What does it mean to define a material as we move along the product lifecycle, from concept, through to engineering design, simulation, prototyping, manufacture, and distribution to the customer? A ‘material’ means one thing to a material engineer, something else to a CAD designer, and another to someone in manufacturing. Companies can spend weeks of wasted effort ensuring consistency or attempting to find or verify data.
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.
If you haven’t been involved in a material information management project, you might think it’s only of interest to materials engineers.
My mother always tells the story of how I learnt to type my name on a computer before I could put pen to paper. I grew up with a love of computers and am not ashamed to say that the topic of artificial intelligence (AI) – covering the gamut of machine learning, and deep learning – is a particular passion. You can imagine my delight, therefore, when I came across not one but two recent articles on how the future of materials science and AI may be intertwined.
With a broad range of applications like corrosion protection, scratch resistance, and structural parts, hybrid materials receive a great deal of attention – particularly in high-performance engineering sectors such as aerospace, and automotive. As well as boasting high specific strength and stiffness, hybrid materials and structures like sandwich panels, foams, lattices, and composites, have the potential to reduce the environmental impact of those industries. But how can we ensure that the full benefits of this class of material are realized? And what challenges are there within the design and development process that could prevent this from happening?
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.
A casual observer at this year’s Material Intelligence seminar (and associated 6th North European Granta User Group meeting), held earlier this month at the Manufacturing Technology Centre (MTC) in Coventry, UK, will have come away with one core message. Whether we’re talking about processes, materials data, or driving a cultural change, the key to success is having a singular purpose and approach.
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.