18428109. METHOD AND SYSTEM FOR KNOWLEDGE-BASED ENGINEERING OF DIGITAL TWIN FOR PLANT MONITORING AND OPTIMIZATION simplified abstract (Tata Consultancy Services Limited)

METHOD AND SYSTEM FOR KNOWLEDGE-BASED ENGINEERING OF DIGITAL TWIN FOR PLANT MONITORING AND OPTIMIZATION

Organization Name

Tata Consultancy Services Limited

Inventor(s)

Sushant Shrinivas Vale of Pune (IN)

Sandipan Maiti of Pune (IN)

Subhrojyoti Chaudhuri of Pune (IN)

Sri Harsha Nistala of Pune (IN)

Sreedhar Reddy of Pune (IN)

Sivakumar Subramanian of Pune (IN)

Anirudh Makarand Deodhar of Pune (IN)

Venkataramana Runkana of Pune (IN)

METHOD AND SYSTEM FOR KNOWLEDGE-BASED ENGINEERING OF DIGITAL TWIN FOR PLANT MONITORING AND OPTIMIZATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18428109 titled 'METHOD AND SYSTEM FOR KNOWLEDGE-BASED ENGINEERING OF DIGITAL TWIN FOR PLANT MONITORING AND OPTIMIZATION

Simplified Explanation: The patent application introduces a knowledge-based approach for creating digital twins of industrial plants to monitor and optimize their operations efficiently.

Key Features and Innovation:

• Knowledge-based plant monitoring and optimization approach
• Derivation of detailed problem definition and identification of plant view of interest
• Identification of plant data of interest
• Generation of digital twin using plant data of interest
• Utilization of digital twin for plant monitoring and optimization

Potential Applications: This technology can be applied in various industries such as manufacturing, energy, and chemical plants to enhance operational efficiency and performance.

Problems Solved: The technology addresses the challenges of building digital twins for industrial plants by providing a scalable and reproducible approach that eliminates the need to start from scratch for each plant.

Benefits:

• Improved operational efficiency
• Enhanced plant monitoring capabilities
• Cost savings through optimized plant operations

Commercial Applications: The technology can be used by industrial plant operators, maintenance teams, and process engineers to streamline operations, reduce downtime, and improve overall productivity.

Prior Art: Readers can explore existing research on digital twins, plant monitoring, and optimization technologies in the industrial sector to understand the background of this innovation.

Frequently Updated Research: Stay informed about the latest advancements in digital twin technology, plant optimization strategies, and industrial automation solutions to enhance your understanding of this field.

Questions about Digital Twins in Industrial Plants: 1. How does the knowledge-based approach in this technology differ from traditional methods of building digital twins? 2. What are the key factors to consider when identifying plant data of interest for creating a digital twin?

Original Abstract Submitted

Existing approaches for building digital twins specific to industrial plants require industry domain experts, process modeling engineers, data scientists, and solution developers to spend considerable time and effort to build the right solution. This is not an easily reproducible process. For each type of industry and for each specific plant, the design, and development process must start all over, more or less from scratch and the effort needs to be reinvested. Hence this is not a scalable proposition. Method and system disclosed herein provide a knowledge-based plant monitoring and optimization approach. In this approach, for a given high-level problem statement, a detailed problem definition is derived, a plant view of interest is identified using the knowledge based approach, and in turn plant data of interest is identified. Further, a digital twin is generated using the plant data of interest, which is then used for the plant monitoring and optimization.