We all know the buzzwords circulating around digital data and the factory. You have heard them—Industry 4.0, smart factories, data analytics, and artificial intelligence (AI). The question we all have is how will this impact workers in the long term? What do these terms really mean? Nevertheless, both traditional software suppliers and makers of advanced manufacturing equipment are offering digital solutions.
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For machine shops in a competitive global marketplace, keeping spindles running and making product is the only way to stay in business. Still, adding a new piece of equipment, even with the promise of improving the efficiency of your existing ones, may be a difficult sell to management.
Adaptive Milling. Dynamic Motion. hyperMILL. Profit Milling. VoluMill. Waveform machining. If you’re one of the lucky people who machines parts for a living, chances are about 50-50 that you’re using one of these or a comparable high-performance programming technology.
Swiss-style machine tools can be a good choice for making complex parts. On the downside, however, Swiss machining itself has a reputation of being complex—and, therefore, more difficult to master than standard machining.
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.
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.
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.
Cyber criminals are increasingly setting their sights on today’s digitized manufacturing industry as an entry point into government and commercial supply chains.