In recognition for his exceptional contributions to the field of materials science and engineering, Prof. Stephen Krause was awarded the ‘Michael Ashby Outstanding Materials Educator Award’ at this year’s ASEE conference in Salt Lake City.
Nominated by Dr. Cynthia Waters, she explains: “Steve has been described as the “Pied Piper” of Materials Active learning. He continually and with excitement shares his “Music” and many follow. This music includes methods and tools to increase learning in a Material Science classroom. One cannot find a more genuine and sharing mentor and Engineering Education leader.”
A worthy winner of this year’s award, Stephen has long been instrumental in many engineering education initiatives, not least the Materials Concept Inventory. Co-developed with Prof. Richard Griffin, of Texas A&M University, the strategy is an interesting methodology which can be used to measure students’ conceptual changes. By exploring common misconceptions, which he has termed the ‘Muddiest Points’, Stephen has been able to quickly identify key topics, which his classes find most challenging.
Further explained in his 2013 ASEE paper, titled ‘Muddiest Point Formative Feedback in Core Materials Classes with YouTube, Blackboard, Class Warm-ups and Word Clouds’, Stephen reviews the effectiveness of four different feedback modes, based on the Muddiest Points responses.
You can read more about Stephen’s achievements here, as well as joining us for a no-cost live webinar on the November 8 when Stephen will be available for questions. Register here.
We would also like to take this opportunity to congratulate Dr. Alison Polaski who received the ‘New Materials Educator Award’, for her exceptional achievements as an early-career professional.
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.
Organizations make big investments in Additive Manufacturing. AM machines, new materials, experts in AM processes, testing, analysis, and simulation – no expense is spared. These costs feel justified in the light of the benefits that AM can bring – parts that can be printed-to-order, new lightweight components with previously unachievable shapes, or reduced manufacturing lead times.
But, there is one aspect we might be forgetting. Will anyone think of the data? Specifically, are we investing enough into managing the complex data created from our AM projects and, if we do, are we thinking about it early enough?
Speaking at a recent webinar, experts from Honeywell Aerospace, Saudi Aramco, and Burberry presented the benefits of systematic materials selection.
With roots in fashion, oil and gas, and aerospace, these organizations are not only diverse in their focus, but in their experiences of using the CES Selector software. The Tempe site within Honeywell Aerospace has been using the software since 2001. Principal Materials Engineer John Perek presented two examples of how it reduced selection time, and minimized cost. The first was a materials substitution project for a pressure regulator housing that was experiencing delayed cracking after molding. The second example involved the necessary replacement of a Be-Cu pitot tube to comply with the restriction of hazardous substances (RoHS) legislation.
If you haven’t been involved in a material information management project, you might think it’s only of interest to materials engineers.
However, the work involved in having a single, organized source of materials information creates benefits that spread far wider than just the engineering department. In fact, the advantages go right to the top of the chain and help address the key goals of a business.
Here are 10 ways that materials information management benefit the entire company and make your Chief Executive happy.
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?
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?
The rate of adoption of additive manufacturing (AM) is incredible. AM brings a physicality to ideas, and offers ways for people to touch upon solutions that would have been impossible to otherwise imagine. Equally impressive is the scale of investment in machines for producing AM parts, which is of course supported by business cases highlighting reduced development times, fewer prototype costs, reduced part counts, and flexible manufacturing. But, I am seeing more and more evidence that the prescribed route to this ‘Nirvana’ is via a process of trial and error for settings, powders, and even machine capability.