Experimental and numerical investigation of cutting forces in micro-milling of polycarbonate glass. Issue 3 (3rd May 2020)

• Record Type: Journal Article
• Authors: Jahan, Muhammad Pervej; Ma, Jianfeng; Hanson, Craig; Chen, Xingbang; Arbuckle, Greg K.
• Is Part Of: Machining science and technology. Volume 24:Issue 3(2020)
• Page Start: 366
• Page End: 397
• Publication Date: 2020-05-03
• Subjects: Polycarbonate -- machinability -- tool coating -- cutting forces -- FEM simulation; Machining -- Periodicals; 671.3505
• DOI: 10.1080/10910344.2019.1698608
• Languages: English
• ISSNs: 1091-0344

Abstract

Abstract: Polycarbonates have found important applications in various types of industries including optical, automotive, aerospace, biomedical, and defense manufacturing industries. Conventional mechanical machining has the capability to create complex multi-scale parts and components for various materials including polymeric materials. This study investigates the cutting forces generated during the machining of polycarbonate glass using the micro-milling process. The goal of this research is to machine high quality micro-channels in polycarbonates for microfluidic applications. Both experimental investigation and numerical simulations using the Finite Element Method (FEM) have been carried out to assess the cutting forces generated in three directions during machining of polycarbonate. The effectiveness of tool coating on the reduction of cutting forces has been investigated. It was found that with the careful combination of depth of cut and feed rate, the ductile mode machining of polycarbonate can be achieved, which produces lower cutting forces, that could result in improved surface finish and low tool wear. Both lower and higher of depths of cut were found to generate higher cutting forces due to dragging action and higher tool-workpiece contact area respectively. The Finite Element Method (FEM) was found to be effective in simulating the cutting forces with acceptable range of errors, and thus, could be used to predict cutting forces at the parametric combinations beyond the capacity of the machine or without carrying out further expensive experimentation, for which the chances of tool failure are higher.