Modeling of Steel Production Sub-Processes by Probabilistic Time Automaton and Assessing the Risk of Deviation from Stability in the Manufacturing Facility Environment

Abstract

In the steelmaking industry in recent years, requirements such as mixed production of various types of products and short delivery times have led to a demand for efficient operation methods that allow for efficient production while tolerating the risk of disruptions to stable operations. However, the steelmaking process is a complex supply chain, and even a localized change in one element can cause the entire system to fail.

In this study, we model the steelmaking sub-process using Uppaal SMC, a statistical model checking tool, and analyze evaluation of operational rules and the effects of uncertain events and the place pre- and post- each process through simulation and statistical analysis. The modeling of the steelmaking sub-process consists of five processes (Cold rolling, Continuous Annealing, Inspection, Temper rolling, and storage) and their pre- and post-process storages. The model also includes upper and reprocessing processes that carry works to and from the sub-processes, and other processes where works are carried out of the sub-processes.

Using the model, we conducted simulations and statistical analyses of evaluation of operational rules and the effects of uncertain events on the entire process, including the pre-and post-process yards, equipment failure probabilities, and quality inspection pass rates. Through some numerical simulation results, the effectiveness and the potential, e.g. for clarifying the effect of the operational rules, of the proposed model are investigated.