PreSense – AI-based Predictive Maintenance at SENEC
In order to improve product quality, SENEC GmbH has launched a project to establish a Predictive maintenance system. Based on frequently repeating failure patterns and reasons for and reasons for failure in electricity storage systems, the underlying assumption is that these patterns can be predicted using statistical analysis and AI methods, these patterns can be predicted to a certain extent. In order to fully undertake this research, SENEC is collaborating with IT-Sonix GmbH together.
In the presentation we would like to introduce the technical approach and inform about the current status of the project.
Bio Armin Geisler
2009 – 2013: Study International Business Management Studies, Hanzehogeschool Groningen, Degree: Bachelor of Business Administration
2013 – 2014: Project Management Trainee, Festool Group GmbH & Co. KG, support and further development of the CRM system „TTS-Connect“.
2014 – 2015: Study of International Accounting, University of Strathclyde Glasgow, Degree: Master of Science
2015 – 2017: M&A Analyst, Translink Corporate Finance, execution and analysis of M&A transactions
2017 – 2020: Global Business Analyst, Konica Minolta Business Solutions Europe, Implementation of a pan-European BIS structure with dashboards, analytics and data science projects
Since 2021: Senior Business Analyst, SENEC GmbH, establishment of the BI area within SENEC, Management of the „PreSense“ project
SENEC GmbH, Leipzig, Germany
2004 – 2010: Studies of Meteorology, University of Leipzig, Degree: Diplom.
2011 – 2013: Research associate, Deutscher Wetterdienst – support of worldwide users of the German weather forecast model Cosmo
2013 – 2021: Research Associate, Center for Geoinformation of the German Armed Forces – Technical support of worldwide Bundeswehr missions with weather model forecasts
Since 2021: Data Analyst, Senec GmbH – Automation of statistical evaluations of company-wide complaints, establishment of the predictive maintenance system „PreSense“