AI Product Testing Instruction Generation From Product Images

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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 for product changes.

Innovation Solution

An electronic system utilizing neural networks, particularly ChatGPT, to automatically generate product testing instructions by capturing images, determining product features, verifying testing feasibility, and executing tests through a product testing device that simulates human actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated product testing device is provided, then testing efficiency is improved, but the complexity of creating testing instructions increases

Engineering Contradiction:

Improvetesting efficiencyVSAvoidtesting instruction creation complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system enables self-service by allowing the product testing device to automatically generate its own testing instructions through image capture and processing units that analyze product images and create appropriate test sequences without human intervention

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical instruction creation with an automated electronic system that uses image processing and computational algorithms to generate testing instructions, eliminating the need for human experts to manually create test protocols

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual product testing is performed, then testing accuracy is maintained, but time consumption increases

Engineering Contradiction:

Improvetesting accuracyVSAvoidtime consumption

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system creates a digital copy of the physical product through image capture, allowing the processing units to analyze and generate testing instructions from the image data, thereby maintaining testing accuracy while eliminating time-consuming manual processes

Inventive Principle:

Principle #26Copying

3Ease of operation

If testing instructions are created for current product, then testing relevance is improved, but adaptability to product changes deteriorates

Engineering Contradiction:

Improvetesting relevanceVSAvoidadaptability to product changes

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The system provides dynamic adaptability by using image capture and processing units that can analyze current product images and generate updated testing instructions on-demand, allowing the testing system to adapt automatically to product changes without requiring manual reconfiguration

Inventive Principle:

Principle #15Dynamics

4Adaptability or versatility

If outsourcing product testing is done, then testing capability is expanded, but finding suitable testers becomes more time-consuming

Engineering Contradiction:

Improvetesting capabilityVSAvoidtime to find testers

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system eliminates the need for external human testers by enabling the product testing device to autonomously perform testing through automated image analysis and instruction generation, thereby expanding testing capability while eliminating the time required to find and coordinate external testers

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250363034A1Electronic systems generating product testing instructions and for providing automated product testing

Publication Date: 2025.11.27 RAINFOREST QA INC

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; one or more processing units configured to obtain the one or more images captured by the image capturer, determine a feature of the product based on at least one of the one or more captured images, determining 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 obtain product testing instruction that is generated automatically after the verification is performed.