A Study on Production Process Control and Intelligence Optimal Structure System Analysis Using Robot Control Systems

Recently, the demand for technology that can process and control manufacturing process data in real time has increased. In particular, the control of production processes using robot control systems and data systems for processes and process management in each manufacturing industry is different, leading to the need for data technology standardization. Importance is emerging. The purpose of this study was to monitor the manufacturing site based on a robot production plan using a robot control system and to study the optimized design of the robot from a structural perspective through the structural design problem of the robot. Through simulations that reflect manufacturing information, it not only establishes optimal production plans (APS, advanced planning, and scheduling) based on a digital twin platform synchronized with the field, but also presents the best alternatives in production and logistics operations, enabling flexible and robust decision-making for actual manufacturing. We wanted to perform a predictive analysis based on judgment. In this paper, we propose an active manufacturing robot system for high-level assembly processes that consists of a robotintegrated motion controller based on a position-force control linkage used as a manufacturing robot and a robot gripper capable of controlling the gripping force of target parts. A joint variable is also used. Additionally, the predicted intelligence optimal solution and moving solution by ADAMS & Marc Cosimulation were used for dynamic analysis using a nonlinear program.