17531857. DATA MODEL BASED SIMULATION UTILIZING DIGITAL TWIN REPLICAS simplified abstract (International Business Machines Corporation)

DATA MODEL BASED SIMULATION UTILIZING DIGITAL TWIN REPLICAS

Organization Name

International Business Machines Corporation

Inventor(s)

Balaji Ganesan of Bengaluru (IN)

Soma Shekar Naganna of Bangalore (IN)

Pranay Kumar Lohia of Bhagalpur (IN)

Priyanka Telang of Bengaluru (IN)

Sameep Mehta of Bangalore (IN)

DATA MODEL BASED SIMULATION UTILIZING DIGITAL TWIN REPLICAS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17531857 titled 'DATA MODEL BASED SIMULATION UTILIZING DIGITAL TWIN REPLICAS

Simplified Explanation

The patent application describes computer hardware and/or software that performs several operations related to digital twin technology. Here is a simplified explanation of the abstract:

• The system receives a data model that represents different types of information and their relationships.
• It generates a set of digital twin replicas, where each replica corresponds to a node in the data model.
• The set of digital twin replicas is used to generate simulated data that corresponds to the types of information represented by the nodes in the data model.
• The simulated data generated by the digital twin replicas is combined into a combined set of simulated data based on the relationships represented by the edges in the data model.

Potential applications of this technology:

• Industrial manufacturing: The system can be used to create digital twin replicas of physical assets and generate simulated data to optimize production processes and predict maintenance needs.
• Healthcare: Digital twin replicas of patients can be created to simulate different treatment scenarios and improve personalized medicine.
• Smart cities: The technology can be applied to create digital twin replicas of urban infrastructure and generate simulated data to optimize resource allocation and improve sustainability.

Problems solved by this technology:

• Lack of real-time data: The system provides a way to generate simulated data based on digital twin replicas, allowing for continuous monitoring and analysis even when real-time data is not available.
• Cost and scalability: Digital twin replicas can be generated and utilized at a large scale, providing a cost-effective solution for simulating complex systems.
• Risk mitigation: By simulating different scenarios, the system helps identify potential issues and risks before they occur in the real world, enabling proactive decision-making.

Benefits of this technology:

• Improved decision-making: The combined set of simulated data provides insights into the behavior and performance of complex systems, enabling better decision-making and optimization.
• Predictive analytics: By utilizing digital twin replicas and simulated data, the system can predict future outcomes and trends, helping businesses and organizations plan and prepare accordingly.
• Enhanced efficiency and productivity: The technology allows for continuous monitoring, analysis, and optimization of systems, leading to improved efficiency and productivity.

Original Abstract Submitted

Computer hardware and/or software that perform the following operations: (i) receiving a data model, the data model including nodes representing types of information and edges representing relationships between the types of information; (ii) generating a set of digital twin replicas, where a digital twin replica of the set of digital twin replicas corresponds to a respective node of the data model; (iii) utilizing the set of digital twin replicas to generate simulated data corresponding to the types of information represented by the nodes of the data model; and (iv) combining the simulated data generated by the set of digital twin replicas into a combined set of simulated data based, at least in part, on the edges of the data model.