International business machines corporation (20240211659). CLASSIFICATION-BASED PRODUCT DESIGN USING VIRTUAL DIGITAL TWIN MODELS simplified abstract
Contents
CLASSIFICATION-BASED PRODUCT DESIGN USING VIRTUAL DIGITAL TWIN MODELS
Organization Name
international business machines corporation
Inventor(s)
Sarbajit K. Rakshit of Kolkata (IN)
Sathya Santhar of Ramapuram (IN)
Sridevi Kannan of Katupakkam (IN)
CLASSIFICATION-BASED PRODUCT DESIGN USING VIRTUAL DIGITAL TWIN MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240211659 titled 'CLASSIFICATION-BASED PRODUCT DESIGN USING VIRTUAL DIGITAL TWIN MODELS
Simplified Explanation: The patent application describes a system and method for automatically generating product designs by converting a digital twin model of a physical product into a virtual digital twin model, collecting user interaction data and sentiment data from virtual interactions, and using machine learning to generate different secondary designs based on user groups.
Key Features and Innovation:
- Conversion of digital twin model to virtual digital twin model
- Collection of user interaction data and sentiment data
- Utilization of machine learning predictive model to generate secondary designs for different user groups
Potential Applications: This technology can be applied in various industries such as product design, manufacturing, virtual reality, and user experience research.
Problems Solved: This technology addresses the challenge of efficiently generating diverse product designs based on user interactions and sentiments.
Benefits: The system allows for the creation of customized product designs tailored to different user groups, leading to increased user satisfaction and potentially higher sales.
Commercial Applications: The technology can be utilized by product design companies, manufacturers, and virtual reality developers to enhance user engagement and optimize product designs for specific target markets.
Prior Art: Prior art related to this technology may include research on digital twin models, user interaction analysis, sentiment analysis, and machine learning in product design.
Frequently Updated Research: Stay updated on advancements in digital twin technology, machine learning algorithms for predictive modeling, and user interaction analysis techniques.
Questions about product design innovation: 1. How does this technology improve the product design process? 2. What are the potential implications of using machine learning in generating product designs?
By providing a detailed summary of the abstract and highlighting the key features, potential applications, problems solved, benefits, commercial applications, prior art, and frequently updated research, this article offers a comprehensive understanding of the innovative technology for automatically generating product designs.
Original Abstract Submitted
a system and method of automatically generating product designs is provided. in embodiments, methods include converting a digital twin model of a physical product having a primary design to a virtual digital twin model enabling user interactions with features of the virtual digital twin model in a virtual environment; collecting user interaction data generated from virtual interactions of users with the features of the virtual digital twin model in the virtual environment; generating sentiment data indicating a sentiment of the users associated with the virtual interactions of the users with the features of the virtual digital twin model; and inputting the user interaction data, the sentiment data, and different groups of the users into a trained machine learning (ml) predictive model, thereby generating, as an output of the ml predictive model, a different secondary design of the physical product for each of the different groups of users.
