Investigating the Machining Characteristics of Titanium Alloys Using Ultarasonic Machining

Abstract

Today, titanium and its alloys are extensively used for aerospace, industrial and consumer applications. In addition to aircraft engines and airframes, titanium alloys are also used in the applications like: missiles; spacecraft; chemical and petrochemical production; plant for hydrocarbon production and processing; power generation; desalination; nuclear waste storage; pollution control; ore leaching and metal recovery; offshore, marine deepsea applications, and ship components; armor plate applications; anodes, automotive components, food and pharmaceutical processing; recreation and sports equipment; medical implants and surgical devices etc. These alloys are branded as difficult to machine materials and the conventional machining processes are unable to provide good machining. Commercially these alloys are machined by non-conventional Electric Discharge Machining (EDM), which is giving good material removal rate however accuracy and surface finish are some problematic areas. Another non-conventional machining process i.e. Ultrasonic machining (USM) is widely used to make holes and cavities in hard or brittle work-pieces by using shaped tools, high frequency mechanical motion, and an abrasive slurry. This process is giving good accuracy and surface finish for such materials. So, the study was aimed to carry out research on ultrasonic machining of titanium alloys (as work material) while machining with USM using different tool materials to know their impact on material removal rate (MRR), tool wear rate (TWR), and to model these characteristics for their applications in manufacturing industry. In the current study the work has been limited to commercially pure titanium (TITAN I 5, ASTM Gr.2) and titanium alloy (TITAN31,' ASTM Gr.5), as work material, in combination with six different tool materials (Stainless steel; High speed steel; High carbon steel; Titanium; Tungsten carbide; Diamond) for experimentation. The results showed that the response variables (out put parameters) were strongly influenced by the control factors (input parameters).