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#datalift use cases in production for manufacturing

Let's break the proof-of-concept cycle and productionize data analytics and machine learning.

With #datalift, we show you how business and government can scale the data economy now.




In this post, we highlight use cases in production presented by AI Guild members who are experts in deploying for manufacturing applications.





ML for factory production excellence. Using machine data to optimize


Presented by Dr. Edith Chorev, Head of Data Science, FactoryPal

Moderated by Dr. Irem Nasir, Machine Learning Scientist, Kineo.ai


Edith’s background is in the field of system and computational neuroscience. She has a Ph.D. from the Hebrew University of Jerusalem. She has worked as a researcher both at the Humboldt University and at the MPG for experimental medicine, focusing on how information is coded by neural networks and neural network dynamics. Since then she worked as a freelance data scientist mainly with biotech early ventures and is now heading the data science efforts in FactoryPal.


She explores solutions using machine and process data in order to find the optimal settings for different manufacturing lines, with a focus on continuous manufacturing with batch processes, where machine settings change often to adapt to variation in production specifications. Edith shows us how to help manufacturers improve efficiency by addressing the challenges in scaling and automatization.


Watch the recorded live session here:


Statistical Health Monitoring of Manufacturing Machines - From Sensors to Insight to Deployment


Presented by Badru Stanicki, Data Scientist & Instructor, Propulsion Academy Zürich

Moderated by Felix Großmann, Junior Data Scientist, allmyhomes GmbH


With a master's in Physics, Badru got into scientific programming and data science during his time at the German Aerospace Center in Spain. After working several years in research, he moved into Data Science first as a student and then as a team member at Propulsion Academy Zürich, offering Full-Stack Coding, Data Science, Python, and AI Courses for Individuals and Corporates in Zurich, Munich, or Remote.


Watch the recorded live session here:


Quality inspection in manufacturing. The TUBA AI machine vision toolkit


Presented by Mahmoud AbdelAziz, Founder & CEO, DevisionX

Moderated by Andrés Prada González, Computer Vision Engineer, Footprint Technologies GmbH


Mahmoud AbdelAziz is a senior expert for machine vision in manufacturing, with 8+ years of spearheading projects & products in many fields of Machine Vision, Robotics, Artificial Intelligence, Smart Manufacturing, Quality Control, and Software Development. He started his first startup QEYE that builds Machine vision solutions for the textile industry. Then, he founded DevisionX for building quality inspection systems using a mix of Machine Vision & AI that can be applied in many industries. Also, he was a partner at Digified, which is using computer vision and AI in FinTech for digital identity verification.


He discusses the evolution of quality inspection processes, that are not only being automated but also leveraging AI. Mahmoud shows us how to enable manufacturing experts to solve their daily challenges using AI & Machine Learning without experience & without coding.


Watch the recorded live session here:


Keen to hear more about DevisionX and their solution?

You will find them at the Expo area on #datalift No 5

Join #datalift No 5


Friday, 28 May at 11.00 CEST. 500 seats for 180 minutes on how to close the gap to deployment. Here's what we offer you:

  • Take part in the discussion with AI Guild members about challenges and solutions for the deployment of data analytics and machine learning solutions.

  • Enjoy peer-to-peer networking in the 60+ minutes via chat and video.

  • Check out the virtual expo and find your preferred partner to get first-hand information via one-on-one interactions.

All that is just one click away. Live. Register here







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