EUROPEAN STEEL TECHNOLOGY AND APPLICATION DAYS 2017 - ESTAD 2017

Pickling lines are often considered as a bottleneck of steel production. Increasing the throughput has been the declared goal of many research projects. Yet, high quality pickling results depend on a complicated mixture of constraints like careful choice of pickling speed, suited entry temperature and a good estimate about how many scale resides on the strip surface. In this paper, a technique is shown that induces a self-optimization of the pickling line. Virtual coils, programmatic representation of the real products, store their production history, predict the amount of scale on the surface and propose an optimum pickling speed. Information from the surface inspection systems are introduced to effectively control the pickling process as such. The paper also shows how such a system works in a real-world production environment.