Call it business
process automation meets engineering. Dassault
Systemes' Isight simulation process automation and design
has been upgraded with new methods and capabilities to exploit
processing along with a new licensing model designed to reduce cost.
SIMULIA brand, gives designers, engineers and researchers an open system
integrate design and simulation models created with diverse CAD, CAE and
design tool applications. The software is designed to help automate the
execution of hundreds or thousands of simulations, saving time and
improve designs by optimizing against performance or cost variables
methods such as Design of Experiments or Design for Six Sigma.
The new Isight 4.5
upgrade provides new scalable parallel algorithms for leveraging
computing resources, enhanced approximation and reliability methods to
product performance across a range of real-world operating variables,
improvements to multi-objective optimization and data mining which
deeper insight into performance attribute tradeoffs. Dassault also
SIMULIA Execution Engine (formerly Fiper) 4.5 for executing Isight
process flows across computing resources.
Customers will now
be able to leverage the new parallel algorithm and optimization features
Isight combined with the distributed computing capabilities of
Engine to evaluate more design alternatives in less time, according to
Crowley, director of product management, SIMULIA, Dassault Systemes.
result in developing better products at a lower cost, he said.
In a related move, users of SIMULIA's Abaqus
Unified FEA will benefit from a new licensing policy that dramatically
the cost for using SIMULIA's Abaqus Unified FEA in automated design
with Isight. Using the combination of these products allows customers to
their Abaqus token usage as much as 60 percent.
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.