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Diagnostics of opportunities: A dialogue tool for addressing digital factory maturity
Volvo Construction Equipment; Karlstad University.
Jönköping University, Jönköping International Business School, JIBS, Business Administration. Jönköping University, Jönköping International Business School, JIBS, Media, Management and Transformation Centre (MMTC). Jönköping University, Jönköping International Business School, JIBS, Centre for Family Entrepreneurship and Ownership (CeFEO).ORCID iD: 0000-0003-2355-763x
Volvo Construction Equipment; Mälardalen University.
2024 (English)In: Advances in Transdisciplinary Engineering: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning, Amsterdam: IOS Press, 2024, Vol. 52, p. 395-406Conference paper, Published paper (Refereed)
Sustainable development
00. Sustainable Development, 9. Industry, innovation and infrastructure
Abstract [en]

For over 15 years, the concept of Industry 4.0, now transitioning into Industry 5.0, has been a focal point for the manufacturing sector. Yet, the success of companies in embracing digital transformation varies. There are numerous models and assessment tools for assessing digital readiness and maturity. Several models have been developed over the years, but firms also realize no “one-size-fits-all” exists when testing them. Previous studies show that firms must take charge of their own digital transformation (DT) journey to find a path that suits their specific needs.This qualitative paper is driven by a case study supported by a within-case analysis conducted with a heavy-machine industry with fourteen production plants worldwide – data collected from 2020 to 2023.Volvo Construction Equipment (Volvo CE), created Factory 4 Tomorrow (F4T) to address Industry 4.0. The central challenge for the F4T initiative was how to facilitate an inside-outside approach to identify an inclusive maturity model that emphasizes learning and collaboration. A diagnostic of opportunities model was created to aid the organisation’s transformation journey. It aimed to support all plants by evaluating their maturity in digital transformation, identifying gaps, and support in prioritising. Unlike traditional models that assess and compare plant levels, this model aimed to foster awareness and alignment, establishing a shared language. Thus, a unique model was explicitly crafted for the firm. The process of developing the model itself enhanced awareness and alignment. Therefore, this paper explores the development process - failures and successes - to compile a digital transformation maturity model tailor-made to a firm’s needs and goals. The objective is to offer comprehensive advice for firms to implement DT initiatives effectively in a way that suits them.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2024. Vol. 52, p. 395-406
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 52
Keywords [en]
Digitalisation, maturity, manufacturing, smart production
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:hj:diva-64000DOI: 10.3233/ATDE240183Scopus ID: 2-s2.0-85191353899ISBN: 978-1-64368-510-6 (print)ISBN: 978-1-64368-511-3 (electronic)OAI: oai:DiVA.org:hj-64000DiVA, id: diva2:1851532
Conference
11th Swedish Production Symposium, SPS2024 Trollhattan 23 April 2024 through 26 April 2024
Projects
SMART PM
Funder
VinnovaAvailable from: 2024-04-15 Created: 2024-04-15 Last updated: 2025-02-03Bibliographically approved

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Machado, Carla G.

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