To get to smart manufacturing, the industry needs integration, simulation and analysis.
Displaying 1-10 of 82 results for
Are you ready for metamorphic manufacturing, what some call the third wave of the industry’s digitization? If not, take in Contributing Editor Karen Haywood Queen’s expertly reported story.
The industry’s fastest growing firms are leveraging new artificial intelligence (AI), blockchain and Internet of Things (IoT) solutions to transform supply chains, transport and logistics. Reliance on paper forms and clashing systems are giving way to improved transparency across the value chain.
Because its president saw opportunities to improve efficiency and an immediate need to make up for capacity lost due to impending worker retirements, Daiwa Steel Tube is set to save more than $1 million a year.
Modern manufacturing is rapidly adopting model-based definition (MBD). When employing an MBD strategy, the CAD model becomes more than the nominal to which all parts are measured and inspected against. MBD keeps the all-important digital thread intact—from design to manufacturing to inspection and quality reporting.
A Michigan company that displays instructions for manual manufacturing processes on work stations via augmented reality (AR) is adding wearables to provide similar guidance.
I just returned from IMTS in Chicago and my first thought was, “where will I be able to rack up all those bonus steps I got last week?” On the easiest day, I walked 7.9 miles, and I topped 10 miles on two other days. It’s easy to understand why.
When I graduated with an engineering degree some decades ago, I learned that the organizations I was going to work for had internal communication problems. This was especially true for those that designed and manufactured complex machinery such as engines, aircraft, or automobiles.
SME’s Smart Manufacturing Hub will be part of IMTS this year. Smart Manufacturing asked past Hub speakers to imagine what manufacturing will look like in 2030. Here are their visions:
My instincts tell me we need a sense of urgency around the use of artificial intelligence (AI) in manufacturing. The urgency is driven by how quickly technology can move today, and how an unexpected breakthrough can quickly dominate.