Leveraging AI for Smart Manufacturing using MATLAB and Simulink




9:30am - 12:15pm




The industrial world is changing with the emergence of smart industry including digitization, Industrial Internet of Things (IIOT) and Industry 4.0. Today’s production machines and handling equipment have become highly integrated mechatronic systems with a significant portion of embedded software.

A major driver of smart industry is the growing amount of data. Vision sensors, electric and hydraulic drives, even production machines and power plants all collect measured data during operation. This data contains information that can be transformed into business value using predictive models and algorithms.

Smart industry depends on the growing complexity of software and an ever-increasing amount of machine data. In the long term, the evolving trend will challenge engineers to become proficient in using new software design methods and data analytics tools in order to embrace this complexity.


Focus Topics

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Adopting AI in Today’s Engineering World

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Integrating Machine Learning and Digital Twin for Predictive Maintenance

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Automating Visual Inspection & Defect Detection using Deep Learning

Focus Topics

With MATLAB and Simulink, engineers don’t need to be programming experts to build and implement high-quality software. They can focus on their technical engineering expertise for designing the functionality of technical systems.

During this seminar we will answer the top 3 engineering questions commonly asked in Smart Industry:

  1. How can you use machine data to improve production performance or predict failure?

  2. How can you apply image processing and deep learning techniques to detect anomalies?

  3. How can you deploy these AI-based systems to industrial PC, edge or cloud computing platforms?

Who Should Attend

Engineering professionals, who are currently working on or wish to implement AI for Smart Manufacturing, such as

  • Data Scientist

  • Operations Managers

  • Process Engineers

  • Production Engineers

  • Quality Control Engineers

  • Plant Managers

  • Controls Engineers



Kevin Chng

Application Engineer

TechSource Systems


Application Engineer

TechSource Systems


9:00 am

9:30 am - 10:00am

10:00 am - 11:00am

11:00 am - 11:15am

11:15 am - 12:15am


Keynote: Adopting AI in Today’s Engineering World

Integrating Machine Learning and Digital Twin for Predictive Maintenance

  • Developing data-driven and physics-based digital twins

  • Identifying key indicators for condition monitoring

  • Developing predictive models using machine learning

  • Deploying analytics to cloud/IT/embedded systems


Automating Visual Inspection & Defect Detection using Deep Learning

  • Working with large datasets, live video, and industrial cameras

  • Creating and training deep neural networks for defect detection

  • Accelerating data labelling using custom automation algorithms

  • Deploying deep learning algorithms to cloud and edge systems

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