Year: 2025
Type: article
Abstract: Data plays a fundamental role in shopfloor management in order to make better decisions and increase efficiency throughout the production system. The idea of data-oriented shopfloor management has been discussed in the literature as an innovative concept, but unlike traditional or digital shopfloor management, it has not been conceptualised from a holistic perspective. For this reason, this paper used qualitative research in the form of expert interviews to collect holistic conceptual requirements for data-oriented shopfloor management. The data were analysed using the Gioia Methodology and transferred into a data structure to derive conceptual requirements at different levels of aggregation. On the basis of the empirical data, data-oriented shopfloor management was modelled, consisting of the system elements shopfloor, management approach with four subsystems and information system. Specifically, two conceptual models were developed for data-oriented shopfloor management as a distinction was made between episodic configuration and strategic adaptation and the persistent operating mode. Both conceptual models represent the reciprocal relationships and interdependencies of the system elements within data-oriented shopfloor management. Looking to the future, this paper provides the basis for further research to refine the conceptual models based on the empirically collected conceptual requirements with a higher level of detail.
Authors: Patrick Eichenseer, Herwig Winkler
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,990
OpenAlex ID: W4409833442