Robotic Coating System with Optical Feedback for Glass Substrates
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Solution Overview
Problem
Current methods for applying coatings to glass substrates, such as those used in automotive windows, are labor-intensive and prone to errors, leading to inadequate or excessive coating application, with limited ability for real-time control and modification.
Innovation Solution
A system and method utilizing optical detection systems and edge computing to control robotic units with nozzles, allowing for real-time determination of substrate characteristics and adjustment of coating application parameters, including amount, thickness, and position, based on patterns transmitted from edge computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional manual or robot-controlled spray methods are used for applying coatings to glass substrates, then the coating application process can be performed, but the coating precision is poor resulting in inadequate or excessive coating application
Solution Approach 1:
The system employs optical detection systems that scan the substrate in real-time to identify its actual shape, position, and characteristics. This feedback information is fed back to the control system, which dynamically adjusts the robotic unit's movement and nozzle positioning to achieve precise coating application that matches the substrate's actual geometry, thereby eliminating both inadequate and excessive coating areas.
Solution Approach 2:
The system transitions from static, pre-programmed coating paths to dynamic, real-time adaptive control. The robotic unit continuously receives updated position and shape data from optical sensors during the coating process, allowing it to dynamically adjust its trajectory, speed, and nozzle orientation to maintain optimal coating application parameters throughout the process.
2Reliability
If operator-controlled inspection systems are used to monitor coating application, then coating quality can be monitored, but the process becomes labor intensive
Solution Approach 1:
The system implements automated self-inspection capabilities through integrated optical detection systems that continuously monitor the coating application process in real-time. The system independently detects coating defects, measures coating thickness, and verifies application quality without requiring external operator intervention, thereby maintaining high reliability while eliminating labor-intensive manual inspection.
Solution Approach 2:
The patent replaces manual operator inspection with automated optical detection and sensing systems. These electronic and optical systems automatically capture images, analyze coating quality metrics, and provide real-time feedback, substituting the mechanical human inspection process with an automated sensor-based system that maintains or improves monitoring reliability while reducing operational complexity.
3Manufacturing precision
If conventional coating systems are designed for specific substrate shapes, then the coating application can be optimized for that shape, but the system lacks adaptability to different substrate types
Solution Approach 1:
The system is designed as a universal coating platform that can handle multiple substrate types and shapes through real-time optical scanning and adaptive control. The optical detection system captures the actual geometry of any substrate presented to the system, and the control algorithm generates appropriate coating paths and parameters dynamically, allowing a single system to perform optimally across diverse substrate configurations without requiring reconfiguration or dedicated tooling for each shape.
Solution Approach 2:
The system performs preliminary scanning and characterization of the substrate using optical detection systems before the actual coating application begins. This preliminary action captures the substrate's shape, size, and position data, which the control system then uses to pre-calculate and optimize the coating path and parameters specific to that substrate, ensuring high coating profile accuracy while maintaining adaptability to different substrate types.
Data Source
AI summary
A method, system, and computer program product for applying materials to a substrate. The method includes determining at least one optical indicium of a substrate based on data received from at least one optical detection system. The method also includes transmitting the at least one optical indicium to at least one edge computing device. The method further includes receiving at least one pattern from the at least one edge computing device. The method further includes controlling at least one robotic unit having at least one robot including at least one nozzle to apply at least one material to the substrate. Controlling the at least one robotic unit includes causing the at least one robotic unit to apply the at least one material to the substrate based on the at least one pattern.