Industrial Challenge

We are pleased to announce that we have received seven submissions to the IDA 2016 Challenge Track. The Winner of the IDA Challenge is the attempt by Camila F. Costa and Mario A. Nascimento

Invited Keynote by SCANIA


erik Bio: Erik Malmkvist is Head of Service Support Solutions within the department Vehicle Information at Scania R&D in Södertälje, Sweden and part of Scania R&D Research Council. His team conducts research and advanced engineering within the fields of machine learning, augmented reality, cloud services and Internet of things to improve Service Operations at Scania.
staffan Bio: Staffan Persson is Head of Operational data and Analysis within the department Systems Development at Scania R&D in Södertälje, Sweden. His team turns operational data into value-adding information of product properties during product operation with methods that manage and analyse operational data from Scania’s connected vehicles and engines to improve Scania’s and its customers business.

Title: Scania’s path toward becoming data-driven

Abstract: As a tech company with more than 100 of years in the heavy long haulage business Scania is adopting to the field of Data Science. With more than 270.000 connected vehicles worldwide Scania has a golden opportunity to turn data into business advantages within our industry.

We will talk about our opportunities and challenges to manage and refine the data that we have available when turning it into a component in Scania’s modular system.

The winners of the IDA Industrial Challenge 2016 will be presented by Erik Malmkvist and Staffan Persson. The data in the IDA Industrial Challenge 2016 consist of operational data collected from Scania heavy trucks in everyday usage. Each training-example in the data set contains two classes, failure of a specific component of the Air Pressure System (APS) within 15 days or no failure. The awards are donated by Scania and go to the most interesting approach for creating a predictive model and to the best performing predictive model according to a contest specific measure. See the IDA Industrial Challenge 2016 for further details.