Passive optimal tool structures for vibration cutting

Higher surface quality of the machined workpiece is obtained when the cutting tool is excited at high-frequency vibrations that are superimposed on its continuous movement. Traditionally excitation of high-frequency vibrations at the tool cutting edge needs special equipment, which poses challenges for implementation of such vibrational cutting tool in industrial environment. More effective could be the passive way with respect to structural changes of the tool. The main idea is based on the intensification of higher vibration modes of a cutting tool as a flexible structure. Higher modes are characterized by higher frequencies and lower vibration amplitudes, which induces vibrational cutting effect that results in a better quality of the machined surface. Furthermore, intensification of a higher mode increases the magnitude of internal energy dissipation inside tool material and thereby makes the tool a more effective damper, which positively influences the amplitudes of workpiece or machine tool itself, providing the possibility to reduce chatter

Multi-fingered haptic palpation utilizing granular jamming stiffness feedback actuators

This paper describes a multi-fingered haptic palpation method using stiffness feedback actuators for simulating tissue palpation procedures in traditional and in robot-assisted minimally invasive surgery. Soft tissue stiffness is simulated by changing the stiffness property of the actuator during palpation. For the first time, granular jamming and pneumatic air actuation are combined to realize stiffness modulation. The stiffness feedback actuator is validated by stiffness measurements in indentation tests and through stiffness discrimination based on a user study. According to the indentation test results, the introduction of a pneumatic chamber to granular jamming can amplify the stiffness variation range and reduce hysteresis of the actuator. The advantage of multi-fingered palpation using the proposed actuators is proven by the comparison of the results of the stiffness discrimination performance using two-fingered (sensitivity: 82.2%, specificity: 88.9%, positive predicative value: 80.0%, accuracy: 85.4%, time: 4.84 s) and single-fingered (sensitivity: 76.4%, specificity: 85.7%, positive predicative value: 75.3%, accuracy: 81.8%, time: 7.48 s) stiffness feedback