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Smart manufacturing and tasks automation in the steel industry: Reflecting on routine work and skills in Industry 4.0

Author

Listed:
  • Luca Antonazzo

    (Centre for Workplace Research (CWER), Prague University of Economics and Business, Czechia)

  • Dean Stroud
  • Martin Weinel

    (School of Social Sciences, Cardiff University, UK)

Abstract

This article presents the findings of research on the European steel industry as it transitions toward Industry 4.0. Drawing on data generated through semi-structured interviews, the authors reflect on the distinction between routine and non-routine work which has informed much recent research on technology effects on jobs. First, they propose to distinguish between ‘deterministic’ and ‘probabilistic’ technological approaches, the latter illustrative of the Industry 4.0 model and characterised by the use of algorithms and statistical learning. Next, the authors maintain that jobs that have been labelled as ‘routine’ may entail a range of tasks that Industry 4.0 technologies remain unable to entirely automatise, which has led to broadening skillsets and a prominence acquired by transversal skills. Hence, the authors suggest overcoming the routine/non-routine dichotomy and deterministic assumptions on workers’ substitution in favour of a continuum-based conceptualisation of tasks and a more nuanced investigation of technology effects.

Suggested Citation

  • Luca Antonazzo & Dean Stroud & Martin Weinel, 2024. "Smart manufacturing and tasks automation in the steel industry: Reflecting on routine work and skills in Industry 4.0," Economic and Industrial Democracy, Department of Economic History, Uppsala University, Sweden, vol. 45(3), pages 914-936, August.
    • Handle: RePEc:sae:ecoind:v:45:y:2024:i:3:p:914-936
    DOI: 10.1177/0143831X231201002
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