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Hard turning processes have several advantages against traditional turning. Improved surface integrity and short process time are some examples. Surface integrity is one of the most important issues in modeling of machining processes. Multiple roughness parameters are observed in relation to several controllable and uncontrollable input parameters. Since these multiple roughness parameters are correlated, multivariate methods are the most suitable approach for process control. This research aims to propose a method for assessing stability and performance of multivariate processes in the presence of noise variables. A hybrid method based on design of experiment, statistical process control and principal component analysis was applied to AISI 52100 hardened steel turning. The process performance index was obtained within the range of 0.18 to 1.11. The best process performance was achieved taking cutting speed of 170m/min and lubricating fluid flow of 3 L/min.

A Multivariate Statistical Quality Control of AISI 52100 Hardened Steel Turning