Issue 50

N. A. Fountas et alii, Frattura ed Integrità Strutturale, 50 (2019) 584-594; DOI: 10.3221/IGF-ESIS.50.49 584 Focused on the research activities of the Greek Society of Experimental Mechanics of Materials Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm Nikolaos Fountas School of Pedagogical and Technological Education, Department of Mechanical Engineering Educators, Laboratory of Manufacturing Processes and Machine Tools, ASPETE Campus, GR 14121, N. Heraklion, Greece fountasnikolaos@hotmail.com Angelos Koutsomichalis Hellenic Air-Force Academy, Faculty of Aerospace Studies, Dekelia Air Force Base, GR 19005, Greece angelos.koutsomichalis@hafa.haf.gr John D. Kechagias Technological Educational Institute of Thessaly, Mechanical Engineering Department, TEI Campus, GR 41110, Larissa, Greece jkechag@teilar.gr Nikolaos M. Vaxevanidis School of Pedagogical and Technological Education, Department of Mechanical Engineering Educators, Laboratory of Manufacturing Processes and Machine Tools, ASPETE Campus, GR 14121, N. Heraklion, Greece vaxev@aspete.gr A BSTRACT . Machinability of engineering materials is crucial for industrial manufacturing processes since it affects all the essential aspects involved, e.g. workload, resources, surface integrity and part quality. Two basic machinability parameters are the surface roughness, closely associated with the functional and tribological performance of components, and the cutting forces acting on the tool. Knowledge of the cutting forces is needed for estimation of power requirements and for the design of machine tool elements, tool-holders and fix- tures, adequately rigid and free from vibration. This work investigates the influ- ence of cutting conditions on machinability indicators such as the main cutting force Fc and surface roughness parameters Ra and Rt when longitudinally turning CuZn39Pb3 brass alloy. Full quadratic regression models were de- veloped to correlate the machining conditions with the imparted machinability characteristics. Further on, an advanced artificial grey wolf optimization algorithm was implemented to optimize the aforementioned responses with great success in finding the final optimal values of the turning parameters. K EYWORDS . Turning; Surface roughness; Cutting forces; Multi-parameter analysis; Optimization; Grey Wolf algorithm. Citation: Fountas, N.A., Koutsomichalis, A., Kechagias, J.D., Vaxevanidis, N.M., Multi-re- sponse optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm, Frattura ed Integrità Strutturale, 50 (2019) 584-594. Received: 23.01.2019 Accepted: 27.05.2019 Published: 01.10.2019 Copyright: © 2019 This is an open access article under the terms of the CC-BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.