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.
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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:
AS A TEAM OF FOUR MANUFACTURING engineering undergraduate students from Western Washington University (Bellingham, WA), we had our minds blown within seconds of walking onto the RAPID + TCT show floor when we attended the event, April 23-26, in Fort Worth, TX.
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.
When the Italian company JDeal-Form (Oleggio, Italy) started using additive manufacturing to apply a micronized polymer coating to the underwire tips and bra straps it sold to brassiere makers, CTO Davide Ardizzoia grew frustrated with his AM vendor’s constant lateness.
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.
New systems, software and processes are replacing so-called islands of automation with seamless, automated manufacturing lines that boost overall equipment effectiveness (OEE) from 30 to 80% or more.
In the near absence of academic programs to teach undergraduate engineering students additive manufacturing, a California-based startup has stepped in to help fill the void through internships.