معرفی
Joe Betts is a Researcher in the Department of Mechanical Engineering at the University of Bath. His work focuses on advanced manufacturing processes, including machining of additively manufactured materials, tool condition monitoring, and applications of machine learning in manufacturing systems. He has collaborated on projects involving surface integrity analysis, finite element modeling of material deformation, and the use of augmented reality in industrial settings.
His research interests span machining of high-performance alloys like Inconel 718 and Ti-6Al-4V, optimization of minimum quantity lubrication techniques, and real-time tool wear monitoring through sensor integration. Recent studies have explored the impact of heat treatment and directionality in additive manufacturing processes.
Betts has contributed to 5 peer-reviewed conference articles and 1 doctoral thesis. His work demonstrates trends in combining computational methods (e.g., neural networks) with practical manufacturing challenges. He has advised on a PhD thesis titled 'Machining of AM Inconel 718 Using Nano Lubricant MQL', supervised by Prof. Shokrani and Prof. Newman.
