The bane of modern engineering is complexity. One promise of artificial intelligence and machine learning is helping engineers to use complex tools and harness vast data sets effectively.
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Most anyone who’s worked in a machine shop for any length of time has at some point attended a trade show or machine tool distributor’s open house. There they see canned demonstrations of CNC machines busily carving up chunks of brass, mild steel, or aluminum into business card holders and tic-tac-toe games.
A Michigan company that displays instructions for manual manufacturing processes on work stations via augmented reality (AR) is adding wearables to provide similar guidance.
My involvement in SME and its AeroDef event began in 2014, when I first presented an Adaptive Machining Overview at AeroDef 2014 in Long Beach, Calif. At the time, the conference was relatively small in terms of attendees and exhibitors in comparison to the explosion of other engineering conferences that began around that time.
Aerospace machining encompasses machines small and large. These range from the Tornos SwissNano to the Makino MAG3, as Rich Sullivan put it. He is the OEM manager for Iscar Metals Inc., Arlington, Texas.
Structured light systems measure surfaces by projecting a pattern of fringes, then using cameras and sophisticated software to convert them into point clouds of metrology data. Accuracy can reach the single-digit microns over millions of points.
Digital manufacturing solutions with product lifecycle management (PLM) tools hold great potential for manufacturers to eventually fully unlock the promise of the Industrial Internet of Things (IIoT).
Manufacturers are facing shrinking product lifecycles with frequently changing customer demands. As a result, they need agile production and flexible factory layouts that can easily be modified whenever needed.
As with any digital transformation process, the devil is in the details, and there are many potential pitfalls that can derail projects.
There is no shortage of competition in a global market. As a manufacturer trying to get ahead of the pack, automation can help with problems like a limited skilled labor force, quality control issues and suboptimal throughput. But the high initial cost and extended implementation time can be deterrents.