Digital Twins in Manufacturing: Virtual and Physical Twins for Advanced Manufacturing (Springer Series in Advanced Manufacturing)

Preface
Contents
1 The State-of-the-Art in the Theoretical and Practical Applications of the Digital Twins Components
	1.1 Numerical Modeling and Prediction of Manufacturing Processes
	1.2 Vibration Cutting for Smart Manufacturing
	1.3 Vibration Energy Harvesting
	1.4 Internet of Things Devices for Manufacturing Process Control
	1.5 The Relationship Between Edge and Cloud-Based Computing
	References
2 Digital Twins for Smart Manufacturing
	2.1 Digital Twin Emphasis on Cutting Tool Vibration Control Through Design Parameters
		2.1.1 Optimally Designed Self-Exciting Drill for Vibration Cutting
		2.1.2 Modified Boring Tool Structures for Effective Cutting
	2.2 Cutting Tool Physical Entities and Their Virtual Counterparts Synchronization
		2.2.1 Simulation and Analysis of Vibration Turning Tool
		2.2.2 Evaluation of Workpiece Surface Roughness and Tool Wear
		2.2.3 Influence of Boundary Conditions on the Vibration Turning Tool Eigen Modes
	2.3 Evaluation of Technological Features of Macro- and Micro-drilling
		2.3.1 Virtual Twin of Vibration Drilling Tool
		2.3.2 Physical Twin of Vibration Drilling Tool
		2.3.3 Characterization of Vibration Drilling Process and Workpiece Surface Quality
		2.3.4 Drilling Process Simulation Using Smoothed Particle Hydrodynamics Method
		2.3.5 Micro-drill Stiffness Amplification by Buckling Mode Control
		2.3.6 Experimental Study of Micro-drill Physical Twin
	2.4 Quality Improvement of Grinding Operations
		2.4.1 An Excitation Approach to Ultrasonically Assisted Cylindrical Grinding
		2.4.2 Development of Actuator for Back Grinding
	2.5 Artificial Neural Networks Approaches for Quality Prediction in Robotized Incremental Sheet Forming
		2.5.1 Determination of Friction Force Between the Tool and Forming Sheet
		2.5.2 Evaluation Methodology of Metal Sheet Forming Process
		2.5.3 Cupping Test for the Material Model Calibration
	2.6 FE Simulations
		2.6.1 FE Simulations of Cupping Test for Material Model Calibration
		2.6.2 Numerical Simulations of SPIF Process
		2.6.3 Evaluation Methodology of Polymer Sheet Forming Process
	References
3 Integration of Digital and Physical Data to Process Difficult-to-Cut Materials
	3.1 Digital Twin for Excited Cutting Tool
		3.1.1 Prevention of Chemical Interactions Between Tool and Workpiece Materials by Contact Time Reduction
		3.1.2 Vibration Milling for Surface Finish Improvement
		3.1.3 Vibration Drilling of Brittle Materials
	3.2 Physical Twin of Vibrationally Excited Workpiece Drilling
		3.2.1 Vibration Excitation of a Workpiece for Drilling Force Reduction
		3.2.2 Development of Actuator Enabling a Brittle-Ductile Transition of Warkpiece Material
	References
4 Wireless Connectivity Options for Tool Condition Monitoring IoT Applications
	4.1 The New Principles of Energy Harvesting in Macro Level
		4.1.1 Virtual Twin of Piezoelectric Energy Harvester
		4.1.2 Enhanced Harvester Configuration
		4.1.3 Investigation of Optimized Cantilever Beam
		4.1.4 Appropriate Way to Extract the Low-Frequency Vibration Energy
	4.2 The New Principles of Energy Harvesting in Micro Level
		4.2.1 Enhanced Vibration Energy Harvesting Configuration
	References
5 Digital Twin-Driven Technological Process Monitoring for Edge Computing and Cloud Manufacturing Applications
	5.1 Edge Computing-Enabled Wireless Vibration Sensor Node
		5.1.1 Use Case of the Non-rotating Tool
		5.1.2 Use Case of the Rotating Tool
	5.2 Wireless IoT Vibration Sensor for Cloud Manufacturing Applications
		5.2.1 Virtual Twin of Piezoelectric Transducer
		5.2.2 Rotating Shank-Type Tool Condition Monitoring
	5.3 Tool Wear Status Recognition Based on Machine Learning
		5.3.1 Support Vector Machines Algorithm Adaptation for Milling Force Prediction
	References