Mehdi Heydari

Iran University of Science and Technology

Papers

Total Citations

H-Index

About

Mehdi Heydari’s research focuses on the optimization and modeling of robotic manufacturing cells, with a particular emphasis on part sequencing, robot motion cycles, and output rate analysis. His work bridges discrete-event modeling and metaheuristic optimization to improve efficiency in flexible manufacturing environments. Heydari’s most cited contributions include developing a Petri net model for part sequencing and robot moves in two-machine robotic cells, which introduced a novel motion cycle capable of handling both identical and varied part production. This foundational work, cited 6 times, provides a formal framework for analyzing system behavior and deadlock avoidance. In a related study, also with 6 citations, Heydari applied metaheuristic algorithms—such as genetic algorithms and simulated annealing—to analyze and maximize output rates in two-machine flexible robotic cells equipped with CNC machines capable of processing multiple operations. These contributions are notable for integrating computational intelligence with manufacturing system design, offering practical tools for improving throughput in automated production lines. Heydari’s work is particularly valuable for researchers and engineers seeking to optimize robotic cell performance through systematic modeling and algorithmic approaches.