MIT has developed a Machining Variation Analysis system that allows designers to create machine tools on the computer and use those tools to virtually machine parts and predict the exact shape of a part given any error that may exist in the machine tool. "Before the MVA, machine-tool designers could not predict the effects of the dozens of error sources that plague a real process," said MIT Professor Alexander Slocum of the Department of Mechanical Engineering. "Every time a machine was designed to make a new part, the company took a gamble. The MVA takes the risk out of developing new manufacturing equipment." With MVA, the user provides information including the geometry of the part and sources of error in the machine's operation. With these parameters, MVA determines the exact shape of the part including all the consequences of the specified errors in machine operation. Slocum developed the MVA with Professor Kevin Otto of mechanical engineering, Daniel Frey of MIT's System Design and Management Program, and colleagues from the National Institute of Standards and Technology and the Landis Division of Western Atlas, Inc. For more information, e-mail the news office at firstname.lastname@example.org or call (617) 253-2700.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
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.