Metal Production Technological Process Modeling Using A Probability Finite Automatic Machine

Abstract

The current trend indicates a significant rise in the popularity of fields such as system management and the development of automated control systems utilizing finite state machines, with a high degree of integration between these domains. Consequently, there is a demand for the development of decision-making systems and software for intellectual support within each area. In contemporary research and scientific endeavors, state machines—whether finite discrete or probabilistic automata—are the most commonly employed tools. However, these often fall short in creating efficient decision-making systems without incurring substantial labor costs. This study focuses on the development of a probabilistic finite state machine that can accurately predict the properties of alloys, thereby offering intelligent decision support during the manufacturing of metal products.