@article { , title = {On modelling of laser assisted machining: forward and inverse problems for heat placement control}, abstract = {Laser assisted machining (LAM) is one of the most efficient ways to improve the machinability of difficult-to-cut materials (e.g. Nickel-based superalloys). In the conventional LAM process, the laser beam is focused ahead of the cutting area at a fixed location, which leads to a series of restrictions, e.g. small heating area and non-uniform heat distribution due to the limitation of beam size and energy distribution. In this paper, a novel spatially and temporally (S\&T) controlled laser heating method was proposed, in which a large area can be heated up with a small laser spot by controlling the beam scanning, i.e., laser power, path and speed of scanning. The laser configuration for the prescribed HAZ (heat affected zone) was achieved by solving the inverse heat conduction problem where the laser power together with either laser path or laser speed were optimised to achieve a particular temperature distribution in the chip to be removed by the following milling cutter. The proposed S\&T laser heating method was thoroughly validated both for the direct and, the more important, inverse heating models by performing extensive temperature experiments by both infrared thermal camera and thermocouple array and further verified by laser assisted milling (LAMill) tests of Inconel 718 for large widths of cuts. The results showed that by applying path-optimised LAMill based on the inverse solution of the thermal problem, the peak and mean principal cutting forces were reduced by 55\% and 47.8\% respectively compared with the conventional dry milling process while the surface roughness improved by at least 14\%. Moreover, after controlling the HAZ using the inverse thermal problem, a microstructure analysis of the machined surface showed that the proposed laser heating method avoids overheating of the workpiece below the planned depth of cut for the milling operation.}, doi = {10.1016/j.ijmachtools.2018.12.001}, issn = {0890-6955}, journal = {International Journal of Machine Tools and Manufacture}, note = {12 mo. embargo. OL 07.12.2018}, pages = {36-50}, publicationstatus = {Published}, publisher = {Elsevier}, url = {https://nottingham-repository.worktribe.com/output/1387652}, volume = {138}, keyword = {Mechanical Engineering, Industrial and Manufacturing Engineering}, year = {2019}, author = {Shang, Zhendong and Liao, Zhirong and Sarasua, Jon Ander and Billingham, John and Axinte, Dragos} }