Worldwide truck sales exceeded 16 millions units in 1997 and are forecast to make up half of all vehicle sales in North America in the next five years. The implications of these numbers are not lost on Ken Sohocki. Chief engineer of General Motors' all-new, full-size trucks, Sohocki and his team oversee the development and execution of the largest and most important program in the company's history. It kicks off this fall with the introduction of the 1999 Chevrolet Silverado and GMC Sierra full-size pickups, followed by a fleet of next-generation SUVs and heavy-duty pickups. Once fully rolled out, the program will consist of some 30 different models. To set a benchmark for the full-size pickup segment, Sohocki and his team aggressively pursued new technologies on all new designs, including novel use of hydroforming, reinforced reaction injection molding, and bused electrical center architecture. Thanks to the creativity of Sohocki's team, the Silverado and Sierra require 25% fewer parts per model and 15% less base engineering content.
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.
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.
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.