<Session_Outline/>
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.
<Key_Takeaways/>
- 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
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<Speaker_Bio/>
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
2010-2018
– 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
2016-02/2021
– master program in business analytics at university of Ulm (Germany), about to finalize
Day 2 | 19th of May – Machine Learning
Stephan Schwarz – Manager Smart Data Processing | Mercedes-Benz AG