Machine tool spindle is the most important mechanical component in removing metal during machining operations. The structural dynamics of the spindle are evaluated at the tool tip since it directly affects the material removal rate. Flexible spindles lead to unstable chatter vibrations, which can be avoided only by reducing the material removal rate. In addition, the spindle motor must have sufficient torque and power to overcome the cutting resistance of work materials to be machined. The spindles are currently designed based on accumulated experience, basic laws of machine design, and metal cutting mechanics. This thesis presents an expert spindle design system strategy which is based on the efficient utilization of past design experience, the laws of machine design and metal cutting dynamics.

The configuration of the spindle is decided by identifying the work material, desired cutting conditions and most common tools which will be used on the machine tool. The spindle drive mechanism, drive motor, bearing types, and spindle shaft dimensions are selected based on the target application. The thesis provides a set of fuzzy design rules which lead to interactive and automatic design of spindle drive configurations. The structural dynamics of the spindle are automatically optimized by distributing the bearings along the spindle shaft. The proposed strategy is to iteratively predict the Frequency Response Function (FRF) of the spindle at the tool tip using the Finite Element Method (FEM) based on Timoshenko Beam elements. Predicted FRF of the spindle is integrated to the chatter vibration stability law which indicates whether the design would lead to chatter vibration free cutting operation at the desired speed and depth of cut. The bearing spacings are iteratively optimized without violating the design constraints of the spindle.

The proposed expert system design is demonstrated by automatically designing several spindles which are found on industrial machine tools.