Model based optimisation of highly automated industrial batch annealing operation

Abstract Modern batch annealing operations are highly automated facilities, equipped with online sensors, model based control and a production management system to archive material, process and quality parameters. In these operations, efficient models and algorithms are used to allocate the resources, schedule the operation and design process cycles of individual stacks. The present work endeavours to enhance the productivity of a highly automated batch annealing facility, operating well above its rated capacity. This was achieved by intelligent analysis of production data and a critical assessment of the prevalent thermal model used for designing the process cycle of the individual stack. Two major limitations, namely, the inability to capture non-isothermal kinetics and the stiff radial conductivity model, of the prevalent thermal model were identified. These limitations were eliminated by designing process cycles with an integrated process model, where phase transformation kinetics is incorporated. Implementation of these process cycles has enhanced the productivity of the batch annealing operation by 7–9%. These benefits have been validated through rigorous laboratory experiments and plant trials.