Automated Assembly Verification Using Image Recognition
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Solution Overview
Problem
Manual assembly of consumer products often results in improper assembly due to difficulties in following written instructions, incorrect selection of components, and lack of verification of proper parts, leading to errors and increased costs.
Innovation Solution
A computer program product and system that manages the assembly sequence by using unique identifiers to verify the presence and correct positioning of components, providing instructions in multiple languages, and sequentially guiding the assembly process, with the ability to detect and correct errors, and collect necessary components for each step.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If written instructions are provided for assembly, then assembly guidance is available, but consumers may ignore or fail to follow them resulting in improper assembly
Solution Approach 1:
The system uses image recognition technology to capture photos of the assembly area and automatically detects the presence and positioning of components. This feedback mechanism replaces manual instruction following with automated verification, where the system tells the consumer what to do next based on what it detects, ensuring proper assembly without requiring the consumer to read or understand complex instructions.
Solution Approach 2:
The system enables the assembly process to guide itself by automatically detecting components and determining the next assembly step. The consumer simply needs to follow the system's prompts rather than independently interpreting written instructions. The system serves itself by using image analysis to track assembly progress and provide contextualized guidance.
2Reliability
If consumers verify presence of proper parts manually, then component correctness can be ensured, but this step is often overlooked or not properly followed
Solution Approach 1:
The system replaces the manual mechanical verification process with an automated optical detection system. Instead of consumers physically checking part numbers or visually inspecting components, the image recognition system automatically identifies components through photograph analysis, ensuring accurate verification without adding manual steps that consumers might skip.
Solution Approach 2:
The system performs component verification in advance before assembly steps are executed. By detecting and verifying the presence of required components prior to each assembly operation, the system prevents errors before they occur, rather than requiring consumers to perform verification checks that may be overlooked during the assembly process.
3Adaptability or versatility
If multiple bolts and nuts are provided for assembly, then proper fastening is enabled, but consumers may choose incorrect components leading to rework
Solution Approach 1:
The system provides real-time feedback to the consumer about which specific component should be used next by analyzing the assembly context through image recognition. Rather than allowing free selection from multiple similar components, the system identifies the correct bolt or nut based on the detected assembly state and guides the consumer to select the appropriate component, ensuring precision while maintaining the flexibility of having multiple component options available.
4Loss of information
If conventional printed instructions are used, then assembly guidance is provided, but consumers find them tedious and difficult to reference
Solution Approach 1:
The system transitions from static printed instructions to dynamic, context-aware digital guidance. The instructions adapt in real-time based on what the system detects in the assembly area, providing only the relevant information needed for the current step. This dynamic approach eliminates the need for consumers to search through lengthy printed manuals, as the system actively provides targeted guidance based on the current assembly state.
Solution Approach 2:
The system introduces a digital intermediary layer between the consumer and the assembly instructions. Instead of directly reading printed instructions, the consumer interacts with the system through a user interface that translates the complex assembly information into simple, context-relevant prompts. This intermediary processes the image data and converts it into user-friendly guidance, making the instruction-following process much more accessible.
Data Source
AI summary
A computer program product, apparatus and system are disclosed for managing a manual assembly sequence by electronically referencing unique identifiers associated with physical components to be assembled in the sequence. Certain embodiments facilitate management of an assembly of a consumer product. In one embodiment, RFID tags are used as unique identifiers. Such embodiments may use RFID tags to determine the presence of the components before each assembly step in the assembly sequence and to determine that the components are being assembled in sequence. Other embodiments determine whether the components are properly assembled after being assembled, that the distance between the components falls within a predetermined range, and/or that the components for an assembly steps is properly orientation with respect to other components.