Defining and assessing industry 4.0 maturity levels–case of the defence sector

Bibby, L and Dehe, B ORCID: https://orcid.org/0000-0002-3016-1871 (2018) Defining and assessing industry 4.0 maturity levels–case of the defence sector. Production Planning and Control, 29 (12). pp. 1030-1043. ISSN 0953-7287

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Official URL: https://www.tandfonline.com/doi/full/10.1080/09537...

Abstract

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Firms do not currently fully appreciate the complex characteristics of Industry 4.0 and as a result are uncertain about what it represents for them. In this study, an assessment model is developed to measure the level of implementation of Industry 4.0 technologies, around three dimensions: ‘Factory of the Future’, ‘People and Culture’, and ‘Strategy’. The ‘Factory of the Future’ is the main dimension and is composed of eight attributes: Additive Manufacturing, Cloud, Manufacturing Execution System, Internet of Things and Cyber Physical Systems, Big Data, Sensors, e-Value Chains, and Autonomous Robots. The study uses a defence manufacturing firm to develop, test and validate the model and report on 12 partners. We concluded that the focal firm has an Industry 4.0 maturity level of 59.35, above the sector average of 55.58. This research contributes by empirically developing a model and providing an analysis of major firms in the Defence supply network.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	05 Jun 2019 15:14
Publisher:	Taylor & Francis
Additional Information:	This is the Author Accepted Manuscript of an article in Production Planning and Control published by Taylor & Francis.
Divisions:	Faculties > Business and Law
Subject terms:	Science & Technology, Technology, Engineering, Industrial, Engineering, Manufacturing, Operations Research & Management Science, Engineering, Industry 4, 0, maturity assessment, defence sector, MANUFACTURING EXECUTION SYSTEM, CYBER-PHYSICAL SYSTEMS, OF-THE-ART, BIG DATA, MODELS, MANAGEMENT, FRAMEWORK, INTERNET, THINGS, FUTURE, MD Multidisciplinary, Operations Research
URI:	https://e-space.mmu.ac.uk/id/eprint/623069
DOI:	https://doi.org/10.1080/09537287.2018.1503355
ISSN	0953-7287
e-ISSN	1366-5871

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