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.
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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.
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.
Technology is changing ever more rapidly. Sometimes this means topics learned in engineering or technical school become obsolete. Whole new fields emerge within a few years, so that even those with freshly minted educations suddenly find themselves faced with new challenges.
Aerospace and defense manufacturing is known for its complex designs, continual changes and the need to negotiate tight margin requirements. At Elite Aviation Products (EAP), a division of Elite Aerospace Group (Irvine, CA), we face these challenges every day.
My original intention for this column was to discuss a phrase getting a lot of buzz lately, artificial intelligence (AI). By any measure, interest in AI is expanding exponentially, both in the number of articles one can read on the subject and, according to Google Trends, the number of searches for those articles.
The demand for titanium components by the aerospace industry began as a whisper about 15 years ago and steadily grew to a sustained, raucous shout over the last five and likely won’t quiet for several more.
Our focus has always been on helping manufacturers improve quality, productivity and visibility. In Sight Machine 2.0, among other things, we’ve added a set of enhancements to improve visibility.
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.
Manufacturers face a difficult task juggling the current “innovation agenda.” Today, the Industrial Internet of Things (IIoT), robotic automation and artificial intelligence (AI) are all poised to be the next big thing.