REGISTRATION VIA EVENTBRITE
The Data Lounge will take place via Zoom. For the open space discussion, we will switch to Wonder. The links will be provided after a registration via Eventbrite.
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Agenda
6 PM – Welcome words by BREMEN.AI // Sven Thies, Coordinator of the Data Lounge
Ralph Grothmann // Principal Consultant for Predictive Analytics // SIEMENS AG
Ralph Grothmann graduated in economics from the University of Bremen in 1999 with focus on financial and investment analysis, portfolio management and econometrics followed by a PhD on „Multi-Agent Market Modeling based on Neural Networks“.
Then, his professional path led him to Munich where he joined the Siemens AG, Corporate Technology. There he worked in the Business Analytics and Monitoring department. Since 2018, he has now been part of the Digital Enterprise and Services Group at Siemens Germany, acting as Principal Consultant for Predictive Analytics.
His research interests include applications of time-delay recurrent and feedforward neural networks for time series forecasting. He is also a member of the scientific advisory board of the German Society of Operations Research (GOR).
6.10 PM – Keynote: Forecasting Customer Demand with Deep Neural Networks – A Data Analytics Use Case from the Siemens Digital Industries Manufacturing Plant in Erlangen
„Accurate forecasts of the customer demand are key for a successful supply chain management. In the production process, the material and capacity can be planned in accordance with the expected demand. Delivery capability and reliability can be ensured. We apply deep feedforward neural networks to explore demand patterns in the sales time series of more than 1.000 products from the area of industrial controls. The models use autoregressive as well as seasonal components. In addition, macroeconomic factors are used to explain the demand fluctuations. The approach incorporates an automated model building, training and evaluation scheme, all of which are implemented in a scalable cloud solution. The forecasts are combined with uncertainty measures to derive decision support for the demand planning department at the Siemens equipment manufacturing plant Erlangen (GWE). We benchmark the forecast accuracy of our approach with state-of-the-art machine learning methods.“
The session will be recorded and uploaded on our YouTube channel.
6.50 PM – Ask The Expert
Once the presentation is finished, you will have the chance to engage with our speaker and ask any questions regarding the talk.
From 7 PM – Open Space Discussion
Afterwards, we would like to invite you to an open space discussion via Wonder. Wonder is a virtual space where people can meet and talk. The tool allows to move freely between conversations and areas.
To prepare this virtual space for the discussion, we would appreciate your input! Feel free to add any topics you would like to discuss, whether it is to talk about the presented case in detail or your own ideas and experiences regarding data analytics.
Drop your suggestions here! The poll is open till 3PM, February 23.
What is an open space discussion?
Open Space allows everyone to engage in discussion with others whom they may not normally have the opportunity to get in touch to. You may either stick to a certain discussion all along or move freely between the separate discussion. Only few principles apply:
- Whoever comes are the right people.
- Whatever happens is the only thing that could have.
- Whenever it starts is the right time.
- Whenever it’s over, it’s over.
- Wherever it happens is the right place.
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