Firefly Optimization Analysis of Steel Manufacturing Plant under the Approach of RPGT

Abstract

This study presents a reliability and cost‑based optimization framework for a steel manufacturing plant. It consists of four subsystems: "Grinding Machine," "Descaling Machine," "Hot Steckel Mill," and "Cutting Machine." A grinding machine is frequently utilized. If this machine malfunctions, it might lead to a serious system failure. Thus, we use a standby unit equipped with a grinding machine and a descaling machine that consists of two parallel machines operating simultaneously. This subsystem can operate with a single machine at a lower capacity. The failure in the hot steel mill and cutting machine leads to the complete breakdown of the system. The study's goal is to maximize manufacturing plant production by enhancing system dependability through better management, control, and maintenance. The analysis focuses on four key performance measures: Mean Time to System Failure (MTSF), steady‑state availability, busy period, and the expected number of server visits under the approach of RPGT. A Markov-based simulation system model has been developed for performance analysis and solved using the firefly algorithm (FA) to improve the outcomes. The main tenets of this approach are as follows: subsystem repair and failure rates vary; repaired units function as reliably as new ones over a certain length of time; repair and failure rates operate independently; and a single repair facility meets all demands. These simplifications make it possible to analyze system performance and dependability in a targeted manner. In order to maximize industrial advantages and maximize dependability, the optimal values of all parameters based on the exponential distribution are taken into consideration. To examine the findings and make inferences about the behavior of the system, tabular and graphical analyses are provided. The work that is being presented aims to provide the most favorable operating condition for the steel manufacturing plant, balancing high reliability, low maintenance burden, and maximum long‑run profit.