The session gives an overview on some  typical fields to use machine learning in production. Based on a case study (stud welding) we show typical methods like classification and root cause analysis. Further first approaches towards explainability are introduced. Finally we present open challenges regarding ML in production.


  • From data perspective various topics(problems) in production are similar
  • Necessary basics to be setup for  scaling
  • First steps towards explainability of models
  • Further challenges regarding data and Ml regarding production data



Stephan Schwarz – Manager Smart Data Processing | Mercedes-Benz AG

Stephan Schwarz ( 49 )

– Diploma in electrical engineering and automation
– Working for Mercedes for nearly 30 years
– 15 years of experience in automation and controls
– maintenance, planning and development of control systems in production
– manager production planning press shop & body shop
– worldwide launches of new models in cooperation with international partners
– working on worldwide controls standard of Mercedes-Benz

– Manager car electronics in production
– 8 years of experience in car electronics
– launching S-class in production

Since 2018: 
– manager smart data processing
– key- projects in analytics and ML in cooperation with business partners

– master program in business analytics at university of Ulm (Germany), about to finalize

May 26 @ 10:15
10:15 — 10:45 (30′)

Day 2 | 19th of May – Machine Learning

Stephan Schwarz – Manager Smart Data Processing | Mercedes-Benz AG