ORIGINAL ARTICLE An integrated toolpath and process parameter optimization for high-performance micro-milling process of Ti–6Al–4V titanium alloy Thanongsak Thepsonthi & Tuğrul Özel Received: 1 May 2014 /Accepted: 24 June 2014 /Published online: 11 July 2014 # Springer-Verlag London 2014 Abstract Titanium alloys such as Ti–6Al–4V offer biocom- patibility, corrosion resistance, and superb mechanical prop- erties and are considered the most important metallic bioma- terial for medical applications. However, mechanical machin- ing of titanium alloys is still highly difficult and even more challenging for micro-scale machining such as micro-milling. Severe burr formation and rapid tool wear create significant problems such as poor surface roughness. In order to improve the performance of micro-milling Ti–6Al–4V alloy, this study proposes an integrated method in selecting the toolpath and optimum process parameters which can meet micro- machining requirements and constraints. Controlled micro- end-milling experiments for measuring burr formation and surface roughness, finite element simulations for predicting forces and tool wear, and mathematical modeling and optimi- zation techniques have been utilized for determining optimum toolpath strategy and process parameters. Based on the micro- end-milling tests on a circular thin rib feature, process optimi- zation results are validated and indicate a significant improve- ment in process performances in terms of minimizing burr formation, maximizing tool life, and surface quality. Keywords Micro-end milling . FE simulations . Process optimization . Titanium alloys List of symbols A,B,C Original Johnson–Cook material model coefficients a, b, d, p, r, s Modified Johnson–Cook material model coefficients a i Polynomial coefficients a p Axial depth of cut (μm) B, b 0 , b 1 Wear depth model constants B T Total top-burr width (mm) C p Specific heat capacity (N/ mm 2 °C) c 1, c 2 Wear rate model constants dF x Differential force component in X direction (N/mm) dF y Differential force component in Y direction (N/mm) F x Cutting force in X direction (N) F x max Maximum cutting force in X direction (N) F x max allow Maximum allowable cutting force in X direction (N) F y Cutting force in Y direction (N) F y max Maximum cutting force in Y direction (N) F y max allow Maximum allowable cutting force in Y direction (N) f z Feed per tooth (mm/rev/tooth) h Convection coefficient (N/s mm °C) h c Thermal contact conductance (N/s mm °C) k Number of independent variables k 1 , k 2 Acceleration coefficients of particles in particle swarm L Maximum linear cutting distance (mm) L req Required cutting distance (mm) l c Tool cutting length (μm) m Shear friction factor n Number of teeth in the micro-end mill p i Vector of the personal best position p g Vector of the best position found by particles in its neighborhood p i Interface pressure (N/mm 2 ) T. Thepsonthi : T. Özel (*) Manufacturing and Automation Research Laboratory, Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ, USA e-mail: ozel@rci.rutgers.edu Int J Adv Manuf Technol (2014) 75:57–75 DOI 10.1007/s00170-014-6102-2