Process Optimization of Chemical Vapor Deposition-Based Boron Nitride Coatings on Floating Ball Valve Components Using a Teaching Learning-Based Optimization Algorithm

Floating ball valves are widely utilized as isolation devices in pipeline systems where minimal pressure drop is essential. These valves typically comprise a carbon steel body, spherical ball, seat ring, sealing elements, stem, and gaskets. Conventional metal-to-metal sealing between the ball and seat often leads to surface degradation, including cracking, peeling, scratching, and delamination-especially under high-temperature or corrosive service conditions. To address these issues, the present study explores the deposition of boron nitride (BN) coatings on the ball and seat components using the Chemical Vapor Deposition (CVD) technique. BN was selected for its superior wear resistance, chemical inertness, and thermal stability, making it ideal for demanding applications across energy, marine, and aerospace sectors. The CVD process parameters-deposition temperature, coating time, and film thickness-were optimized using a teaching learning-based optimization algorithm to enhance coating performance. The objective was to minimize surface roughness and porosity while maximizing hardness. The optimal CVD conditions were identified as a temperature of 950°C, a coating thickness of 11 µm, and a deposition time of 20 hours. The optimized BN coating significantly improves the functional lifespan and sealing efficiency of floating ball valve components under adverse operating environments.