Abstract
Manufacturing process design and implementation can benefit from the adaptation of Digital Twins. However, the explanatory power coming by physics models presents a strong contradiction with the demand of rapid decision making required for their control and optimization. In the context of laser welding applications, this work investigates three physics-based modelling methods (namely direct Stefan method, apparent heat capacity method and Enthalpy method) along with sensorial data towards the formation of a knowledge database in order to aid the development of a Digital Twin. Also, the methodology for creating such a Digital Twin is discussed incorporating the best result(s) and method(s). This Digital Twin is proved useful in optimizing the process itself but also monitoring, through selection of sensors.
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