AI for Predictive Maintenance – Opportunities and Challenges in Prognostics of Trucks and Buses
An increasing number of connected vehicles and new business models have pushed for a more intelligent AI and machine learning-based solution for predictive maintenance rather than just corrective or preventive actions.
Traditionally trucks’ maintenance usually involved either a corrective action (fix it when it is broken) or Preventive action (Scheduled maintenance) on some components such as filters and brakes and the oil change intervals. However, with increased number of connected vehicles (over half a million) and business requirements on selling trucks as a service and a transport solution rather just a normal vehicle sale has pushed for more intelligent AI and Machine learning based predictive maintenance solution. Moreover, with goal of reducing emissions and advancement of newer technologies on electromobility, autonomous solutions and hydrogen fuel cells with more complex and expensive components have put even more emphasis on the need for advanced predictive maintenance approach.
This seminar will provide a background and business contexts on the need for the predictive maintenance in transportation industry. It will also go through some of the current work and AI and ML models with fully integrated CICD pipeline and show results of a model in real life use. Finally, it will present opportunities for the future work.
Speaker: Dr. Atabak Taheri, Volvo AB
Dr. Atabak Taheri has been in three year active journey in Volvo AB in the area of prognostics and predictive maintenance in various roles of specialist, Product owner, Tech lead and Group was a lecturer for industrial candidates wanting to improve their knowledge and career in the areas of Machine learning, predictive maintenance and ERP. He has gotten his PhD from the University of Strathclyde on Ship machinery Predictive maintenance.
An increasing number of connected vehicles and new business models have pushed for a more intelligent AI and machine learning-based solution for predictive maintenance rather than just corrective or preventive actions.
Traditionally trucks’ maintenance usually involved either a corrective action (fix it when it is broken) or Preventive action (Scheduled maintenance) on some components such as filters and brakes and the oil change intervals. However, with increased number of connected vehicles (over half a million) and business requirements on selling trucks as a service and a transport solution rather just a normal vehicle sale has pushed for more intelligent AI and Machine learning based predictive maintenance solution. Moreover, with goal of reducing emissions and advancement of newer technologies on electromobility, autonomous solutions and hydrogen fuel cells with more complex and expensive components have put even more emphasis on the need for advanced predictive maintenance approach.
This seminar will provide a background and business contexts on the need for the predictive maintenance in transportation industry. It will also go through some of the current work and AI and ML models with fully integrated CICD pipeline and show results of a model in real life use. Finally, it will present opportunities for the future work.
Speaker: Dr. Atabak Taheri, Volvo AB
Dr. Atabak Taheri has been in three year active journey in Volvo AB in the area of prognostics and predictive maintenance in various roles of specialist, Product owner, Tech lead and Group was a lecturer for industrial candidates wanting to improve their knowledge and career in the areas of Machine learning, predictive maintenance and ERP. He has gotten his PhD from the University of Strathclyde on Ship machinery Predictive maintenance.
