 978-1-64368-268-6 (tryckt)ISBN: 978-1-64368-269-3 (digital)OAI: oai:DiVA.org:mdh-58298DiVA, id: diva2:1661137
Konferanse
SPS2022, Proceedings of the 10th Swedish Production Symposium, Skövde, Sweden, 26-29 April 2022
Tilgjengelig fra: 2022-05-25 Laget: 2022-05-25 Sist oppdatert: 2023-11-13bibliografisk kontrollert
Inngår i avhandling
1. Smart Maintenance Technologies in the Manufacturing Industry: Implementation, Challenges, Enablers and Benefits
Åpne denne publikasjonen i ny fane eller vindu >>Smart Maintenance Technologies in the Manufacturing Industry: Implementation, Challenges, Enablers and Benefits
2023 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

In Industry 4.0, production, Information Technology (IT), and the Internet are combined. The nine technologies of Industry 4.0, Artificial Intelligence (AI) and Cyber-Physical System (CPS), are changing machines, strategies, processes, and maintenance.

In the first generation of maintenance, machines were run to failure, which is related to Corrective Maintenance. Systems for planning and control were implemented in the second generation, related to Predetermined Maintenance. Condition Based Maintenance (CBM) was presented in the third maintenance generation. Industry 4.0 places new demands on maintenance and different maintenance approaches are presented in previous research, such as Maintenance 4.0, Smart Maintenance and Self-Maintenance. This research focuses on smart maintenance technologies, using the nine technologies of Industry 4.0, such as Industrial Internet of Things (IIoT), and Big Data and Analytics, for machine connection, maintenance data collection, analysis of data, and making decisions using AI. CPS can be used to integrate the physical world, such as manufacturing machines, factory environment, material, people, and executions, with the cyber world, such as data analysis, apps, services, and decision-making.

Previous research presents several approaches to smart maintenance technologies. One problem is a lack of research regarding how smart maintenance technologies can be implemented to add benefits to the maintenance organization in line with company’s goal. Furthermore, previous research presents that further research is needed to support the manufacturing industry in what step an organization should take to implement smart maintenance technologies. In this research, four studies have been performed, which include literature reviews to obtain a clear overview of the research area of smart maintenance, as well as collected empirical data. The empirical data is collected from large companies and Small and Medium-sized Enterprises (SMEs), within the manufacturing industry, to obtain a clear overview of the manufacturing industry’ situation. The studies show that the manufacturing industry faces several challenges when implementing smart maintenance technologies, despite the concept of Industry 4.0 has been discussed for more than ten years. In this research, a conceptual implementation process is proposed, including challenges and enablers to consider when implementing smart maintenance technologies, as well as benefits of using smart maintenance technologies.

sted, utgiver, år, opplag, sider
Eskilstuna: Mälardalens universitet, 2023. s. 75
Serie
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 350
HSV kategori
Forskningsprogram
industriella system
Identifikatorer
urn:nbn:se:mdh:diva-64731 (URN)978-91-7485-622-4 (ISBN)
Presentation
2023-12-15, Mälardalen Industrial Technology Center, John Engellaus Gata 1, Eskilstuna, 09:00 (svensk)
Opponent
Veileder
Tilgjengelig fra: 2023-11-14 Laget: 2023-11-13 Sist oppdatert: 2023-11-24bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Person

Giliyana, SanSalonen, AnttiBengtsson, Marcus

Søk i DiVA

Av forfatter/redaktør
Giliyana, SanSalonen, AnttiBengtsson, Marcus
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 390 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf