This posting is the first that I have seen that provides some believeable description of what PLM may be able to offer. So thanks for the education. It is clear now that not all organizations need to buy PLM software.
Automotive, aerospace, and electronics have been the traditional sweet spots for PLM. The big companies have long adopted the platforms and even smaller suppliers in their respective value chains have gotten on board. Some of the newer industries where PLM is seeing traction is medical devices, shipbuilding, consumer products goods, and retail, particularly footwear. Any where there are farflung partners and lots of configurations of products or particularly large and integrated assemblies (shipbuilding is a lot like aerospace) is showing interest.
Given the advantages of PLM -- and its ever developing new tools - I would guess it is getting adopted widely. In the radio show, you asked what industries are the leaders (besides the obvious aerospace). They answer you received was vague. I would guess auto and electronics are big. What are you seeing in terms of adoption and industries?
Managing the ECO (engineering change orders) is one of the low-hanging fruit applications of PLM and you're right, Alex, about the significant amount time spent trying to track down and stay abreast of that data--especially in light of mounting time to market pressures. With the new Service and Quality modules of Windchill 10.0, PLM is really branching out into territory that's been talked about for a while, not really been implemented in any grand fashion. It will be interesting to see how companies respond.
I can see where managing ECNs (aka product change data) would actually be a more difficult task (or maybe I should say, more time consuming) than many of the actual steps in the design process. Who among us has not lost some vital piece of information that was at their fingertips just 2 minutes earlier. This data becomes ever more critical as SKUs proliferate and time to market pressures increase.
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.