Concept for distributed robotics learning environment: Increasing the access to the robotics via modularisation of systems and mobility

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)
25 Downloads (Pure)


The ongoing digital transition affects manufacturing industry at all levels, from workers at a shop floor to machine systems, and from business models to future markets. Emerging technologies such as robotics, Internet of Things (IoT), Artificial intelligence (AI), and cyber-physical production systems (CPPS) capable of facilitating real-time processes, visibility and transparency of factory operations will speed up the change of manufacturing paradigms. The mass customization and personification is expected to increase further.The capability to address the requirements and needs of each individual customer will be a key differentiation and competitive factor. At the same time the workforce in Europe is diminishing, causing a miss-match between skills and needs from the industry. In manufacturing industry any skills are developed by experience, reflecting time on the labour market and age and skills taught in qualifications change. Qualifications which are prone to technological change are likely to reflect quite different embodied skills according to age cohort. In order to answer these challenges we have established a robotics fablab concept to support both formal and non-formal education offered to the younger students and industrial workforce alike. The concept utilises digital learning contents, a fablab operating philosophy and mobile factory concept, meaning that parts (e.g. robot cells) of the laboratory can be shipped to another location for a while to be used by learners. This paper will described the concept and preliminary findings from the applicability of the concept.

Original languageEnglish
Title of host publication10th Conference on Learning Factories, CLF2020
Number of pages6
Publication statusPublished - 2020
Publication typeA4 Article in conference proceedings
EventConference on Learning Factories - Graz, Austria
Duration: 15 Apr 202017 Apr 2020

Publication series

NameProcedia Manufacturing
ISSN (Print)2351-9789


ConferenceConference on Learning Factories


  • Automation
  • Education
  • Learning
  • Modular
  • Robotics

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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