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Giliyana, S., Salonen, A. & Bengtsson, M. (2024). A Conceptual Implementation Process for Smart Maintenance Technologies. In: Engineering Asset Management Review: (pp. 61-84). Springer Science and Business Media Deutschland GmbH, 3
Open this publication in new window or tab >>A Conceptual Implementation Process for Smart Maintenance Technologies
2024 (English)In: Engineering Asset Management Review, Springer Science and Business Media Deutschland GmbH , 2024, Vol. 3, p. 61-84Chapter in book (Refereed)
Abstract [en]

Industry 4.0 is usually presented as usage of technologies. Some of these play an important role in the development of smart maintenance technologies. However, although the subject of smart maintenance has been discussed for more than 10 years, the manufacturing industry still finds it challenging to implement smart maintenance technologies to add benefits to maintenance organizations in line with company’s goals. This study presents a conceptual process for implementing smart maintenance technologies, challenges and enablers to consider when implementing, and benefits. This article is based on an analysis of empirical findings from seven large manufacturing companies in Sweden, previous maintenance research, and authors’ three previous smart maintenance research articles. In the first article, the authors explored perspectives on smart maintenance technologies from 11 large companies within the manufacturing industry, while in the second one, perspectives on smart maintenance technologies from 15 manufacturing Small and medium-sized enterprises (SMEs) were presented. In the third and final one, the authors developed and presented a testbed for smart maintenance technologies.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2024
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:mdh:diva-66248 (URN)10.1007/978-3-031-52391-5_3 (DOI)2-s2.0-85186405105 (Scopus ID)
Note

Book chapter; Export Date: 13 March 2024; Cited By: 0; Correspondence Address: S. Giliyana; Mälardalen University, Eskilstuna, Sweden; email: san.giliyana@mitc.se

Available from: 2024-03-13 Created: 2024-03-13 Last updated: 2024-03-13Bibliographically approved
Giliyana, S., Karlsson, J., Bengtsson, M., Salonen, A., Adoue, V. & Hedelind, M. (2024). A Testbed for Smart Maintenance Technologies. In: Lecture Notes in Mechanical Engineering: . Paper presented at 7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, 13 June 2023 through 15 June 2023 (pp. 437-450). Springer Science and Business Media Deutschland GmbH
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2024 (English)In: Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH , 2024, p. 437-450Conference paper, Published paper (Refereed)
Abstract [en]

Industry 4.0 presents nine technologies including Industrial Internet of Things (IIoT), Big Data and Analytics, Augmented Reality (AR), etc. Some of the technologies play an important role in the development of smart maintenance technologies. Previous research presents several technologies for smart maintenance. However, one problem is that the manufacturing industry still finds it challenging to implement smart maintenance technologies in a value-adding way. Open questionnaires and interviews have been used to collect information about the current needs of the manufacturing industry. Both the empirical findings of this paper, as well as previous research, show that knowledge is the most common challenge when implementing new technologies. Therefore, in this paper, we develop and present a testbed for how to approach smart maintenance technologies and to share technical knowledge to the manufacturing industry.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2024
Keywords
Knowledge, Smart maintenance technologies, Testbed, Augmented reality, Industry 4.0, Maintenance, 'current, Empirical findings, Maintenance technologies, Manufacturing industries, Smart maintenance technology, Testbeds
National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:mdh:diva-65365 (URN)10.1007/978-3-031-39619-9_32 (DOI)2-s2.0-85181978943 (Scopus ID)9783031396182 (ISBN)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, 13 June 2023 through 15 June 2023
Available from: 2024-01-17 Created: 2024-01-17 Last updated: 2024-01-17Bibliographically approved
Bengtsson, M., Pettersson, R., Giliyana, S. & Salonen, A. (2024). The Importance of Using Domain Knowledge When Designing and Implementing Data-Driven Decision Models for Maintenance: Insights from Industrial Cases. In: Lecture Notes in Mechanical Engineering: . Paper presented at 7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, 13 June 2023 through 15 June 2023 (pp. 601-614). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>The Importance of Using Domain Knowledge When Designing and Implementing Data-Driven Decision Models for Maintenance: Insights from Industrial Cases
2024 (English)In: Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH , 2024, p. 601-614Conference paper, Published paper (Refereed)
Abstract [en]

The advanced technologies available in the development of Smart Maintenance within Industry 4.0 have the potential to significantly improve the efficiency of industrial maintenance. However, it is important to be careful when deciding which technologies to implement for a given application and when evaluating the quality of the data generated. Otherwise, what should be cost-effective solutions may end up being cost-driving. The use of domain knowledge in selecting, developing, implementing, setting up, and utilizing these technologies is increasingly important for achieving success. In this paper, we will elaborate on this topic by presenting and analyzing insights from industrial cases, drawing on the authors’ extensive experience in the field.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2024
Keywords
Data-driven decisions, Domain knowledge, Industrial cases, Maintenance, Smart maintenance technologies, Cost effectiveness, Advanced technology, Cost-effective solutions, Data driven decision, Decision modeling, Industrial case, Industrial maintenance, IS costs, Maintenance technologies, Smart maintenance technology
National Category
Reliability and Maintenance
Identifiers
urn:nbn:se:mdh:diva-65367 (URN)10.1007/978-3-031-39619-9_44 (DOI)2-s2.0-85181979974 (Scopus ID)9783031396182 (ISBN)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, 13 June 2023 through 15 June 2023
Available from: 2024-01-17 Created: 2024-01-17 Last updated: 2024-01-17Bibliographically approved
Giliyana, S., Bengtsson, M. & Salonen, A. (2023). Perspectives on Smart Maintenance Technologies – A Case Study in Small and Medium-Sized Enterprises (SMEs) Within Manufacturing Industry. In: 16th WCEAM Proceedings: . Paper presented at 16th World Congress on Engineering Asset Management (WCEAM), Seville from 5–7 October 2022. (pp. 571-585). Springer Nature
Open this publication in new window or tab >>Perspectives on Smart Maintenance Technologies – A Case Study in Small and Medium-Sized Enterprises (SMEs) Within Manufacturing Industry
2023 (English)In: 16th WCEAM Proceedings, Springer Nature , 2023, p. 571-585Conference paper, Published paper (Refereed)
Abstract [en]

Industry 4.0 consists of nine technological pillars: IIoT, Cloud Computing, Big Data and Analytics, AR, etc. Some of the pillars play an essential role in maintenance development. Previous research presents many technologies for smart maintenance, but one prevailing problem is that there are still challenges to implementing smart maintenance technologies cost-effectively in the manufacturing industry. Therefore, we explore perspectives on smart maintenance technologies from respondents within 15 manufacturing SMEs. We start by investigating whether the companies had implemented smart maintenance technologies, if so, in what context. Then, we explore perspectives from the manufacturing SMEs on added values, challenges, opportunities, advantages, and disadvantages of smart maintenance technologies. However, as none of the case companies had implemented any Smart Maintenance Technologies, only implementation challenges could be investigated.

Place, publisher, year, edition, pages
Springer Nature, 2023
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Engineering and Technology Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:mdh:diva-62070 (URN)10.1007/978-3-031-25448-2_53 (DOI)2-s2.0-85151146920 (Scopus ID)978-3-031-25448-2 (ISBN)
Conference
16th World Congress on Engineering Asset Management (WCEAM), Seville from 5–7 October 2022.
Available from: 2023-03-14 Created: 2023-03-14 Last updated: 2023-11-13Bibliographically approved
Sannö, A., Giliyana, S., Lindhult, E. & Synnelius, E. (2022). Handbook for conducting thesis projects in co-production with industry (1ed.). Eskilstuna: Mälardalens universitet
Open this publication in new window or tab >>Handbook for conducting thesis projects in co-production with industry
2022 (English)Other (Other (popular science, discussion, etc.))
Abstract [en]

This handbook is developed for thesis students, as well as academic supervisors and industrial supervisors. The handbook aims to clarify the thesis process and make it easier for you to work as a team. By following this process, you will make sure that the thesis will have both academic and industrial contributions.

Place, publisher, year, pages
Eskilstuna: Mälardalens universitet, 2022 Edition: 1
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mdh:diva-57406 (URN)
Available from: 2022-02-14 Created: 2022-02-14 Last updated: 2022-02-15Bibliographically approved
Giliyana, S., Salonen, A. & Bengtsson, M. (2022). Perspectives on Smart Maintenance Technologies – A Case Study in Large Manufacturing Companies. In: Amos H.C. Ng, Anna Syberfeldt, Dan Högberg, Magnus Holm (Ed.), Advances in Transdisciplinary Engineering: . Paper presented at SPS2022, Proceedings of the 10th Swedish Production Symposium, Skövde, Sweden, 26-29 April 2022 (pp. 255-266). IOS Press, 21
Open this publication in new window or tab >>Perspectives on Smart Maintenance Technologies – A Case Study in Large Manufacturing Companies
2022 (English)In: Advances in Transdisciplinary Engineering / [ed] Amos H.C. Ng, Anna Syberfeldt, Dan Högberg, Magnus Holm, IOS Press, 2022, Vol. 21, p. 255-266Conference paper, Published paper (Refereed)
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. 

Place, publisher, year, edition, pages
IOS Press, 2022
Keywords
Smart Maintenance, Maintenance 4.0, Predictive Maintenance, Industry 4.0
National Category
Engineering and Technology
Research subject
Innovation and Design
Identifiers
urn:nbn:se:mdh:diva-58298 (URN)10.3233/ATDE220145 (DOI)2-s2.0-85132808966 (Scopus ID)978-1-64368-268-6 (ISBN)978-1-64368-269-3 (ISBN)
Conference
SPS2022, Proceedings of the 10th Swedish Production Symposium, Skövde, Sweden, 26-29 April 2022
Available from: 2022-05-25 Created: 2022-05-25 Last updated: 2023-11-13Bibliographically approved
Giliyana, S., Karlsson, J., Bengtsson, M., Salonen, A., Adoue, V. & Hedelind, M.A Testbed for Smart Maintenance Technologies.
Open this publication in new window or tab >>A Testbed for Smart Maintenance Technologies
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Industry 4.0 presents nine technologies including Industrial Internet of Things (IIoT), Big Data and Analytics, Augmented Reality (AR), etc. Some of the technologies play an important role in the development of smart maintenance technologies. Previous research presents several technologies for smart maintenance. However, one problem is that the manufacturing industry still finds it challenging to implement smart maintenance technologies in a value-adding way. Open questionnaires and interviews have been used to collect information about the current needs of the manufacturing industry. Both the empirical findings of this paper, as well as previous research, show that knowledge is the most common challenge when implementing new technologies. Therefore, in this paper, we develop and present a testbed for how to approach smart maintenance technologies and to share technical knowledge to the manufacturing industry.

Keywords
Smart Maintenance Technologies, Knowledge, Testbed
National Category
Engineering and Technology Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Systems
Identifiers
urn:nbn:se:mdh:diva-64729 (URN)
Available from: 2023-11-13 Created: 2023-11-13 Last updated: 2023-12-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-4543-0069

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