Enhancing Digital Twins of Semi-Automatic Production Lines by Digitizing Operator Skills
Source abstract
Abstract
In recent years, Industry 4.0 has provided many tools to replicate, monitor, and control physical systems. The purpose is to connect production assets to build cyber-physical systems that ensure the safety, quality, and efficiency of production processes. Particularly, the concept of digital twins has been introduced to create the virtual representation of physical systems where both elements are connected to exchange information. This general definition encompasses a series of major challenges for the developers of those functionalities. Among them is how to introduce the human perspective into the virtual replica. Therefore, this paper presents an approach for incorporating human factors in digital twins. This approach introduces a methodology to offer suggestions about employee rotations based on their previous performance during a shift. Afterward, this method is integrated into a digital twin to perform human performance assessments to manage workers’ jobs. Furthermore, the presented approach is mainly comprised of a human skills modelling engine and a human scheduling engine. Finally, for demonstrating the approach, a simulated serial single-product manufacturing assembly line has been introduced.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Transformation in Industry · Flexible and Reconfigurable Manufacturing Systems · Assembly Line Balancing Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
FAST-Lab, Faculty of Engineering and Natural Sciences, Tampere University, 33720 Tampere, Finland
Funding
European Union’s Horizon 2020 research and innovation program
References (53)
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