Priced under $4,000, the In-Sight(tm) 1000 machine vision sensor
represents Cognex Corp.'s entry into the low-cost vision sensor fray. It hits
the price and size "sweet spot" for many custom machine builders, according to
Product Manager Carl Gerst, "making vision reliable and affordable enough to use
throughout the plant in a multi-point vision area network."
Networked vision applications help users manage, monitor, and control vision activity over an Ethernet network, improving access to real-time vision data plant-wide and beyond. Using a PC or PLC master, data from multiple Insight 1000's can be managed in central host. Alternatively, one Insight 3000 uses its second processor to handle the networking activity of up to 40 Insight 1000's in a master/slave arrangement.
Networked vision lets users set up and modify vision applications from remote sites, monitor inspection activity from any location in the plant, and share up-to-the minute production data with management.
According to Gerst, other vision sensors typically lack the power and flexibility to solve all but the simplest vision tasks. In contrast, Insight 1000 offers the capabilities of an advanced vision system. It features a complete library of proven vision software tools, including Pat-Find(TM) a novel part location tool based that brings Cognex's high-end PatMax(r) geometric recognition technology down to the vision sensor level.
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.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
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.