Decision Experiments in the Learning Factory: A Proof of Concept

Abstract

There are plenty of human-centred research questions in production science. So far, the focus of the analysis is skewed towards technical considerations. Decision experiments, however, provide a promising approach to gain insights from a human perspective by using learning factories as field-in-the lab environments. This article reports operative insights and qualitative results from a decision experiment in the learning factory. Participants assemble electronic servo motor components and are paid according to their productivity. The adjustment to the learning factory as a lab environment and modifications to production stations in the learning factory that allow for a rigorous data collection are described. Furthermore, as a proof of concept, this article states how
the setup was perceived by four participants that were sampled and interviewed in a technical pilot. Overall, participants stated a high level of satisfaction and engagement with the task and were not distracted by noise. Since other activities naturally take place in learning factories during experimental sessions, participants were asked about whether they felt observed by bystanders, which was confirmed to some extent. This article discusses remedies to these effects for future experiments. Finally, a list of essential questionnaire items that should be contained in decision experiments in learning factories in general is presented. Using these insights, decision experiments in learning factories can push the envelope in human-centred production science.

Keywords: Industry 4.0, Human-Centred Production Systems, Behavioural and Experimental Economics, Experimental Pilot