This paper proposed a CNC interpolator based on block overlap, capable of changing acceleration and deceleration time constants during continuous machining. The time constant can be set individually for each block through G-code commands. A velocity profile generation algorithm is proposed to set different time constants for both acceleration and deceleration phases. This algorithm can be applied to short blocks. The block overlap algorithm can be used for corner smoothing. A simulation model of the CNC interpolator was constructed to evaluate the proposed interpolation algorithm. Simulation results demonstrated that the proposed algorithm increased precision in areas with significant angular changes by adjusting time constants while simultaneously reducing machining time.

Directed energy deposition (DED) additive manufacturing technology enhances the functionality of existing or damaged parts by adding metallic materials to the surfaces. Blown-powder DED technology utilizes a focused, high-energy source to fuse the part’s surface with the supplied metal powder. Maintaining a constant stand-off distance (SOD), the distance between the deposition head and the workpiece, is a key factor in ensuring deposition quality, as variations in SOD will change the powder focus position and the laser spot size on the surface. Therefore, traditional additive manufacturing systems require CAD or pre-scanned surface data. In this study, we proposed auto-surface tracking technology. No workpiece CAD data or pre-scanned surface data are required, and in-situ measurement and feedback control can automatically consider the deposition height differences that cause a change in SOD when depositing the next layer. The accuracy of the SOD measurements and feedback control error was verified using a step height sample. The mean SOD measurement error was 4.7 ㎛ with a standard deviation of 42 ㎛ (reference SOD, 14 ㎜). The feasibility of the autosurface tracking technology was confirmed through the additive manufacturing processes of the gear and an actual blanking mold applied in the defense and industrial fields.

A virtual machine tool, a computer simulation model of the machine motion and cutting process with a level of accuracy and consistency that can replace an accurate machine tool, is one of the critical digital transformation technologies in the manufacturing industry. During the machine development phase, cost and time can be reduced by evaluating machining efficiency and quality through virtual prototyping. In the machine application phase, virtual machine tools can be used to accurately assess the condition of equipment and processes by analyzing actual data combined with simulated data. This paper introduces a virtual machine tool system that can analyze the behavior of an accurate machine tool by integrating physical models of structure, numerical controller, and cutting process. The key features of the virtual machine tool, synchronous machining simulation, machining stability detection, machining error estimation, and part program optimization, were evaluated through various machining tests with a vertical 3-axis milling machine.

With the advent of the 4th industrial revolution, advanced digital manufacturing technologies are actively developed to strengthen manufacturing competitiveness. Smart factories require a real-time digital twin including a Cyber-Physical System (CPS) of machines and processes and intelligent technologies based on the CPS. To predict machining quality and optimize machines and processes, it is necessary to analyze the cutting force during machining. Therefore, for real-time digital twin, a fast cutting force simulation model that receives information such as the positions of the feed axes in short time intervals from the CNC and calculates the cutting force until the next information is input is required. This paper proposes a voxel-based fast cutting force simulation in NC milling for real-time digital twin. The proposed simulation model quickly calculates the cutting force by using only information of voxel elements removed by each tool edge without complicated Cutter-Workpiece Engagement (CWE) and chip thickness calculations in previous studies. To verify the performance of the developed simulation, experimental machining was performed and the measured cutting force and simulated cutting force were compared. It was demonstrated that the proposed model can successfully predict the cutting force 3.5 times faster than the actual process.

One of common challenges in designing modern production machines is realizing high speed motion without sacrificing accuracy. To address this challenge it is necessary to maximize the stiffness of the mechanical structure and the control system with consideration on the main disturbance input, cutting forces. This paper presents analysis technologies for realizing high stiffness in production machines. First, CAE analysis techniques to evaluate the dynamic stiffness of a machine structure and a new method to construct the physical machine model for servo controller simulations are demonstrated. Second, cutting forces generated in milling processes are analyzed to evaluate their effects on the mechatronics system. In the effort to investigate the interaction among the structure, controller, and process, a flexible multi-body dynamics simulation method is implemented on a magnetic bearing stage as an example. The presented technologies can provide better understandings on the mechatronics system and help realizing high stiffness production machines.

In this paper, a simulation based estimation method of energy consumption of the spindle and feed drives for the NC machine tool during the cutting process is proposed. To predict energy consumption of the feed drive system, position, velocity, acceleration and jerk of the table are analyzed based on NC data and then the power and energy are calculated considering friction force and mass of the stages. Energy consumption of the spindle is estimated based on models from acceleration motion of rotating parts, friction torque and power loss of motors. Moreover, simulation models of cutting power and energy for the material removal along the NC tool paths are proposed.