LLumin's Insight

Fully autonomous factories are in sight as manufacturers adopt Industry 4.0 technologies. Does this spell the end for human maintenance staff? Not likely. Many companies are moving to approaches that blend human and artificial intelligence, where humans and smart systems work together to keep plants running. An excellent example of this type of collaboration is a worker taking guidance, on what to fix and when, from an asset management system that triggers predictive maintenance alerts when it detects a problem in the making.

Article Excerpt:
The implementation of Industry 4.0 tech may increase the likelihood of fully autonomous factories, but it isn't the end for human workers on the shop floor.  

LLumin's Insight

For years, manufacturers have submitted OSHA 300A forms covering work-related injuries and illnesses. Last year, OSHA required businesses to submit them digitally. Manufacturers that tracked such processes on paper needed to make a change. A smart way to transition is to make reporting part of a broader safety compliance effort based on a materials tracking and inventory management solution such as LLumin’s READYTrak, which can help ensure the enforcement and automatic documentation of compliance processes.

Article Excerpt:
Last July, OSHA began to require U.S. businesses to submit their 300A forms digitally.  

LLumin's Insight

Artificial intelligence (AI) is being used in many manufacturing areas from robotics on factory floors to predictive maintenance to prevent equipment downtime. However, AI is still a new technology. Companies lack expertise in its use, and they need to guarantee a return on investment (ROI). Rather than being widely embraced, the use of AI in most plants is gradually phased in in the form of testbeds and smaller projects. Such projects help prove out the technology for expanded use.

Article Excerpt:
What is holding up AI adoption, and where is it already in use?

LLumin's Insight

Predictive maintenance of equipment based on artificial intelligence models holds great promise. An asset management system could alert a plant or facilities manager that a piece of equipment is about to fail. However, predictions are only as good as the data they are based on. A false alarm triggered by a lack of data or inaccurate data can lead to incorrect actions and additional costs. Bottom line: predictive maintenance will only be able to predict those problems for which it already has accurate data.

Article Excerpt:
  Although the machine learning and artificial intelligence (AI) solutions that enable predictive maintenance are helpful, they’re only as helpful as they’re trained to be.  

LLumin's Insight

The U.S. Navy is planning to use artificial intelligence-based predictive maintenance. The technology aims to eliminate unplanned downtime for critical shipboard systems powered by pumps and motors. Failure of such devices in a land-based plant or facility is disruptive enough. At sea, and in combat situations, breakdowns can endanger the crew. The initiative, which is headed by the Defense Innovation Unit, builds on previous Department of Defense AI-based predictive maintenance programs for the Army and Air Force.

Article Excerpt:
The Pentagon's innovation arm looks to expand predictive maintenance technology to Navy ships.