Technological developments

More than 50 years ago, computer pioneer John Von Neumann conceived of a self reproducing machine. It would mine its own ore, smelt it into metal ingots, machine the ingots into parts, and assemble the parts into a copy of itself. During the 1980s, nanotechnology evangelists worked out the same idea on a much smaller scale, prompting critics to envision a horror scenario in which molecule size bots reduce the entire world to a featureless mass dubbed ‘gray goo’. Today there’s RepRap. Unlike gray goo or Von Neumann’s idealized machines. RepRap (short for replicating rapid prototype) doesn’t harvest its own materials. But also unlike them, it’s entirely real. For about US$ 725 in parts, this self reproducing machine, spawned by a global band of engineers and hobbyists, will squirt out complex three dimensional patterns of molten plastic filaments that will solidify into most, if not all, of the mechanical parts for another RepRap (see sidebar, self Reproduction Is Hard; Self Assembly is Harder). Rep rap consists of a roughly cubicle half meter frame enclosing its fabrication volume along with motors, drive electronics, and one or more write heads that extrude plastic (or some other material) into the desired shapes. RepRap gets its instructions from your PC, via a USB connection. Software on the PC, written min Java, takes design files produced by 3-D drawing programs and turns them into instructions for the RepRap. The software converts solid object models into a series of movements with the extruder on or off, and with either or solid interior filling, depending on a part’s structural requirements. Because all of RepRap’s software and hardware designs are open source, no one knows exactly how many people are using it on projects. Adrian Bowyer, a Senior Lecturer in Mechanical Engineering at the University of Bath, in England and the originator of the project, recall the day last winter when a RepRap machine appeared on exhibit at the Science Museum in London. He had never even heard from the team building it, much less known of their plans to put one on display Zach Smith, who manages the RepRap Research Foundation in New York City, counts a dozen or so core developers, but about 500 more have bought parts from they foundation’s online store. Some of the circuit boards and other components can’t be purchased elsewhere, he notes, although a determined builder could fabricate them from scratch. “I’m fascinated not only by the idea of RepRap but also by the possibility of building one. I already have some ideas that would extend RepRap’s ability to create different forms” – for example, how to implement some of the rough designs others have floated for additional assembly heads that pick up and place components or wield cutters that in turn would cut parts from materials that can’t be extruded. But for me, RepRap’s biggest appeal is its appetite for prefabricated circuit boards that don’t have to be etched or solder and for structural components that call for a minimum of epoxy or lathe work. In other words, even if building it, this thing might actually work.

Oil light for everything:

The dashboards of most cars have a spot for a useful little light, the one that flashes ‘check oil’ when the engine’s lubrication system appears to be compromised. It was not always thus: Pulling the dipstick and studying the quantity and quality of the oil clinging to it was once part of routine auto maintenance. Research conducted at the Georgia Institute of Technology in Atlanta promises to take the concept of the oil, light to new dimensions. Soon, a computer model incorporating data from sensors will be able to calculate in real time the amount of useful life left in an engineering system. Fully embraced, the work by engineering professor Nagi Gebraeel might result in an integrated logistics system where mechanical equipment is almost autonomously kept at optimal working condition. At first, Gebraeel researched the vibration and acoustic signals from rotating bearings to create a model that could use noise and vibration data to predict the remaining life in an individual bearing. Experimental results suggested that such a system could reduce costs associated with part failure and lack of a specific spare part by more than half. Gebraeel recently began working with Rockwell Collins to develop adaptive models to estimate the remaining useful life of electronic aircraft components. The goal is to embed a prognostic system into an aircraft’s avionics, so that decisions about air worthiness of an aircraft can be made more or less automatically. Prognostic models combine experimentally derived general reliability characteristics with real time signals from networked sensors. A model would use the vital signs from the sensors to predict the best time to order spare parts or to schedule maintenance .To help develop this prognostic model concept further, Gebraeel is working with a Virginia-based company, Global Strategic Solutions LLC, to develop embedded diagnostics and prognostics that could predict the probable life remaining of electrical power generation systems on board US Naval aircraft, and for the communication, navigation, and identification avionics systems used on the Joint Strike Fighter.

“What? Gaming in the workplace? No way!” This is something that we hear from Corporate
Closely tied to the question of how much capacity should be provided to meet forecasted
The notion of focus naturally, almost inevitably from the concept of fit. Just as a
At its heart a capacity strategy suggests how the amount and timing of capacity changes
However, as with most strategic decisions, the issue is more complex than it first appears.