This document discusses applying non-traditional optimization techniques to improve quality in tool holders. It begins with an abstract that describes using Taguchi's design of experiments, response surface methodology, and genetic algorithms to optimize grinding process parameters and minimize defects. The document then reviews literature on using techniques like genetic algorithms and particle swarm optimization to optimize machining processes. It presents the methodology used, which includes conducting experiments using an L9 orthogonal array to evaluate control parameters, developing a mathematical model relating parameters to quality, and using genetic algorithm and particle swarm optimization to minimize deviations from quality targets.