Evidence-based approach for removal mechanisms and process modelling in micro ultrasonic machining

Research advancement in the field of micromanufacturing is motivated by the demand on miniaturized features, components and products as well as by the promising developments in adoption of various existing macro manufacturing techniques for microscale manufacturing. One such technique is ultrasonic machining (USM), in which a tool and free abrasive particles are utilized to remove material from the workpiece. There is no direct contact between the tool and workpiece during the process. In addition, no surface or subsurface thermal damage is induced into the machined feature. These characteristics make the USM process an appropriate candidate for micromachining applications. Thus, micro ultrasonic machining (micro-USM) has become a niche technique to make micro components and micro features from hard, brittle materials for various applications such as micro electromechanical systems, microfluidics devices, biotechnology devices, and pressure sensors. However, there is a lack of established knowledge base in some aspects of micro-USM including material removal mechanisms and modes, machined surface quality, and material removal modelling. This research has endeavoured to achieve advancements in micro-USM technique through machine system development, process performance enhancement, removal mechanism investigations, and process model development. A new micro-USM system has been proposed in which a standard booster in combination with a special designed full-wave booster horn is employed for clamping and vibrating the workpiece. The design is capable of providing a consistent transmission of the ultrasonic vibration to the workpiece. Further, a force measurement system with a rapid response control has been developed to respond to the variation of static forces during the machining process. Machining experiments have been conducted using the developed micro-USM system to investigate the influence of process parameters on the surface and edge quality of the machined features. Results have demonstrated a considerable improvement in the quality of the machined surface.Doctor of Philosophy (MAE