Preliminary study of knowledge transfer aspect in the creation of a framework for education and training of digital manufacturing technologies

Abstract

Abstract Digitalization is changing the industry. As this change accelerates its speed, it also requires a transformation process where knowledge transfer between industry and research institutes play a significant role. There is a need to be more fluent, flexible, and efficient in order to get the latest research results into industrial implementation as quickly as possible. The challenge in knowledge transfer is that its speed in the current stage is too slow compared to the speed of development and changes required by digitalization of traditional manufacturing industries. The motivation for this study is the gap in knowledge transfer. One emerging digital transformation is the establishment of modern digital manufacturing technologies, e.g., additive manufacturing (AM). There are different approaches to supporting the industry in this transformation. Knowledge transfer can happen, for example, through education (e.g., master students) and industrial training, but also the fluent transfer of the latest research results from research institutes to companies is needed. University education needs to support the requirements of the manufacturing industry by providing future experts with skills to smooth the transformation process and bring novel technology applications, such as AM, to industrial-scale use. The article discusses how university education can support future competence-building in the industry. Similar needs are also present in industrial training, which universities often provide. Both education and training need to be improved from fundamental approaches to explain how this new knowledge should be created, i.e., how knowledge transfer happens most efficiently. The outcome of this article is the basis of the framework for education and training of digital manufacturing technologies by using modern learning methods and tools. More detailed pedagogical and knowledge transfer models can be developed and applied when this framework is created.