Thanks for that info Rob. That means it's possible--although not necessarily likely--that newer machine vision interface standards might go into the emerging economy geographies. But not necessarily the more complex ones, like GigE, which require more expertise. It's not a clear picture, anyway, from the MV standpoint.
Rob, I don't know the geographic distribution of where new machine vision installations are going in vs older installed base. What I do know, though, is that there are still a lot of older analog camera systems in Asia, especially Japan, so that's not considered an area where GigE is likely to take hold, at least for awhile.
Rob, that division sounds a lot like what I've heard about using Ethernet for machine vision networks: it's being deployed in new systems, and not so much in existing ones, because of the difficulty of re-engineering and re-configuring hardware and software, as well as training.
Good question, Chuck. I would think the difference between the 60 percent and the 40 percent of Rockwell implementations can be tracked along greenfield versus brownfield plants. Ethernet is likely going into most new plants as well as some upgrades at existing plants. But I'll bet a lot of the existing plants are not going to Ethernet with their upgrades.
Alex, thanks for the link to your article. What a fascinating trend! It makes me think of the production version of what IT has been working on for awhile, the "agile enterprise," or whatever they are calling it now, for BPM.
Yes, the plant floor is definitely following in the footsteps of mainstream enterprise business systems. The question is, how much will this trend accelerate when plants who aren't yet using Ethernet finally migrate to Ethernet-based automation systems? Rockwell Automation claims that only about 60% of the equipment they sell is Ethernet-based. What happens when the other 40% finally make that move?
Alongside this article, I'd like to recomment that readers check out my story, Top 5 Roadblocks to the Digital Factory of the Future. This is an important trend, the ability to rapidly adapt (repurpose) production lines, using graphical programming tools and networks PLCs to which software can be downloaded via network links. This is a big part of the ability to go rapidly from prototyping to production.
Rob, thanks for the overview. Looks like some pretty exciting trends and new developments to watch for. I'm especially interested in increasing simulation: it's good to see this powerful technology put to very practical uses in factories. I also liked the diagrams in the Connected Automation System and Cloud Computing in Automation slides. If a picture can say 1,000 words, a diagram can say 5,000.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.