Ralf Klinkenberg, RapidMiner

Predictive Big Data Analytics in the Process Industry: Predicting and Preventing Machine Failures, Critical Situations, and Product Quality Issues as Early as Possibly Using Machine Learning from Structured and Unstructured Data

The presentation describes predictive analytics use cases in the chemical industry, the steel industry, and other production processes:

• Predicting and preventing machine failures before they happen
• Predicting critical situations as early as possible and providing recommendations for preventing them and/or fixing them
• Predicting product quality issues as early as possible in the process in order to improve product quality and cost

Ralf Klinkenberg is the co-founder and head of funded R&D of the Predictive Analytics software provider RapidMiner. He has more than 20 years of experience in data mining, text mining, predictive analytics, machine learning, big data and applications in many industries. In 2001, he founded the open-source project RapidMiner with Dr. Ingo Mierswa and Dr. Simon Fischer, and in 2007 he founded the company RapidMiner with Dr. Ingo Mierswa.