AI Product Test Instruction Generation From Product Images
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Product testing is a lengthy and labor-intensive process, often requiring outsourcing to external testers, which can be time-consuming and unsuitable for fast turn-around times, and existing automated testing systems require manual instruction creation that is costly and inefficient when product changes occur.
Innovation Solution
An electronic system utilizing neural networks, such as ChatGPT, to automatically generate product testing instructions by capturing images, determining product features, verifying test feasibility, and executing tests through a product testing device that simulates human actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If product testing is outsourced to external testers, then product testing can be performed, but it is time-consuming and not suitable for fast turn-around times
Solution Approach 1:
The system enables self-service automated product testing by allowing the product itself to generate testing instructions through neural network analysis of its own images and features, eliminating the need for external testers and reducing turnaround time while maintaining testing reliability
Solution Approach 2:
The patent replaces the mechanical process of manual test creation and external human testing with an automated electronic system using neural networks and image processing to generate and execute testing instructions, significantly reducing time while preserving testing thoroughness
2Extent of automation
If manual product testing instruction creation is performed, then automated product testing can be executed, but it is time-consuming and labor-intensive
Solution Approach 1:
The system performs self-service by automatically generating testing instructions through neural network analysis of product images and features, eliminating the need for manual instruction creation while enabling comprehensive automated testing execution
Solution Approach 2:
The patent substitutes the manual mechanical process of creating testing instructions with an automated neural network-based system that analyzes product images, identifies features, and generates appropriate testing instructions automatically, dramatically reducing both time and labor requirements
3Reliability
If product testing instruction is created manually, then testing can be performed, but debugging and adjusting instructions when product changes occur is expensive
Solution Approach 1:
The system implements dynamics by continuously analyzing updated product images and features through neural networks to automatically generate revised testing instructions when product changes occur, maintaining testing accuracy without requiring expensive manual debugging and adjustment
Solution Approach 2:
The patent replaces the expensive manual process of debugging and adjusting testing instructions with an automated neural network system that dynamically regenerates appropriate instructions based on updated product characteristics, significantly reducing maintenance costs while preserving testing reliability
Data Source
AI summary
An electronic system includes: a product retriever configured to access a product; an image capturer configured to capture one or more images of the product; and one or more processing units configured to generate prompts for input to a neural network, wherein the prompts are configured to prompt the neural network to determine a feature of the product based on at least one of the one or more captured images, determine a suggested testing for the feature of the product, perform a verification to determine whether the suggested testing for the feature of the product can be performed, and generate product testing instruction after the verification is performed.