Schneider Electric Systems Usa, Inc.

Geometric Ltd.

Ashish Patil

Sameer Kondejkar

Bhaskar Sinha

Amitabha Bhattacharyya

Venkatesh Jagannath

Padmaja Bodanapu

Christine Zuzart

Rajesh Jain

Ajay Deshpande

Alpana Sharma

Nitin Umap

Rahul Rajadhyaksha

Rajkumar Krishnan

Systems and methods for controlling industrial process automation and control systems can automatically, through the use of machine learning (ML) models and algorithms, extract plant assets from engineering diagrams and other plant engineering data sources. The systems and methods can establish asset relationships to create a plant asset registry and build an asset hierarchy from the plant assets. The systems and methods can generate an ontological knowledge base from the plant asset hierarchy, and provide an HMI for controlling the industrial process based on the plant asset hierarchy and the ontological knowledge base.

Automatic extraction of assets data from engineering data sources for generating an HMI

Automated evaluation and extraction of information from piping and instrumentation diagrams (P&IDs). Aspects of the systems and methods utilize machine learning and image processing techniques to extract relevant information, such as tag names, tag numbers, and symbols, and their positions, from P&IDs. Further aspects feed errors back to a machine learning system to update its learning and improve operation of the systems and methods.

Machine learning analysis of piping and instrumentation diagrams

A method of automatic manufacturability evaluation of plastic models comprises generation of a likely pulling direction, recognition of common features on plastic parts, and then applying manufacturability rules The manufacturability rules can be specified and customized through user specified rule parameters and depend upon the geometric parameters of the recognized features. A system comprises a user interface for selection and customization of DFX (Design for 'X') rules for evaluation of a design. The system includes a user interface integrated with a CAD system for receiving the CAD data and displaying the results to the user. Geometry analysis engines are integrated into the system, for extracting the various features and corresponding parameters required as input to the manufacturability rules. The system further involves extensible interfaces for rules and analysis engines which allows users to write their own customized rules and engines and integrate these into the CAD based DFX evaluation system.

Manufacturability evaluation of injection molded plastic models using a CAD based DFX evaluation system

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Pune, India

Ashish Patil