Boring Tool Chatter Suppression Using Magneto-Rheological Fluid Damper through Regression Models

Abstract

Chatter is a problem of instability in the metal cutting process, especially in boring operation when the length of the hole to be bored is high. The phenomenon is characterized by violent vibrations, loud noise and poor quality of surface finish. Chatter causes a reduction of the life of the tool and affects the productivity by interfering with the normal functioning of the machining process. Many academic and industrial engineers reported the chatter suppression in turning operation; however, for boring operation, there is a lot of scope for studying the chatter suppression problem. This paper presents the use of magneto-rheological fluid for active chatter suppression through regression models. The vibration signals corresponding to different machining conditions were captured. The relevant features of the signals were extracted. The characterized magneto-rheological fluid was taken and regression models were built to suppress the tool chatter based on on-line vibration measurement. The models built in the study are linear regression model, support vector regression model and artificial neural network model. The regression model results are validated.