Qiuhua Tang
Papers
13
Total Citations
915
H-Index
11
About
Qiuhua Tang is a prominent researcher specializing in robotic assembly line balancing, optimization algorithms, and sustainable manufacturing systems. His work has fundamentally advanced the field of intelligent production engineering, with a particular focus on two-sided robotic assembly lines, U-shaped assembly configurations, and collaborative robot integration in industrial settings. Tang's most celebrated contribution, his 2016 co-evolutionary particle swarm optimization algorithm for two-sided robotic assembly line balancing, has garnered 234 citations, reflecting its landmark status in the field. Alongside this, his parallel research on minimizing energy consumption using simulated annealing (137 citations) established him as a pioneer in energy-aware manufacturing optimization. His work consistently bridges multiple objectives — reducing carbon footprints, minimizing cycle times, lowering noise pollution, and maximizing line efficiency — demonstrating a sophisticated understanding of real-world industrial constraints. Notably, Tang was among the first researchers to simultaneously address balancing and sequencing in robotic mixed-model assembly lines, and his later investigations into collaborative robots (cobots) reflect his commitment to emerging automation trends. Employing diverse metaheuristics including grey wolf optimization, cuckoo search, and migrating bird optimization, his cumulative body of work exceeds 880 citations, making him an essential reference point for researchers and engineers advancing smart, sustainable manufacturing systems.
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