Walking the Gemba in the Omniverse
NVIDIA Omniverse - Designing, Optimizing and Operating the Factory of the Future
Connected Systems Reveal Data Value
The multitude of data that technology captures can be invaluable in uncovering new efficiencies or fixing roadblocks. Between 60% and 70% of data within an enterprise, however, goes unused. Most plants have the tools and data at their fingertips, but realizing their value requires some consideration in the area of connected work. Connected-worker technology provides tools that connect people, data, and systems so that organizations can become more adept at decision making, have increased process visibility, and can ensure more agile operations.
Collaboration requires presence sensing
The challenge of automation has always been to keep people safe while trying to produce more product in the same footprint. The faster a machine runs, the more physical space is required to guarantee that, if something goes wrong, the machine has enough time to come to a complete and safe stop before potentially making contact with humans or other machines around it. Traditionally, this would involve a physical cage around the piece of automation. This cage could take the form of a frame with either polycarbonate or expanded steel (fence) panels.
Made to physically defend a person from getting too close, these types of guarding systems also take up a lot of real estate. For this reason, they are not well-suited to a cobot application where we don’t want the new automated device taking up any more space than the human it is replacing.
The technology required to respond to this need for an ever tighter operating envelope has advanced dramatically, especially over the past two or three years. While we will delve into that momentarily, it is important to note that the robot manufacturers, in addition to coming up with new ways to sense the presence of people in proximity to the robot, have had to come up with ways to safely limit the range of operation to be inside the normal operating range of the robot.
Gaining an Edge on Line Control
Edge control provides access to real time OEE and information visualization that changes the value calculation. With edge control, end-users can easily tie together existing equipment, other legacy controllers and new external sensing. The combined raw data can be analyzed at the edge to generate information needed by operators to take fast informed action, and it is the foundation for more advanced production line integration, with the ultimate goal of insight-driven and adaptive operation.
Intel Accelerates AI for Industrial Applications
The human eye can correct for different lighting conditions easily. However, images collected by camera can naturally vary in intensity and contrast if background lighting varies as well. We’ve seen scale challenges observed by factories trying to deploy AI for defect detection based on the exact same hardware, software and algorithm deployed on different machines on the factory floor. Sometimes it took months for factory managers and data scientists to find out why they were getting great results on one machine with high accuracy, low false positive and false negative rates, while on the next machine over the AI application would crash.
Intelligent edge management: why AI and ML are key players
What will the future of network edge management look like? We explain how artificial intelligence and machine learning technologies are crucial for intelligent edge computing and the management of future-proof networks. What’s required, and what are the building blocks needed to make it happen?
As I said before, Moore’s Law is not dead, it just is just transforming for a new era of applications. The discussion on AI use in fabs continues. Toyota and Siemens tie the knot on digital transformation for die casting.