Abstract: Existing multi-agent system are employed collaboratively, where each agent specialized in extracting entities, relations, or events from documents which is a more generalized collaborative framework without specific customizations. The disclosed method presents a collaborative multi-agent knowledge graph Retrieval-Augmented Generation (RAG) framework using a plurality of collaborative multi-agent LLMs for extracting information from a plurality of multimodal documents and constructing the unified knowledge graph to facilitate accurate and efficient query-based retrieval. A query generator agent generates a plurality of queries that aim to uncover all possible information present in the plurality of multimodal documents. A domain model is generated by a domain model generator agent based on the plurality of queries. The domain model populator agent populates the domain model with data extracted from the plurality of multimodal documents.

Abstract: Existing multi-agent system are employed collaboratively, where each agent specialized in extracting entities, relations, or events from documents which is a more generalized collaborative framework without specific customizations. The disclosed method presents a collaborative multi-agent knowledge graph Retrieval-Augmented Generation (RAG) framework using a plurality of collaborative multi-agent LLMs for extracting information from a plurality of multimodal documents and constructing the unified knowledge graph to facilitate accurate and efficient query-based retrieval. A query generator agent generates a plurality of queries that aim to uncover all possible information present in the plurality of multimodal documents. A domain model is generated by a domain model generator agent based on the plurality of queries. The domain model populator agent populates the domain model with data extracted from the plurality of multimodal documents.

Abstract: Conventional models extract chemical data through querying tables by decomposing complex user queries. This disclosure relates generally to a method and system for extraction of chemical molecules and associated target properties from text and complex tables using Large Language Models (LLMs). The disclosed method extracts a plurality of molecular property values associated with the chemical molecules, from a plurality data sources, via generating a chemical composition schema utilizing LLMs. The chemical composition schema acts as a lens to view tabular information and a text. Relevant tables are identified and tabular information comprising chemical composition instances are extracted from a plurality of documents utilizing the chemical composition schema, along with LLMs and prompting techniques. The chemical composition instances are curated and reconciled into a unified knowledge graph, which is then used for querying.

Abstract: This disclosure relates generally to systems and methods for monitoring and controlling a manufacturing process using contextual hybrid digital twin. Data pertaining to the manufacturing process is obtained from a plurality of data generation sources which is further inputted to one or more physics based models and train machine learning models such that simulated data and real time tata is obtained. Further, a gap between the simulated data and the real time data is determined and learnt. The learnt gap is further minimized and an augmented set of models are obtained. The augmented set of models along with a set of soft-sensing data is used to create the contextual hybrid digital twin for the manufacturing process. The performance of the manufacturing process is monitored and controlled using a performance analytics and decision making enablers of the contextual hybrid digital twin respectively in real time.

Abstract: Tool wear monitoring is critical for quality and precision of manufacturing of parts in the machining industry. Existing tool wear monitoring and prediction methods are sensor based, costly and pose challenge in ease of implementation. Embodiments herein provide method and system for monitoring tool wear to estimate Remaining Useful Life (RUL) of a tool in machining is disclosed. The method provides a tool wear model, which combines tool wear physics with data fitting, capture practical considerations of a machining system, which makes the tool wear prediction and estimated RUL more stable, reliable and robust. Further, provides cost effective and practical solution. The disclosed physics based tool wear model for RUL estimation captures privilege of physics of tool wear and easily accessible data from CNC machine to monitor and predict tool wear and RUL of the tool in real-time.

Abstract: A framework for assessing technical feasibility of additive manufacturing of an engineering design. This framework needs to be based on preliminary identification of key parameters that influence the decision making process. The parameters may also be customized for a particular application. Each of these parameters can be assigned weightage either relative or arrived at by paired comparison using a pre-determined minimum point method. Each of the attributes are then assigned scores which are then multiplied by the weightages assigned. The summation of all such scores on a weighted average basis indicates the potential for 3D printing of that part or assembly. It offers to select the right part to leverage the benefit of additive manufacturing. It narrows down on the ideal manufacturing process for the qualified parts and proposes to reduce subjectivity by using paired comparison of attributes. It also provides a faster assessment of technical aspects of the design.

Abstract: A system for securing a secret word during a read of the secret word from a read-only memory (ROM) is disclosed. The system includes a memory controller coupled to the ROM and a random number generator coupled to the memory controller. The random number generator is configured to generate a random number. The system further includes a number shuffler coupled to the random number generator and the memory controller. The number shuffler is configured to generate a bit read order based on the random number and the memory controller is configured to read bits of the secret word from the ROM according to the bit read order.

Abstract: Tool wear monitoring is critical for quality and precision of manufacturing of parts in the machining industry. Existing tool wear monitoring and prediction methods are sensor based, costly and pose challenge in ease of implementation. Embodiments herein provide method and system for monitoring tool wear to estimate Remaining Useful Life (RUL) of a tool in machining is disclosed. The method provides a tool wear model, which combines tool wear physics with data fitting, capture practical considerations of a machining system, which makes the tool wear prediction and estimated RUL more stable, reliable and robust. Further, provides cost effective and practical solution. The disclosed physics based tool wear model for RUL estimation captures privilege of physics of tool wear and easily accessible data from CNC machine to monitor and predict tool wear and RUL of the tool in real-time.

Abstract: A system for securing a secret word during a read of the secret word from a read-only memory (ROM) is disclosed. The system includes a memory controller coupled to the ROM and a random number generator coupled to the memory controller. The random number generator is configured to generate a random number. The system further includes a number shuffler coupled to the random number generator and the memory controller. The number shuffler is configured to generate a bit read order based on the random number and the memory controller is configured to read bits of the secret word from the ROM according to the bit read order.

Abstract: A system for securing a secret word during a read of the secret word from a read-only memory (ROM) is disclosed. The system includes a memory controller coupled to the ROM and a random number generator coupled to the memory controller. The random number generator is configured to generate a random number. The system further includes a number shuffler coupled to the random number generator and the memory controller. The number shuffler is configured to generate a bit read order based on the random number and the memory controller is configured to read bits of the secret word from the ROM according to the bit read order.

Abstract: A framework for assessing technical feasibility of additive manufacturing of an engineering design. This framework needs to be based on preliminary identification of key parameters that influence the decision making process. The parameters may also be customized for a particular application. Each of these parameters can be assigned weightage either relative or arrived at by paired comparison using a pre-determined minimum point method. Each of the attributes are then assigned scores which are then multiplied by the weightages assigned. The summation of all such scores on a weighted average basis indicates the potential for 3D printing of that part or assembly. It offers to select the right part to leverage the benefit of additive manufacturing. It narrows down on the ideal manufacturing process for the qualified parts and proposes to reduce subjectivity by using paired comparison of attributes. It also provides a faster assessment of technical aspects of the design.