Manufacturing Task Analysis Using Images and Tool Signals
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Solution Overview
Problem
Existing technologies face challenges in automatically analyzing tasks in manufacturing processes, particularly for indented products where task sequences and product designs differ significantly, making it difficult to accurately determine task completion.
Innovation Solution
An analysis device that receives images from an imaging device and detection signals from tools used in manufacturing tasks, utilizing end determination data to accurately determine the completion of each task based on consistent product states and signal patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual checks are used to determine task completion, then accuracy of task analysis is improved, but labor costs and time consumption increase
Solution Approach 1:
The patent replaces manual visual inspection with an automated analysis device that uses imaging devices to capture images and AI algorithms to analyze task completion. The system automatically compares captured images with reference images to determine whether tasks are completed, eliminating the need for manual checks while maintaining high accuracy.
Solution Approach 2:
The system enables self-service by allowing the manufacturing system to automatically monitor and determine task completion without external human intervention. The analysis device continuously captures images and autonomously determines task status, allowing the production line to self-regulate and report completion status automatically.
2Productivity
If automated analysis is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The analysis device is designed as a universal system that can handle multiple types of tasks and products through configurable reference images and AI algorithms. Rather than requiring separate systems for each task type, a single multi-functional device adapts to different manufacturing scenarios by loading appropriate reference data and analysis parameters.
Solution Approach 2:
The patent introduces an intermediary analysis device that sits between the manufacturing process and the control system. This intermediary component simplifies the overall system architecture by centralizing the complex image analysis and task determination logic in a dedicated unit, rather than distributing complexity across multiple components.
3Adaptability or versatility
If traditional task monitoring methods are used, then system complexity is kept low, but adaptability to different products and task sequences deteriorates
Solution Approach 1:
The system implements dynamic adaptability by allowing the reference images and analysis parameters to be updated and reconfigured for different products and task sequences. The AI algorithms dynamically adjust to new task types by learning from reference data, enabling the system to adapt to varying manufacturing requirements without physical reconfiguration.
Solution Approach 2:
The patent utilizes parameter changes to achieve adaptability by modifying analysis parameters, reference images, and threshold values based on the specific product and task being monitored. Rather than changing the physical system structure, the solution changes software parameters and data inputs to accommodate different manufacturing scenarios.
Data Source
AI summary
According to one embodiment, an analysis device performs an analysis related to a plurality of tasks of a manufacturing process. The analysis device receives an image when each of the plurality of tasks is performed. The analysis device receives the images from an imaging device acquiring the images. The analysis device receives a detection signal from a tool used in at least one of the plurality of tasks. The detection signal is detected by the tool. The analysis device refers to end determination data for determining an end of each of the plurality of tasks. The analysis device determines the end of each of the plurality of tasks based on the images, the detection signal, and the end determination data.