Development of the Intelligent Pneumatic Sewing Platform for Mask Production.

Area of Science:

• Robotics and Automation
• Mechanical Engineering
• Control Systems

Background:

• Pneumatic systems offer advantages in speed and energy efficiency for automation.
• Developing precise control for nonlinear pneumatic systems remains a challenge.
• Automated mask production requires robust and efficient fabrication platforms.

Purpose of the Study:

• To design and fabricate a two-dimensional pneumatic servomechanism-based mask sewing platform.
• To develop and analyze a mathematical model for precise control of the pneumatic system.
• To validate the platform's capability for automatic mask production.

Main Methods:

• Platform design using SOLIDWORKS, integrating pneumatic cylinders and a fabric-clamping mechanism with a sewing machine.
• Mobility analysis to determine the mechanism's degrees of freedom.
• Development of a mathematical model for the pneumatic servo control system.
• Formulation of an intelligent parameter adjustment feature with a sliding-mode controller.
• Real-time control implementation using MATLAB Simulink.

Main Results:

• The mask sewing platform was successfully designed, constructed, and experimentally verified.
• The control system demonstrated effective management of the nonlinear and time-variant pneumatic system.
• Hybrid and fifth-order paths were successfully implemented, confirming the platform's functionality.
• The platform proved capable of automatically producing masks with high precision.

Conclusions:

• The fabricated pneumatic servomechanism-based platform offers a simple, fast, and energy-efficient solution for automated mask production.
• The developed sliding-mode controller effectively manages the complex dynamics of the pneumatic system.
• The study validates the feasibility of using advanced control strategies for robotic automation in manufacturing.