Investigated Information Data of CNC Machine Tool for Established Productivity of Industry 4.0

Abstract

The information data of CNC machine tool based on the controller tuning operation are investigated for established productivity of industry 4.0. Industry 4.0 is a smart productivity based on industrial internet of things, big data, and cyber physical systems in manufacturing industries. For productivity of industry 4.0 establishing, the position control gains Kp, position feedforward control gains Kf, and speed control gains Kv, in CNC machine tool are major tuning parameters. The different KP gains of 10, 50, 100, 300, and 400 rad/s are investigated for a smart productivity in position control mode. The system responses of CNC machine tool at different position feedforward gains Kf of 0, 50, 80, and 100% and the different speed control gains Kv of 50, 100, 1000, 2000, and 3000 rad/s are investigated for a smart productivity. In addition, the steady-state errors and the setting times at the different Rg ratios of (1:1), (3:1), (5:1), and (7:1) are analysed in position control mode. Results showed the KP gains mainly enhances the settling times and reduces the rise times. The tuning output responses of different Kf gains are almost second order system. The speed control gains Kv mainly enhances the transient response. The characteristic responses of the tuning operations are enabled with connectivity to a cloud network to share the big data, to support decision making, and to adjust operations in real time.