Digital twin technology for existing turbine operations:• Collect, clean, transform and validate data, part of data pre-processing• Feature selection (RF, Stepwise first order) and Feature extraction using machine learning technique and domain knowledge• Presents data in the form of charts, plots and tables for immediate reference –Descriptive analysis• Model validation using K-fold Cross Validation, Error metrics. Identify effect(trend) of individual variables through… Show more Digital twin technology for existing turbine operations:• Collect, clean, transform and validate data, part of data pre-processing• Feature selection (RF, Stepwise first order) and Feature extraction using machine learning technique and domain knowledge• Presents data in the form of charts, plots and tables for immediate reference –Descriptive analysis• Model validation using K-fold Cross Validation, Error metrics. Identify effect(trend) of individual variables through sensitivity analysis• Develop machine learning predictive models (Linear, Random Forest, MARS, Stepwise first order, KNN, PLS) to accurately predict the behavior of turbine process parameters• Work closely with software development teams to ensure accurate integration of machine learning models into firm platforms.Development of Valves and Actuator Localization:• R&D for Emergency Stop Valve• Localization of hydraulic Actuator for Emergency Stop and Control Valves• Project Management for the New Project Development• Failure mode effects analysis (Design and Manufacturing)• Vendor Qualification and process audit Show less

Design Engineering for the Turbine Components:(Mitsubishi Hitachi Power Systems)• Layout and general arrangement drawings for the core machine• Generic models and their assembly based on the variable parameters• Material selection based on the requirements and the usage type• Part of Design Failure Mode Effect Analysis (DFMEA) team for the evaluation of the design and detaileddesign.