Work-Based Learning in Smart Manufacturing: Current State and Future Perspectives

6 Pages Posted: 2 Jun 2021

See all articles by Steffen Nixdorf

Steffen Nixdorf

TU Wien - Institute of Management Science

Fazel Ansari

TU Wien - Institute of Management Science

Wilfried Sihn

TU Wien - Institute of Management Science

Date Written: June 2, 2021

Abstract

The ongoing digital transformation in manufacturing is raising the demand for skilling, re-skilling and upskilling of workforces. At the same time, it largely affects skill mismatches in socio-technical work systems. Industry 4.0’s enabling technologies, especially AI and collaborative robotics offer new ways of learning, which introduce innovative work-based learning (WBL) approaches. In this context, Learning Factories confront a challenge on how to cope with the pace of technological enhancement and increasing skill mismatches and competence gaps on the job market. This paper is to conduct a systematic and community-specific literature survey to elicit and cluster the current state of the art in WBL represented in the International Association of Learning Factories (IALF) over the past years. Of particular importance are articles i) emphasizing new ways of technology-enhanced WBL, and ii) examining research gaps regarding (reciprocal) learning among human and intelligent machines in collaborative work systems. Finally, the future pathways of research in WBL within and beyond IALF are identified.

Keywords: Work-Based Learning, Learning Factories, Competence Management, Industry 4.0

Suggested Citation

Nixdorf, Steffen and Ansari, Fazel and Sihn, Wilfried, Work-Based Learning in Smart Manufacturing: Current State and Future Perspectives (June 2, 2021). Proceedings of the Conference on Learning Factories (CLF) 2021, Available at SSRN: https://ssrn.com/abstract=3858379 or http://dx.doi.org/10.2139/ssrn.3858379

Steffen Nixdorf (Contact Author)

TU Wien - Institute of Management Science ( email )

Theresianumgasse 27
Vienna, 1040
Austria

Fazel Ansari

TU Wien - Institute of Management Science ( email )

Theresianumgasse 27
Vienna, 1040
Austria

Wilfried Sihn

TU Wien - Institute of Management Science ( email )

Theresianumgasse 27
Vienna, 1040
Austria

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