https://popups.uliege.be/esaform21/index.php?id=2113 Publications of Auteurs Domenico Umbrello fr 0 https://popups.uliege.be/esaform21/index.php?id=2459 Machining continues to dominate the market among manufacturing processes requiring in-depth investigation on how material removal processes influence the surface integrity of the products. In this paper, experimental studies were carried out to evaluate the influence of several process parameters on surface integrity changes of Ti6Al4V alloy and to improve the overall process/product performance. In particular, orthogonal cutting operations were conducted varying the process parameters as cutting speed, feed rate and cooling conditions (dry, MQL and cryogenic cooling). Product quality specifications have been monitored in terms of microstructure, hardness modification, phase changes, also including tool wear analysis. Indeed, a systematic study is necessary since various factors are simultaneously involved, as well as changes during processing. Thus, due to the complexity of the process and the number of factors involved, the analysis of variance (ANOVA) was performed to optimize the process through the identification of significant parameters to maximize the useful tool-life and minimize the time of production. Tue, 23 Mar 2021 19:15:08 +0100 Fri, 02 Apr 2021 16:58:37 +0200 https://popups.uliege.be/esaform21/index.php?id=2459 https://popups.uliege.be/esaform21/index.php?id=2107 Nickel based superalloys, such as Waspaloy, are extensively used to manufacture components that operate under high temperature cyclic loads, because of their superior chemical and thermo-mechanical properties. In particular, these artifacts are mainly produced by shaping and/or finishing machining operations. Despite of their huge properties, these alloys show an extremely poor workability, that makes them part of the group of the so called difficult-to-cut materials. Therefore, the proper selection of the machining conditions is always challenging for the designers. In this context, predictive models represent an extremely useful tool to numerically simulate the machining process, guaranteeing a good knowledge of the material behavior under machining conditions, and avoiding expansive and time consuming experimental campaigns. Besides, the proper selection of the material rheological model is of fundamental importance in order to obtain precise and affordable results from the numerical model. In this work a Johnson-Cook based viscoplastic flow behavior model was proposed. The model was obtained from Artificial Neural Network (ANN) based interpolation techniques and validated using orthogonal machining experimental tests. Moreover, the proposed model was compared with other rheological models available from literature to benchmark their affordability and assessing their performances. Tue, 23 Mar 2021 12:48:40 +0100 Mon, 29 Mar 2021 10:53:46 +0200 https://popups.uliege.be/esaform21/index.php?id=2107