Machine Vision Tool Selection via Image-Guided Job Flow
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Solution Overview
Problem
Users face challenges in selecting appropriate machine vision tools within software suites, leading to inefficiencies and inaccurate results due to extensive navigation and subjective tool selection, which can result in defective products being missed or incorrectly flagged.
Innovation Solution
An interactive graphical user interface (GUI) analyzes a portion of an image to determine a corresponding tool for processing, automatically recommending the appropriate tool for a machine vision job, reducing the need for manual navigation and subjective selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually navigate through the machine vision software to select tools, then they can choose from a comprehensive suite of tools, but it requires extensive time and multiple navigation interactions
Solution Approach 1:
The system performs self-service by automatically analyzing the image and recommending appropriate tools without requiring manual user navigation. The application autonomously identifies image features and matches them with suitable machine vision tools, eliminating the time-consuming manual selection process while maintaining access to the comprehensive tool suite.
Solution Approach 2:
The system performs preliminary action by pre-analyzing the image content and preparing tool recommendations before the user needs to make a selection. The automatic image analysis and tool matching occur in advance, so when the user reviews the recommendations, the appropriate tools are already identified and ready for selection, significantly reducing the time required.
2Ease of operation
If users manually select tools from a large list, then they have control over tool choice, but they may inadvertently select the wrong tool or make subjective errors
Solution Approach 1:
The system implements feedback by automatically analyzing the image content and providing data-driven tool recommendations based on actual image features rather than subjective user judgment. The feedback loop involves the system examining the image, identifying relevant characteristics, and recommending tools that are objectively suited to those characteristics, thereby improving selection accuracy and reducing errors.
Solution Approach 2:
The system acts as an intermediary between the image and the tool selection process. Rather than directly connecting user intent with tool selection, the automatic image analysis serves as an intermediary that objectively evaluates the image content and mediates the selection of appropriate tools, reducing the risk of human error and subjective mistakes.
3Productivity
If the machine vision job uses inappropriate tools, then the system can still execute the job, but defective products may pass inspection or good products may be incorrectly flagged
Solution Approach 1:
The system performs preliminary action by automatically analyzing images and recommending appropriate tools before the inspection job is executed. This pre-analysis ensures that the correct tools are selected in advance, preventing the execution of jobs with inappropriate tools that would lead to inspection errors or reduced manufacturing precision.
Data Source
AI summary
Methods and systems for facilitating selection of tools for one or more machine vision jobs are disclosed herein. An example method may be performed by one or more processors and includes displaying, via a display screen, an interactive graphical user interface (GUI) of an application, the application configured to generate job scripts for imaging devices to execute and the application operating in a job construction mode. The method also includes displaying an image within the GUI and detecting a selection of a portion of the image. The method further includes analyzing the portion of the image to determine a corresponding tool for processing the portion of the image and adding the corresponding tool to a job flow of the machine vision job.