Rifatsiddiquepial

: Exploring Minimum Quantity Lubrication (MQL) techniques to reduce environmental impact during high-speed machining.

: Investigating surface roughness and cutting temperatures in precision turning. For instance, his work on ResearchGate details experimental studies on turning SiC-Al Alloy composites and AISI 1040 steel. RifatSiddiquePial

: Utilizing Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to develop models that predict tool wear and material performance under various cutting conditions. : Exploring Minimum Quantity Lubrication (MQL) techniques to

is a researcher and academic primarily associated with the field of mechanical engineering and manufacturing technology. His work often focuses on advanced machining processes, predictive modeling, and sustainable engineering practices. Research Contributions RifatSiddiquePial