Abstract
Workforce wellbeing is of strategic importance in new economy, not only for enterprises but for SMEs as well. Fatigue is one of key factors which affect workforce wellbeing, particularly in risk-sensitive environments such as manufacturing. Despite that importance of fatigue is identified in literature, this aspect is not much leveraged in existing solutions aiming high levels of effectiveness by optimal operation planning and scheduling. In this paper, a solution aiming optimal fatigue-aware planning and scheduling in manufacturing based on semantic knowledge graphs is presented. Thanks to adoption of ontologies, our approach enables seamless integration of heterogeneous data sources including legacy ERP systems, external services as well as sensors such as IoT wearable devices. Complementing the planning and scheduling solution, two additional apps are developed: 1) mobile app for physiological data acquisition using wearable device for purpose of fatigue estimation 2) shopfloor monitoring web app with machine operation instructions incorporated.
Publisher
University of Belgrade, Technical Faculty in Bor