System dynamics modelling and learning factories for manufacturing systems education
Carla Susana A. Assuad, Nina Tvenge, Kristian Martinsen
Abstract
Manufacturing systems are complex socio-technical systems with non-linearities, accumulation, flows and delays that challenge decision-making processes. System Dynamics (SD) is a valuable approach to analyse and understand complex interlinkages. This paper discusses how SD can be applied to learning factories (LF) at manufacturing education for enhanced learning outcome. LF are physical, full scale high-fidelity simulators for manufacturing education, where students act as operators and train on interaction with humans, machines, software and technology. Using simulations both virtual and full-scale add value in learning outcomes. By using SD, learners can play “what-if” analysis to understand the effects of their decisions.