#142 sensXPERT about Deep Learning in Engineering and Manufacturing Industry

Exciting discussions with Dr. Phil on industrial machine
learning, algorithms, and deep learning in today's podcast
episode.

Dr. Phil Gralla and I discussed industrial machine learning, deep
learning, and algorithms. We emphasized the importance of
understanding the use case and the machines in use before delving
into advanced technologies. Not everything that is labeled AI is
actually AI. Many other techniques, such as decision trees and
support vector machines, are valuable. It's crucial to choose the
right approach for specific applications rather than following
trends. In traditional industries like composites and plastics,
there may be apprehension about adopting AI, but it should be
seen as a tool to support human decision-making, not replace it.
Utilizing available data can lead to significant efficiency
improvements, as demonstrated by a case involving robot
utilization.

Dr. Phil emphasized the significance of statistics in
decision-making by machines and the diverse tools available for
different applications. Applying AI and machine learning in
manufacturing is about supporting efficiency, not replacing human
workers.

Stay tuned for more insights from our material characterization
journey! Overall, the key is to understand the processes and make
informed decisions using the available tools and data.

If you want to discuss this in person, then let's meet at JEC
Forum DACH 2024 in Stuttgart on October 22-23, 2024 where Dominik
Riescher of sensXPERT - Optimizing Plastics Manufacturing will be
available for meetings. See Outro for details on JEC Group's
format in collaboration with AVK.

Composites Lounge will be there, too.