The latest EOS laser sintering system, the FORMIGA P 100, will make its North American debut on May 1st at the RAPID 2007 event in Detroit. The system produces plastic parts in polystyrene or polyamide and has a smaller format than the EOS' previous machines. According to Jim Fendrick, EOS' vice president for North America, the system represents a ground-up redesign. “It's not just a scaled down version of our previous machines,” he says, noting the the new machine features advances in its optics and scanning system that allow it to build walls as thin as 0.016 inches. The FORMIGA P 100 also features a newly designed radial recoater that improves part quality while decreasing powder consumption. “The parts coming off the machine look very crisp,” Fendrick says. EOS is positioning the machine as suitable not just for prototypes but for rapid manufacturing work–or “e-manufacturing” as EOS terms it. Fendrick points out that the FORMIGA P 100 sports 23 components that have been made on EOS' own laser sintering machines. “The machine practices what we preach,” he says.The FORMIGA P 100 offers a build envelope of 8 x 10 x 13 inches and is housed in a 52 x 42 x 77 inch cabinet. North American installations will begin in the third quarter of 2007.
Are they robots or androids? We're not exactly sure. Each talking, gesturing Geminoid looks exactly like a real individual, starting with their creator, professor Hiroshi Ishiguro of Osaka University in Japan.
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.