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Utilizing AI for Gaining Efficiency in Production Processes and Improving Product Quality with MATLAB


This webinar is Part 3 of the Artificial Intelligence in Industrial Automation and Machinery series.

Many industries are looking to AI to deliver increased efficiency of production processes and improving product quality. The addition of AI in manufacturing leads to increased complexity in the workflow, from design to production. The digital transformation in manufacturing resulted in many production lines instrumented with sensors, but process engineering teams often lack the specialized skills required by AI and struggle to apply analytical models to the process data. This presentation provides an overview of the MATLAB and Simulink platforms and tools that empower process engineers to employ statistical, signal processing and machine learning approaches to improve the quality of noisy process data, apply anomaly detection to monitoring manufacturing processes and quality, and increase efficiency from improved monitoring. 


  • Learn about the three main objectives in applying AI to manufacturing
  • Apply advanced preprocessing and feature engineering to build robust models of manufacturing processes
  • Empower operators and processes engineers with Apps and dashboards

About the Presenters

Rareș Curatu is responsible for driving the business development of the Industrial Automation & Machinery industry for MathWorks in EMEA. Working with companies in energy generation and transmission, machine building, and automation equipment manufacturing, Rareș helps them to adopt Industry 4.0 and Industrial IoT workflows based on MATLAB and Simulink.

Bernhard Suhm is the product manager for Machine Learning at MathWorks. He works closely with customer facing and development teams to address customer needs and market trends in our machine learning related products, primarily the Statistics and Machine Learning toolbox. Prior to joining MathWorks Bernhard led a team of analysts consulting call centers on optimizing the delivery of customer service. He also held positions at a usability consulting company and Carnegie Mellon University. He received a PhD in Computer Science specializing in speech user interfaces from Karlsruhe University in Germany.

Francesca Perino is Principal Application Engineer at MathWorks. She focuses on enabling MathWorks customers to be successful in their adoption and use of MATLAB platform to solve their numerical modelling and AI challenges with cutting-edge technology, tools and methods. She has expertise in data ingestion and processing, software design and application development in MATLAB, big data for enterprise-scale predictive analytics.

Before MathWorks, she spent few years working as research engineer and software developer. She holds a M.Sc. in Physics specializing in numerical methods and statistics in atmospheric science from Torino University in Italy.

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