Abstract
In the Industry 4.0 era, advanced analytical tools are essential for progressing with digital transformation, especially within complex socio-technical systems. However, the growing complexity of these systems in manufacturing impedes system improvement, and traditional analytical methods focusing solely on the technological aspect often fall short. To overcome this problem, this paper introduces an integrated methodology combining Discrete-Event Simulation, Functional Resonance Analysis Method, and Work Domain Analysis for analysing and enhancing manufacturing systems by considering factors like operator skill levels, demand changes, and production constraints. Implemented in two industrial case studies, this methodology effectively identifies system limitations and aids in structured data analysis, positioning it as a vital decision support system in the digital transformation of Industry 4.0.
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