Optical Recognition System for Automatic Machine Parameter Adjustment
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Solution Overview
Problem
Manual adjustment of semiconductor processing machines is time-consuming and inconsistent due to operator experience variations, leading to inefficiencies in maintaining operation conditions within the expected tolerable range.
Innovation Solution
An apparatus and method utilizing an optical recognition system, control unit, and remote control interface to monitor and automatically adjust processing machines by comparing actual operation information with expected parameters, using an AI algorithm to generate control signals and adjust parameters such as magnetic field, arc current, and temperature, enabling systematic and efficient operation control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment is used by operators, then the operation condition can be adjusted based on experience, but the process is time-consuming and inconsistent due to operator experience differences
Solution Approach 1:
The system enables self-service automation where the control unit automatically monitors operation conditions through the optical recognition system, compares them with expected values, and adjusts parameters without human intervention. The machine serves itself by autonomously detecting deviations and executing corrections based on stored operation models.
Solution Approach 2:
The patent replaces the mechanical manual adjustment process with an automated control system. The optical recognition system captures display information, the control unit processes data and makes decisions, and the remote control interface executes adjustments, substituting human operators with an integrated automated control loop.
2Ease of operation
If manual adjustment is used by operators, then the operation condition can be adjusted, but different operators produce different adjustment results due to experience variation
Solution Approach 1:
The system standardizes operation conditions by storing optimal parameter sets in operation models within the database. Instead of relying on varying operator judgments, the control unit retrieves and applies predefined parameter configurations that ensure consistent, repeatable results across different production runs and operators.
Solution Approach 2:
The optical recognition system continuously monitors operation conditions and feeds this information back to the control unit. The control unit compares actual conditions with expected values from operation models and automatically adjusts parameters to maintain consistency, creating a closed-loop feedback system that eliminates operator variability.
3Productivity
If automated control is implemented, then productivity and consistency are improved, but the device complexity increases
Solution Approach 1:
The control unit performs multiple functions: it controls the optical recognition system, accesses the database for operation models, processes comparison logic, generates control signals, and interfaces with the processing machine. This multi-functional design consolidates what could be separate complex subsystems into a single integrated control unit, managing overall system complexity.
Solution Approach 2:
The optical recognition system acts as an intermediary between the processing machine display and the control unit. It captures display information and converts it into a form usable by the control unit, serving as a buffer that simplifies the interface between the physical machine and the digital control system.
4Productivity
If automated control is implemented, then manpower requirements are reduced, but the initial setup and system complexity increase
Solution Approach 1:
Operation models containing optimal parameter sets are pre-stored in the database before production begins. This preliminary preparation of control data eliminates the need for manual parameter optimization during production, reducing ongoing manpower requirements while the initial setup effort is concentrated in the database population phase.
Data Source
AI summary
An apparatus for controlling an operation of a machine includes an optical recognition system, a control unit, and a remote control interface. The optical recognition system is configured to monitor and obtain actual operation information displayed on a panel of a processing machine in accordance with an operation time. The control unit is configured to receive the actual operation information and check the actual operation information with expected operation information. The expected operation information is obtained based on an operation model which is already built up corresponding to a current fabrication process. Deviation information between the actual operation information and the expected operation information is determined and converted into a parameter set. The remote control interface receives the parameter set and converts the parameter set into a control signal set to control the operation of the processing machine.