Handbook of Machine Tool Analysis

Written by seasoned experts in the field, this reference explores efficient methods of design, structural analysis, and algorithm formulation to reduce waste, noise, and breakage in system function, identify faults in system construction, and achieve optimal machine tool performance. The authors investigate issues such as force, noise, vibration, and acoustic emission to predict the durability and strength of major system components. They evaluate noise levels for different types of machine tools, the effect of abrasion, fissure, and chemical diffusion on acoustic emission signals, the role of neural networks in machine tool diagnostics, and the Kurtosis method in virtual instrumentation.

Ioan D. Marinescu is Director of the Precision Micro-Machining Center and Professor in the Mechanical, Industrial, and Manufacturing Engineering Department, The University of Toledo, Ohio Constantin Ispas is Professor and Dean of the College of Engineering and Management of Production Systems, the Politehnica University of Bucharest, Romania Dan Boboc is Assistant Professor of Machine Tools and Robotics, the Politehnica University of Bucharest, Romania