"What's important about this 18.0 release is that we've made tighter integration for our legacy customers so they can continue using the core engineering system, but still benefit from the other Creo Apps, like advanced FEA tools," says Teague. "Data can now move back and forth … and we're creating a process that enables both direct and parametric modeling whereas before they were separate tools." To create this tighter integration, PTC leveraged its Granite kernel so solids can be sent back and forth between the two systems.
While Creo 1.0 users can take advantage of direct modeling capabilities in Creo Direct, Teague says he doesn't see that platform as a replacement for long-time CoCreate users yet because it doesn't provide the equivalent feature set. Creo Direct is a completely new direct modeling engine and currently doesn't have the advanced sheet metal, cabling, and advanced simulation capabilities offered by the standalone Creo Elements/Direct 18.0 tool.
"Creo Direct was born in the Creo data model and paradigm," Teague says, explaining PTC's decision to start its direct modeling capability from scratch instead of modifying CoCreate for the Creo platform. "That gave us an opportunity to simplify some things that you just can't do with a product in its 18th release."
Stay tuned, though. Teague says Creo Direct will have that functionality over time and at some point, may be robust enough for long time CoCreate users to cross over.
Beth, what's the status of virtual modeling as a replacement for acual physical prototypes? It seems like virutal got a tremendous buzz a few years back, and now I don't hear much about it. I know virtual modeling is a huge success at P&G, but a lot of their modeling is process modeling and not product modeling. My own gut feel is that the tremendous advances in inexpensive, great-looking 3D-printed prototypes have pushed all-virtual modeling to the background. It seems I've been in many engineering departments where I asked the all-virutal question, and I get a kind of pained look on the face of the chief engineer, and a comment that begins: "We tried it on X, but......" What's your take?
I actually think virtual prototyping is used pretty extensively in manufacturing organizations today--particularly ones in the automotive, aerospace and heavy machinery sectors that have made significant investments in PLM and digital prototyping tools.
Most forward-thinking engineering organizations are pushing for more virtual prototyping and virtual simulation far earlier on the process because it is so much cheaper to iron out design flaws then before "bending metal," as they'll tell you. I think the cost of these tools has come down greatly, they have become far more accessible and easy to use, and I think usage is definitely on the rise. That said, clearly virtual prototypes will ever completely replace physical prototyping or even the rapid prototyping stuff. But using the digital world to reduce the number of physical prototypes built is definitely where it's heading.
I think there's a place for both virtual and physical prototyping, especially in the product manufacturing arena. During the design phase, virtual prototyping and finite analysis cut down on the cost of multiple physical prototypes by requiring the designer to make only one...maybe two actual renditions of what he's inventing. This also cuts down (in a big way) the amount of time it takes to complete a project!
@plasticmaker: I have to agree about the role of both methodologies. You can never fully replace the physical prototype. Yet as you mentioned, by reducing the number of physical prototypes to one or two greatly takes cost, time, and late-stage workarounds out of the process, which ultimately leads to better products in a shorter timeframe.
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.