Multiple-Criteria Fuzzy Optimization of the Heat Treatment Processes for Two Steel Rolled Products

This paper presents a developed method for fuzzy multiple-criteria optimization of the rolled-steel heat treatment processes in the modern metallurgical plant. At the first stage of the study, by means of passive industrial experiments or a mathematical simulation of heat transfer processes, and using statistical methods, the regression dependencies of the output parameters of process quality on the input variables that are technological parameters are established. Then, based on the quality parameters, membership functions are formed that represent local criteria of the process quality, and their ranks are calculated using the matrix of pairwise comparisons. The practically useful methodology of the fuzzy multiple-criteria optimization of technological processes is proposed. To illustrate this methodology's practical efficiency, the solutions of two optimization problems are found by maximizing the global criterion that aggregates local criteria using their ranks. It is shown that the efficiency of the obtained optimal heat treatment modes significantly exceeds the efficiency of the technology used earlier in the plant.

Automated summary

This paper introduces a method for fuzzy multiple-criteria optimization of rolled-steel heat treatment processes, establishing regression dependencies between quality outputs and technological input parameters using statistical methods. Local criteria membership functions are formed based on quality parameters, and a practical methodology for optimizing technological processes is proposed. The efficiency of the optimal heat treatment modes obtained significantly exceeds that of earlier technologies used in the plant.