Computational Model for Knowledge Transfer Skills in Industry 4.0 in an Enhanced and Effective Way

Abstract

The current swift pace of development is a reality that is crossing many domains in society demanding specific measures to cope with such scale of development. In the new paradigm of Industry 4.0, new competences and professional skills are needed in the most diverse quadrants of society. The importance of adequately adapt the societal systems and to promote the adequate skills is worth as much as the value we give to present and future generations. Among demanding challenges arising from this changing reality, the transfer of knowledge from academia to industry is probably the most demanding. This reality is present across diverse countries and continents and for that, pilot deployments and lessons learned should be documented and shared to promote better and effective skill development. In this context, the SHYFTE project is establishing a computational model for knowledge transfer skills in industry 4.0.

A Systematic Review of Industry 4.0 Technology on Workforce Employability and Skills: Driving Success Factors and Challenges in South Asia

“…Moreover, the findings suggest strategies for adopting new skills in developing countries, especially in South Asia. Creating a learning environment, industry-academic collaboration, infrastructure development, sharing and transferring of knowledge internally and externally, and reforming education with enhanced training curricula can help in making skilled and efficient workforces (Artifice et al 2019;Sallati et al 2019). Based on the analyses and syntheses of the systematic review, the authors propose a framework (Figure 10), "Industry 4.0 SEI Framework", that depicts the driving factors, challenges, and required skills for the future labor market.…”