The current level of Industry 4.0 is characterized by two main technologies—efficient use of new sensors and application of artificial intelligence (AI). This Special Issue deals with single- or multisensor systems used for various machining methods, such as dynamometers, accelerometers, acoustic emission sensors, current and power sensors, image sensors, temperature sensors, ultrasonic sensors, optical sensors, laser sensors, and other sensors. The application of sensor systems can more effectively solve the problems of automation and modeling of technological parameters of the main types of machining, such as turning, milling, drilling and grinding, etc. Such systems are widely used in tool condition monitoring, monitoring of machined surfaces, machine dynamics, etc. In this Special Issue, modern methods of artificial intelligence for the analysis and prediction of data obtained by sensor systems are also considered, such as neural networks, image processing, fuzzy logic, adaptive neurofuzzy inference systems, Bayesian networks, support vector machines, ensembles, decision trees and regression, k-nearest neighbors, Markov models, singular spectral analysis, and genetic algorithms. The possibility of building diagnostic systems of machining processes based on complex sensor systems and their use in conjunction with artificial intelligence create opportunities for the development of efficient and reliable machining processes for Industry 4.0.
It is our pleasure to invite you to submit original research papers, short communications or state-of-the-art reviews which are within the scope of this Special Issue.
Dr. Danil Yurievich Pimenov
Dr. Tadeusz Mikolajczyk
Dr. Munish Kumar Gupta