Data Driven Optimal Coil Batching for Annealing Lines with Eligibility Constraints

This study proposes a modeling and scheduling methodology to solve the optimization problem of base (an annealing facility) reflecting various field requirements. Our main intention is to achieve a virtual loading simulation and instruction automation. In order to increase the productivity in an annealing line, the process should be executed by loading as many coils as possible into the base. Nonetheless, when loading into the base, several characteristics of both coils and base, such as subdivided an annealing cycle as well as process time, and so on, must be taken into consideration. As a result, we expect to build big data by collecting on-site facility data of the annealing line based on real-time IoT technology and industry standard protocols.