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Overview

The accumulation of salt deposits on turbine blades can significantly impair turbine efficiency, resulting in a process bottleneck that increases operational costs. See how to determine the optimal  wash time to prevent bottlenecking, and how they implemented an end-to-end predictive maintenance workflow using MATLAB®.

 

Highlights:

Learn how they estimated the remaining useful life of a turbine and deployed the application so that decision makers can access up-to-date data to define optimal wash schedules.

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Speaker

Supamith Sutharojana, Application Engineer Team Lead at Ascendas Systems

Supamith and his team helps engineers across different industries with various applications like Predictive Failure Detection using Machine Learning, Data Forecasting Analytics, Powertrain Calibration and Testing, Vehicle Analysis and Validation, etc.

He specializes in the areas of Model-Based Design and Auto Code Generation with MATLAB/Simulink. He holds a bachelor’s degree from Chulalongkorn University major in Automotive Engineering. Before joining Ascendas Systems, he was an Engine Software Designer at Toyota Daihatsu Engineering & Manufacturing working in Engine Calibration and Engine software development field.

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