Marc Ball-llosera graduated in Telecommunications Technical Engineering at Polytechnic University of Catalonia (UPC), he completed a Master’s degree in Enertronics also at UPC and a Master’s degree in Big Data & Analytics at EAE Businees School.
He has been part of the Innovation teams for 14 years developing, researching and executing projects in the field of mechatronic systems for heavy duty, bus&coach and Railway – Rolling Stock.
Among his current responsibilities at Masats (last 6 years), the leadership of the predictive maintenance project for public transport access systems with success stories in Barcelona, Madrid and Singapore stands out.
Sessions
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June 06: Digital solutions and connectivity for safer and more reliable operations
Predictive maintenance: Accessibility systems for Public Transport
1. WHAT HAVE WE DONE? Masats is working on a predictive maintenance project for accessibility systems in public transport since 2017. We are currently monitoring 3 fleets: Barcelona, Madrid and Singapore. The main objective is to validate technically the system and the KPIs. Through the years our ECUs evolved from only controlling doors to also generate smart data used by the system. We created our own cloud platform and AI engines to generate alarms. Roadmap: from predictive to prescriptive. 2. WHY CAN WE GENERATE PREDICTIVE ALARMS? Masats has been designing, developing and manufacturing accessibility systems for 50 years. This gives us the know-how of all the fault modes, effects and possible causes. 3. MEASURE CBM VALUE Defined KPIs: - Reliability - Availability - Cost (LCC) Next steps: How CBM/Predictive alarms arrive to the operator? Cooperation on measure value Business model: how can we all win?
