Remote AI Troubleshooting for Circuit Card Assemblies
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Solution Overview
Problem
Current troubleshooting systems for circuit card assemblies and printed circuit boards (PCBs) are limited by the need for physical proximity and technical expertise, which can lead to delays and increased costs due to the logistics of transporting technical knowledge to production sites.
Innovation Solution
A system and method for autonomous troubleshooting using artificial intelligence (AI) and machine learning, which includes a test station with a computer, memory, and a test probe, and an operator station that communicates with the test station via a network to teach the AI program and store acceptable test results in a knowledge database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If technical expertise is transported to production sites to troubleshoot defective PCBs, then troubleshooting quality is improved, but travel time and logistics costs increase
Solution Approach 1:
The patent creates a virtual copy of the expert troubleshooting environment by transmitting video feeds from the production site to a remote expert's workstation. This allows the expert to visually inspect and guide troubleshooting without physically traveling to the site, thereby maintaining high troubleshooting quality while eliminating travel time and associated logistics costs.
2Reliability
If technical expertise is transported to production sites to troubleshoot defective PCBs, then troubleshooting quality is improved, but logistics costs increase
Solution Approach 1:
The patent creates a virtual copy of the expert troubleshooting environment by transmitting video feeds from the production site to a remote expert's workstation. This allows the expert to visually inspect and guide troubleshooting without physically traveling to the site, thereby maintaining high troubleshooting quality while eliminating travel time and associated logistics costs.
3Measurement precision
If physical proximity to PCBs is required for troubleshooting, then inspection accuracy is improved, but device complexity increases due to logistics requirements
Solution Approach 1:
The patent introduces video transmission technology as an intermediary between the remote expert and the physical PCB. High-resolution cameras capture detailed images and video feeds of the defective boards, transmitting them to the expert who can perform visual inspection with high accuracy without needing physical proximity. This eliminates the complex logistics of transporting experts or boards while maintaining inspection quality.
4Reliability
If defective PCBs are shipped to expertise locations for troubleshooting, then troubleshooting quality is improved, but productivity decreases due to shipping time
Solution Approach 1:
The patent creates a virtual copy of the expert troubleshooting environment by transmitting video feeds from the production site to a remote expert's workstation. This allows the expert to visually inspect and guide troubleshooting without physically traveling to the site, thereby maintaining high troubleshooting quality while eliminating travel time and associated logistics costs.
Solution Approach 2:
The patent introduces video transmission technology as an intermediary between the remote expert and the physical PCB. High-resolution cameras capture detailed images and video feeds of the defective boards, transmitting them to the expert who can perform visual inspection with high accuracy without needing physical proximity. This eliminates the complex logistics of transporting experts or boards while maintaining inspection quality.
Data Source
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AI summary
System and method for autonomous trouble shooting of a unit under test (UUT) having a plurality of replaceable components include: a test station that stores an artificial intelligence (Al) program and a knowledge database (KDB) including acceptable test results for each test point represented by an acceptable test vector, a test probe to test the circuit card assembly; and an operator station to send commands to the test station via the communication network to teach the Al program to capture and store the acceptable test result for each test point of the UUT by the test probe, in the KDB, wherein the Al program commands the test probe to test the UUT, stores the test results in a test result vector, compares the test result vector with the stored acceptable test vector, and displays recommendation as which replaceable component in the UUT to be repaired or replaced.