An important goal in the implementation of an industry 4.0 strategy is the optimization of production to further increase the quality of the produced product. This also depends on the optimal setting of many production parameters, the early detection of possible deviations and their elimination. The aim of the project is to further improve the quality of the intermediate product by optimizing the setting of process steps and parameters as well as further recognition of the interrelationships in the complex production process at the plant in Schwabmünchen. This is achieved by a data analysis of the production parameters, sensor data, test protocols and their interdependencies. Forecasts and rules for the production can be created, due to the results of tis data evaluation.


  • Application and adaptation of relevant Big Data practices
  • Discovery of patterns in data as a result of data analysis
  • Development of data models with predictive power for the production process
  • Further increase in product quality
  • Challenges and tasks:
  • The collection of data from the relevant systems and their linkage & understanding of the process chain and quality inspection
  • The application of appropriate data modeling methods

“From working with SDIL and IBM, we have learned a lot about data preparation and data analytic” says Marcel Röcker, from OSRAM GmbH in Schwabmünchen. “In addition, the information we have acquired helps us for the next step in data analytic.”

Data Innovation Community

Industrie 4.0

Project Partners


Contact Person

M. Röcker, m.roecker@osram.com

P. Kiradjiev, kiradjiev@de.ibm.com

Project Duration

März 2017 – Mai 2017