The management of materials information is just one piece of the ‘materials intelligence’ puzzle. Discover how to reduce design cycles, minimize risk, improve product quality, aid compliance, and much more, by taking these five steps to increasing your Materials IQ.
Can users of today’s advanced simulation methods for Automotive still learn from sentiments expressed 150 years ago?
On two occasions I have been asked, “Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?” … I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.
So said Charles Babbage, widely considered the father of the computer, way back in 1864. He was obviously right – but are we still guilty of the confusion he identifies?
As any simulation analyst can tell you, quality materials and property data is essential for modeling and simulation within product design. However, this information often exists in many different formats and locations throughout an organization. For authors of data, generating the right materials information for simulation (usually by analyzing populations of materials test data) can be time consuming, the process can be inefficient, and it’s certainly always complex. Moreover, the final data that’s produced out of this process is not always then traceable to its source.
CES Selector has been used for some pretty cool things over the years, and it’s great to hear how our solution is helping the legendary Chip Ganassi Racing Teams (CGRT) zoom towards victory.
Together with the Altair Partner Alliance, all of us at Granta are excited to announce that our powerful material selection tool, CES Selector, is now available for use by HyperWorks customers. It almost goes without saying that CES Selector is the industry standard tool for materials selection and graphical analysis of material properties. It is used to innovate and evolve products, quickly identify solutions to materials issues, confirm and validate material choices, and reduce material and development costs.
Our very own Stephen Warde has been interviewed for the blog of one of the major providers of CAD/PLM software. Speaking to PTC, Steve highlights the difficulties faced by design engineers and the impact materials have on the ultimate cost and performance of a product.
The rapid development of Additive Manufacturing (AM) technology displays signs of immense promise for making topologically-optimized parts with optimal cost and performance. But with great power comes great challenges! Engineers require an understanding of the complex interactions and relationship between part design, materials, production processes and part performance. Designing the ‘ideal’ geometry can also prove to be a significant challenge. One secret is that succeeding in the real world of AM production requires you to do the right things in the virtual world—in how you simulate AM processes and handle AM data.
Simulation engineers are often desperate for sophisticated material properties to support their temperature dependent and/or non-linear material models, enabling more accurate simulation and validation of product performance.
If you are in the ‘material authority’ role in your company, either as a materials specialist or a member of the simulation team who has acquired this responsibility, you will need to respond! I’ve worked with many people in this role who are dedicating a lot of time to queries from design and simulation engineers about how materials will perform under various conditions, or which is the best material to use in certain operating conditions and environments.
I recently presented at a web seminar hosted by Granta’s partners at Dassault Systèmes, and it raised an interesting question about the materials property data needed by simulation analysts. We were looking, in particular, at the Abaqus/CAE® software. Its users want accurate material properties for use in their CAE software. But they also want confidence in that data – to know that it comes from a reliable source. And their companies want control: i.e., to ensure that all of their analysts are using data that is consistent, up-to-date, and traceable should simulation results ever need to be reviewed or updated. How can we meet these various requirements without disrupting well-established workflows and processes?