Prepared for work in Industry 4.0? Modelling the target activity system and five dimensions of worker readiness

ABSTRACT

Within Industry 4.0 research, the spotlight shines on technological and organisational challenges. This study shifts the focus to worker readiness, beginning with an analysis of twenty-three models to establish the state of research. Findings demonstrate that existing models are mostly early-stage proposals addressing competences featured in mainstream 21^st-century and digital-competence frameworks. Worker-level factors explicitly aligned with emerging cyber-physical systems receive little attention. To construct a worker-readiness model calibrated to the needs of Industry 4.0, the authors devised a research procedure based on a two-phase integrative review of 135 publications. Firstly, they deployed an activity-system apparatus to produce a structured description of the target environment. Secondly, major worker competence groupings, aligned with this target, were extracted, tagged and reduced to five dimensions. The resulting model consolidates prior research and introduces two original competence groupings addressing human-machine partnering and decision-making in Industry 4.0. This study is a foundational step by the Educational Informatics Lab, Ontario Tech University, Canada, toward deploying a global online profile tool for generating, analysing and aggregating worker readiness profiles. This cross-disciplinary project will help researchers, educators, corporate trainers, human resource managers, policymakers, and systems designers more effectively diagnose the readiness of workers for Industry 4.0.

KEYWORDS:

• Industry 4.0
• work environment
• worker readiness
• worker competences
• readiness model
• digitalised work

Acknowledgments

The authors acknowledge the tremendous support and input of Christian Desjardins (ictin.us) during both the planning and execution stages of this project. In addition, the authors recognise the feedback of Dr Olena Mykhailenko (collaboritsi.com) during the writing and editing stages, and suggestions from EILAB-associated colleagues during the initial scoping phase. This project would not have been possible without the EILAB infrastructure (eilab.ca) at Ontario Tech University, Canada (ontariotechu.ca) and the seminal research contributions of its founding director Dr François Desjardins.

Dedication

We dedicate this study to the workers of General Motors automotive plants in Oshawa, Canada who, in the face of plant closures, are conquering the challenge of learning new skills as manufacturing transitions towards Industry 4.0.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Ontario Centres of Excellence (www.oce-ontario.org) and Punchtime (ictin.us), Voucher for Innovation and Productivity, Application [#30859].