Automated Error Diagnostics for Semiconductor Controllers
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Solution Overview
Problem
Manual error diagnostics in industrial apparatus, such as semiconductor processing equipment, are time-consuming, prone to human error, and restricted by clean room access, often resulting in lost data and prolonged equipment downtime.
Innovation Solution
Automated customizable error diagnostics (ACED) systems that allow a higher level controller to detect error conditions, transmit diagnostic commands, and collect data automatically, eliminating the need for manual intervention by field service engineers and ensuring data collection before system shutdown.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual error diagnostics are performed by field service engineers using laptops, then diagnostic capability is achieved, but time consumption and equipment downtime increase
Solution Approach 1:
The system enables automated self-diagnosis by having the controller automatically execute diagnostic commands and collect error data without requiring field service engineer intervention. The controller monitors error conditions, selects appropriate diagnostic commands, executes them, and stores results autonomously, transforming the manual diagnostic process into an automated self-service system.
Solution Approach 2:
The system performs preliminary diagnostic actions by automatically collecting and storing error data and diagnostic results in memory before field service engineers arrive. This preliminary data collection ensures that when engineers do arrive, they can immediately access pre-collected diagnostic information, eliminating the need to wait for on-site diagnostics to be performed.
2Loss of information
If field service engineers manually collect diagnostic data, then diagnostic information is obtained, but human error increases and data integrity decreases
Solution Approach 1:
The system replaces the manual mechanical process of field service engineers physically connecting laptops and typing commands with an automated electronic control system. The controller automatically selects and executes diagnostic commands, retrieves data from memory, and stores results without human intervention, eliminating the variability and potential for human error inherent in manual operations.
Solution Approach 2:
The system implements automated feedback loops where the controller continuously monitors for error conditions, automatically responds by executing appropriate diagnostic commands, and stores the results. This closed-loop feedback mechanism ensures that diagnostic actions are consistently triggered and executed based on detected error states, maintaining data integrity through systematic automated processes rather than manual judgment.
3Ease of operation
If laptops are brought into clean rooms for diagnostics, then diagnostic access is achieved, but clean room restrictions and access delays occur
Solution Approach 1:
The controller acts as an intermediary that enables diagnostic functionality without requiring physical access to the equipment. By embedding diagnostic capabilities within the controller itself and allowing remote execution of diagnostic commands, the system eliminates the need for field service engineers to physically enter clean rooms with laptops, thus removing the access restrictions and delays associated with clean room protocols.
4Reliability
If the system is shut down during error conditions, then safety is maintained, but diagnostic data is lost
Solution Approach 1:
The system performs preliminary data collection by automatically monitoring error conditions and executing diagnostic commands to collect and store relevant error data in memory before the system is shut down. This ensures that diagnostic information is captured and preserved while the error condition still exists, maintaining data integrity even though the system must subsequently shut down for safety reasons.
Data Source
AI summary
A system and method of automated customizable error diagnostics is provided for use with industrial apparatus, such as semiconductor manufacturing apparatus. An external device, such as a robot, is provided with its own low level controller and a high level controller is provided to send instructions to the low level controller. The high level controller is programmed to perform automated customizable error diagnostics to diagnose errors in the external device. The high level controller monitors the occurrence of error conditions in the external device and executes a list of diagnostic commands based upon a detected error condition. Data concerning the error condition is automatically gathered to diagnose the cause of the error, before the external device executes its own error handling routines. In some embodiments, an editor is provided to edit and customize the diagnostic commands and a viewer is provided to allow diagnostic data to be viewed.