Knowledgefeed vol. 27: Deep Learning for Predictive Quality & Predictive Maintenance

Get ready for our 27th Knowledgefeed featuring characteristics of Industrial AI and how state of the art deep learning methods can be applied to solve complex problems and bring more value to companies.

Talk (duration 60 – 90 mins): Predictive Maintenance, Predictive Quality & Visual Inspection

By Simon Stiebellehner -Head of AI, craftworks & Daniel Ressi -Data Scientist, craftworks

Artificial Intelligence plays a major role in Industry 4.0 and more industrial companies than ever are starting to utilize their data to gain value and insights. The industrial domain offers very promising opportunities but this potential also comes with very specific requirements and challenges. This talk gives insights into the characteristics of Industrial AI and how state of the art deep learning methods can be applied to solve complex problems and bring more value to companies. Based on real use cases, three common areas of Industrial AI and the applied modelling approaches will be presented:

1. Predictive Maintenance: Can faults of machines be predicted in advance?
2. Visual Inspection: Can computer vision automatically assess the quality of products?
3. Predictive Quality: Can product defects be predicted in advance and prevented in future?

Simon is a Head of AI at craftworks and lecturerin statistics and digital marketing at WU Wien and FH Wien. After having completed his Bachelorin Information Systems, he gained diverse industry experience,ranging from Microsoft to global players of the consulting industry. Subsequently, Simon obtained his Masters degree from University College London (UCL), specializing in Machine Learning and Data Science. Afterwards, he was a doctoral candidate and research associate, conducting research at the intersection of Neural Probabilistic Language Models and Recommendation Systems in a Real-Time Bidding context.

LinkedIn: https://www.linkedin.com/in/simonstiebellehner/ Website: https://craftworks.at

Daniel is a Data Scientist at craftwork and develops customized deep learning solutions for industrial clients. His background is in Biomedical Engineering, where he focused his research on Recurrent Neural Networks for Brain Machine Interfaces (BSc, TU Graz) and for Computational Neuroscience (MSc, Imperial College London). Craftworks develops award-winning artificial intelligence solutions for industrial enterprises. Their customers range from the automotive to the paperindustry and everything in between.

LinkedIn: https://at.linkedin.com/in/daniel-ressi Website: https://craftworks.at

As always: grab the opportunity to ask our lecturers questions, discuss your ideas and of course enjoy the company of some interesting folks!

Please do not hesitate to present your own projects, ideas or thoughts. We are more than gladly sharing the stage with you! Please refer to our blog-post / Discussion entry for further details:

https://viennadatasciencegroup.at/2016/09/06/power-to-the-people/

Looking forward to meeting you at the Knowledgefeed!

Stay tuned and RSVP on our Meetup:

https://www.meetup.com/Vienna-Data-Science-Group-Meetup/events/258669227/