Advances in Intelligent Manufacturing and Service System Informatics

Zekai Şen obtained B.Sc. and M.Sc. degrees from Technical University of İstanbul in 1971. His post-graduate studies were carried out at the University of London, Imperial College of Science and Technology. He was granted Diploma of Imperial College (D.I.C) and M.Sc. in Engineering Hydrology in 1972 and Ph.D. in Stochastic Hydrology in 1974. He has worked in different faculties as the head of department such as the Faculty of Earth Sciences, Hydrogeology Department; Faculty of Astronautics and Aeronautics, Meteorology Department. His main interests are hydrology, water resources, hydrogeology, hydrometeorology, hydraulics, science philosophy and history. He has published numerous papers in journals of national and international repute. Dr. Özer Uygun received the B.Sc., M.Sc., and Ph.D. degrees in industrial engineering from Sakarya University, Turkey, in 1999, 2002, and 2008, respectively. He started his academic position at Marmara University and worked as aLecturer from 2000 to 2003. Then, he was a Research Assistant at Sakarya University from 2003 to 2008, where he is currently an Associate Professor. He was a Researcher in the EU FP6 Network of Excellence (I*PROMS: 2004 2009) and FP6 STREP Project (IWARD: 2007 2009). He successfully completed the EFQM Assessor Training in Brussels in 2015. His research interests are Operations Research, Optimization, Decision Making, Multi-criteria Decision Making, and Artificial Intelligence. Caner Erden is an assistant professor at the Faculty of Applied Sciences, Sakarya University of Applied Sciences, Turkey. He received his Ph.D. in industrial engineering from Natural Science Institute Industrial Engineering Department, Sakarya University, Turkey. His main research interests include scheduling, discrete event simulation, meta-heuristic algorithms, modelling and optimization, decision-making under uncertainty, machine learning and resource allocation and rough sets.

• Project Idea Selection in an Automotive R&D Center.- Modeling Electro-Erosion Wear of Cryogenic Treated Electrodes of Mold Steels Using Machine Learning Algorithms.-  Determination of the Most Suitable New Generation Vacuum Cleaner Type with PFAHP-PFTOPSIS Techniques Based on E-WOM.- Quality Control in Chocolate Coating Processes by Image Processing: Determination of Almond Mass and Homogeneity of Almond Spread.- Internet of Medical Things (IoMT): An Overview and Applications.- Forecasting Electricity Prices for the Feasibility of Renewable Energy Plants.