Mixed Reality 3D Model Creation via Automated Scanning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for creating mixed reality experiences face challenges due to inaccurate or missing CAD models, costly reverse engineering, and subjective quality assurance processes, which hinder efficient implementation and accuracy in industrial settings.
Innovation Solution
A mixed reality system that uses a virtual reality and augmented reality controller to create and refine 3D CAD models of physical objects, incorporating AI-based machine learning for data parsing and categorization, and objective quality assurance through sensor data, enabling efficient procedural guidance content creation and conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CAD models are used to create mixed reality experiences, then accuracy is improved, but cost and accessibility worsen due to expensive licensing and model availability issues
Solution Approach 1:
The patent uses 3D scanning to create digital copies of physical objects, replacing the need for expensive licensed CAD models. The scanning system captures geometric data directly from the object, creating an accessible alternative to proprietary CAD models while maintaining accuracy for mixed reality applications
Solution Approach 2:
The patent replaces traditional mechanical CAD modeling processes with automated 3D scanning and photogrammetry techniques. This substitution eliminates manual model creation costs and licensing fees while producing accurate digital representations suitable for mixed reality experiences
2Adaptability or versatility
If reverse engineering is used to create 3D models, then model availability is improved, but cost and time consumption worsen
Solution Approach 1:
The system enables self-service 3D modeling through automated scanning and processing. Objects are scanned and converted into usable 3D models without requiring expert reverse engineering personnel, significantly reducing both cost and time while improving model availability for diverse applications
Solution Approach 2:
The patent performs preliminary 3D scanning and model creation before mixed reality implementation is needed. This advance preparation creates a library of ready-to-use models, eliminating time-consuming reverse engineering during deployment and enabling faster implementation
3Ease of operation
If traditional quality assurance processes are used, then human judgment is improved, but objectivity and reliability worsen due to subjective human decisions
Solution Approach 1:
The patent implements automated feedback loops where sensor data from mixed reality devices is continuously monitored and compared against expected outcomes. This objective feedback mechanism replaces subjective human judgment with reliable, data-driven quality assurance that consistently evaluates whether procedures are performed correctly
Solution Approach 2:
The system replaces manual quality inspection with automated sensor-based monitoring and analysis. IoT sensors and mixed reality device sensors objectively measure parameters such as torque, temperature, and procedural steps, eliminating human subjectivity while maintaining ease of operation through automated evaluation
4Measurement precision
If IoT sensors are used for quality assurance, then objective measurement is improved, but granularity and procedural specificity worsen
Solution Approach 1:
The patent makes mixed reality devices multi-functional by enabling them to perform both procedural guidance and quality assurance functions. The same sensors used for navigation and interaction are also utilized for objective measurement and quality evaluation, eliminating the need for separate granular sensor systems while maintaining measurement precision
Data Source
AI summary
This disclosure and exemplary embodiments described herein provide methods and systems for a blockchain-based system for managing discrepancies, assigning procedures, ensuring quality assurance, and updating digital twins with real-world information. According to an embodiment, the system uses a combination of smart contracts and a decentralized network to facilitate transparency, security, and efficiency in various industries such as manufacturing, construction, and maintenance. The system includes multiple block types, each representing a specific aspect of the process: marking up discrepancies, assigning Parallel Content Authored instructions, completing tasks with quantitative quality assurance, and updating digital twins. By leveraging the inherent advantages of blockchain technology, this system provides an auditable, tamper-proof record of the entire process while streamlining interactions between different blocks.