Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Domain Specific Assets: A Software Platform for Use Case Driven Human Friendly Factory Interaction

Version 1 : Received: 9 April 2020 / Approved: 10 April 2020 / Online: 10 April 2020 (07:46:10 CEST)

How to cite: Brandt, F.; Brandt, E.; Ghofrani, J.; Heik, D.; Reichelt, D. Domain Specific Assets: A Software Platform for Use Case Driven Human Friendly Factory Interaction. Preprints 2020, 2020040167. https://doi.org/10.20944/preprints202004.0167.v1 Brandt, F.; Brandt, E.; Ghofrani, J.; Heik, D.; Reichelt, D. Domain Specific Assets: A Software Platform for Use Case Driven Human Friendly Factory Interaction. Preprints 2020, 2020040167. https://doi.org/10.20944/preprints202004.0167.v1

Abstract

In current efforts to digitize manufacturing and move it into the fourth stage of the industrial revolution, a wide range of integration solutions is being considered to enable manufacturing to adapt to change. In transforming a factory into a self-organized, autonomous factory, companies are currently struggling with rapidly changing requirements and production factors, among other things. This is a particular problem for the human being as an actor within the factory, as the amount of new technologies and protocols increases the training effort. Proprietary interfaces of the control providers, a wide range of different communication protocols, complicate the understanding of the production processes, the evaluation and testability of new use cases and increase the danger of creating silos of knowledge as well as building collaboration barriers. As a solution to these problems, we propose an open software platform and define a way to model use case driven domain specific asset representation (DSA) that focuses on the human being and his needs for representing the factory in a way that it meets his requirements for the current production needs. We therefore conducted research on google scholar on human factors in industry 4.0 and used technologies as well as already existing platforms and their architecture.

Keywords

cyber physical systems; industry 4.0; human machine interaction; sustainable production

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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