AR Assembly Procedure Generation from CAD Models
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Solution Overview
Problem
Current assembly and integration of testing preparation procedures for equipment on factory/testing floors are prone to human error due to the critical nature of sensor placement, which is time-consuming and costly to rectify.
Innovation Solution
A method utilizing a procedure generation engine to process computer-aided design models, determine sensor locations and orientations, and generate augmented reality assembly, integration, and testing preparation procedures, leveraging AI and ML algorithms to automate the process and reduce human error.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual sensor placement procedures are used, then flexibility in handling complex sensor configurations is maintained, but human error increases and time consumption increases
Solution Approach 1:
The system performs preliminary actions by automatically generating complete sensor placement procedures before the actual installation. The procedure generation engine processes CAD models, determines optimal sensor locations and orientations, and creates step-by-step instructions in advance, eliminating the need for manual planning and reducing on-site decision-making time while ensuring consistent, error-free placement procedures.
Solution Approach 2:
The system creates a digital copy of the sensor placement procedure through automated generation from CAD models. This virtual procedure template includes all necessary instructions, sensor locations, and orientations, which can then be replicated consistently without human error. The generated procedures serve as reusable templates that can be applied to multiple testing scenarios.
2Productivity
If automated procedure generation is implemented, then time consumption is reduced and consistency is improved, but system complexity increases
Solution Approach 1:
The procedure generation engine is designed as a universal system that handles multiple testing scenarios and equipment types through a single integrated platform. It processes various CAD model formats, generates procedures for different sensor types, and adapts to different testing requirements without requiring separate specialized tools for each application, thereby managing complexity through consolidation.
Solution Approach 2:
The system introduces an intermediary layer between the CAD models and the actual sensor placement operations. This intermediate procedure generation layer translates complex CAD data into simplified, step-by-step installation instructions, shielding the user from underlying system complexity while providing straightforward actionable guidance. The intermediary handles the computational complexity internally while presenting simple outputs to users.
Data Source
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AI summary
A method is provided. The method is implemented by a procedure generation engine executing on a processor. The method includes processing a computer-aided design model of a candidate under test to determine at least sensor locations and automatically determining augmented reality interactivity between the candidate under test and the sensor locations. The method includes determining a sensor list identifying and corresponding sensors to the sensor locations and generating an augmented reality assembly, integration, and testing preparation procedure based on the sensor locations, the augmented reality interactivity, and the sensor list.