Predictive maintenance is increasingly being adopted, as it can reduce unplanned downtimes and maintenance costs when industrial equipment breaks. In this video series, you will see how you can use simulation models of industrial systems along with Model-Based Design to cover the entire predictive maintenance workflow. The workflow spans from data acquisition and preprocessing to design and deployment of the predictive maintenance algorithm onto a PLC and as standalone executable or web application.

Key Takeaways:

  • Frequent maintenance and unexpected failures are a large cost in many industries
  • MATLAB enables engineers and data scientists to quickly create, test and implement predictive maintenance programs
  • Predictive maintenance
    • Save money for equipment operators
    • Increases reliability and safety of equipment
    • Creates opportunities for new services that equipment manufacturers can provide

Target Audience

Manufacturing , E&E , Semincondutor, Energy Production, Utilities

Speakers’ Profile

Nor Aziah Binti Mohd Azubir
Senior Application Engineer, Techsource System Sdn Bhd

Nor Aziah is a Senior Application Engineer at TechSource Systems. Her main field of specialization is in control systems, especially for Electric Vehicle applications. Previously, she worked as a Control System Engineer for electric vehicle prototype development in Perusahaan Otomobil Nasional (Proton). She also had joined MRCB-George Kent as an Electronic Access Control (EAC) Project Engineer for the LRT3 project.

Then, she had the opportunity to work with simulation on torque vectoring for the electric vehicle's prototype development in Systems Consultation and Services (SCS), using the MATLAB/Simulink. Now, she is undergoing projects related to electric vehicles, automated driving systems using Model Based Design approach.

Aziah holds a Master of Philosophy (MPhil) in Vehicle System Engineering from Malaysia-Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia. Initially, she also holds a bachelor's degree in Electrical-Mechatronics Engineering in Universiti Teknologi Malaysia.