To Support Iot Collaborative Expressiveness on the Shop Floor

Abstract

The availability of new research for IoT support and the human-centric perspective of industry 4.0 opens a gap to support operators in unleashing their creativity so they can provide improvements opportunities with IoT technology. This paper presents a case-study carried out in four Swedish manufacturing companies, where four different workshops were facilitated to support operators in the conceptualization of manufacturing improvements with IoT technologies. The empirical material gathered during these workshops has been analyzed in five different reflective sessions and discussed in light of previous research from industry 4.0, operators, and IoT support. Results indicate that operators can collaboratively create conceptual IoT solutions and that expressiveness in communicating their ideas and needs using IoT technology is more relevant than technical aspects and details of their proposed IoT solutions. This technological expressiveness is identified as a necessary skill to be cultivated on the shop floor and can potentially contribute to making a more effective and socially sustainable industrial landscape in the future.

Development of cloud visualization a machining manufacturing system shop floor

“…Data processing involves a series of operations performed to extract knowledge from the extensive data sets. The transformation of data into information and knowledge is essential for manufacturers to make informed and rational decisions [25], [26].…”

Co-Designing with AI in Sight

“…This pilot study is a follow-up consequence of a case study that started in 2017 called "Karakuri IoT". The case study aimed to democratise the adoption of the Internet of things (IoT) in industrial settings through a bottom-up approach, by supporting factory workers' expressiveness in the conceptualisation of IoT improvement solutions (Aranda-Muñoz et al, 2021). In the last stages of Karakuri IoT, we identified a lack of methods and tools that involve factory workers for the purpose of using the potential data generated from their IoT proof of concept ideas to find other suitable AI improvements in factories.…”