Evaluating Thermal Feedback for Automated Digital Shadow Generation
pathway with real-time sensing of control parameters and material conditions is central to enabling
Industry 4.0. The concept of digital twins is the third in a series of automated data integration levels,
indicating fully automatic feed-forward data transfer from digital space to real space as well as
automatic feedback from physical sensors to a digital simulation in real time. Here, we begin to evaluate
how to use surface temperature as determined by infrared thermal camera as part of a useful feedback
loop to predict the internal temperature gradients during open-die forging trials of commonly forged
materials. The work is driven by the broader question of: “What technology is required to create a fully
automated digital twin for use in metals deformation processing?”
The current state of the art within industry is a digital shadow, a digital object created with automatic
input from sensors on the physical object. The data from sensors is usually sparse, noisy, and indirect,
and can be challenging to directly feed into models . In addition, deformation models can take minutes
to solve simple problems or hours to resolve complex ones, while real processes occur in seconds. Given
this, there is a clear need to down-select inputs into digital simulations that have the most physical
significance and influence on our ability to resolve a simulation satisfactorily.
An evaluation of the significance of thermal process parameters encountered for a range of forging
conditions and the degree to which they can be measured and controlled for was performed. This
yielded insight into the potential use of thermal control feedback loops for automating the creation of
digital deformation simulations.