Toward a Sawmill Digital Shadow Based on Coupled Simulation and Supervised Learning Models

Digital Twins (DT) have been introduced as promising decision support tools in many different settings and serve a variety of purposes. Many challenges are raised by their development, including an efficient usage computational resources to balance performance on precision, cost speed. This study is, particular, concerned with Shadows (DS), concept derived from DT, applied sawmills sawing production units. A method combine computationally intensive sawmill simulation model machine learning is proposed predict the set lumbers sawed logs. Numeric experiments exposed, demonstrates improvements 11% 18% monitored couple regret its baseline.