Tag Archives: innovation

Making engineering work for society

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Last week I attended a one-day workshop for PhD students sponsored by Airbus.  Most of the students produced a poster describing their research; and a dozen brave ones gave a three-minute presentation on their PhD thesis.  It’s a challenge to describe three years of research in three minutes to an audience that are not experts in your specialist field.  However, the result was an exciting and stimulating morning covering subjects as diverse as multidisciplinary design optimization and cognitive sources of ethical behaviour in business.  The latter was presented by Solenne Avet who was the only woman amongst the twelve three-minute thesis presenters.  The gender diversity was better for the other, longer talks with two women out of six presenters.  Interestingly, the female PhD students were the only ones tackling the interaction between engineering and human behaviour, including system-human communication, collective engineering work and innovation processes, which I have suggested is essential for viable engineering solutions to our global and societal challenges [see my post ‘Re-engineering engineering’ on August 30th, 2017].  This population sample is too small to make a reliable generalization; however, it suggests that a gender-balanced engineering profession would be more likely to succeed in making substantial contributions to our current challenges [see UN Global Issues Overview].

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Blinded by the light

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It has become a habit during our summer vacation to read the novels short-listed for Bailey’s Women’s Prize for Fiction.  Unusually this year, we were not only unanimous in our choice of the best novel but we also agreed with the judges and selected the ‘The Power‘ by Naomi Alderman.  In another of the books, Do Not Say We Have Nothing by Madeleine Thien, a Chinese composer called Sparrow thinks ‘about the quality of sunshine, that is, how daylight wipes away the stars and planets, making them invisible to human eyes, might daylight be a form of blindness? Could it be that sound was also be a form of deafness? If so, what was silence?’.  I felt some resonance between these thoughts and John Hull’s writings on blindness and my earlier blog posting on ‘Listening with your eyes shut‘ [on May 31st, 2017].  In our everyday life, we are bombarded with sounds from people living around us, from traffic and from devices in our homes and places of work.  We rarely experience silence; however, when we do, perhaps on holiday staying in a remote rural location, then a whole new set of sounds becomes apparent: waves breaking on the shore in the distance, the field mouse rooting around under the floorboards, or the noises of cattle enjoying the lush grass in the field next door.  Okay, so you have to be in the right place to hear these sounds of nature but you also need silence otherwise you are deaf to them, as Sparrow suggests.

The same is true for knowledge and understanding because our minds have finite capacity [see my post entitled ‘Silence is golden‘ on January 14th, 2014].  When you are bombarded with information and data it is easy to become overwhelmed and unable to structure the information in way that makes it useful or meaningful.  In our connected society, information has become like white noise, or daylight obscuring the stars and planets.  Information is blinding us to knowledge and understanding.  We need to aggressively filter the information flow in order to gain insight and knowledge.  We should switch off the digital devices, which bombard us with information constantly, to leave our minds free for conceptual and creative thinking because that’s one of the few tasks in which we can outperform the smartest machine [see my post entitled ‘Smart machines‘ on February 26th, 2014].

In a similar vein see: ‘Ideas from a balanced mind‘ on August 24th, 2016 and ‘Thinking out-of-the-skull‘ on March 18th, 2015.

Wanted: user experience designers

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A few weeks ago, I listened to a brilliant talk by Professor Rick Miller, President of Olin College.  He was talking at a conference on ‘New Approaches to Higher Education’.  He tolds us that the most common job description for recent Olin graduates was ‘user experience designer’ rather than a particular branch of engineering.  Aren’t all engineers, user experience designers?  We design, manufacture and maintain structures, machines, goods and services for society.  Whatever an engineer’s role in supplying society with the engineered environment around us, the ultimate deliverable is a user experience in the modern vernacular.

Rick Miller’s point was that society is changing faster than our education system.  He highlighted that the relevance of the knowledge economy had been destroyed by internet search engines.  There is no longer much advantage to be gained by having an enormous store of knowledge in your head, because much more is available on-demand via search engines, whose recall is faster than mine.  What matters is not what you know but what you can do with the knowledge.  And in the future, it will be all about what you can conceive or create with knowledge.  So, knowledge-intensive education should become a thing of the past and instead we need to focus on creative thinking and produce problem-solvers capable of dealing with complexity and uncertainty.

Getting smarter

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A350 XWB passes Maximum Wing Bending test [from: http://www.airbus.com/galleries/photo-gallery%5D

Garbage in, garbage out (GIGO) is a perennial problem in computational simulations of engineering structures.  If the description of the geometry of the structure, the material behaviour, the loading conditions or the boundary conditions are incorrect (garbage in), then the simulation generates predictions that are wrong (garbage out), or least an unreliable representation of reality.  It is not easy to describe precisely the geometry, material, loading and environment of a complex structure, such as an aircraft or a powerstation; because, the complete description is either unavailable or too complicated.  Hence, modellers make assumptions about the unknown information and, or to simplify the description.  This means the predictions from the simulation have to be tested against reality in order to establish confidence in them – a process known as model validation [see my post entitled ‘Model validation‘ on September 18th, 2012].

It is good practice to design experiments specifically to generate data for model validation but it is expensive, especially when your structure is a huge passenger aircraft.  So naturally, you would like to extract as much information from each experiment as possible and to perform as few experiments as possible, whilst both ensuring predictions are reliable and providing confidence in them.  In other words, you have to be very smart about designing and conducting the experiments as well as performing the validation process.

Together with researchers at Empa in Zurich, the Industrial Systems Institute of the Athena Research Centre in Athens and Dantec Dynamics in Ulm, I am embarking on a new EU Horizon 2020 project to try and make us smarter about experiments and validation.  The project, known as MOTIVATE [Matrix Optimization for Testing by Interaction of Virtual and Test Environments (Grant Nr. 754660)], is funded through the Clean Sky 2 Joint Undertaking with Airbus acting as our topic manager to guide us towards an outcome that will be applicable in industry.  We held our kick-off meeting in Liverpool last week, which is why it is uppermost in my mind at the moment.  We have 36-months to get smarter on an industrial scale and demonstrate it in a full-scale test on an aircraft structure.  So, some sleepness nights ahead…

Bibliography:

 

ASME V&V 10-2006, Guide for verification & validation in computational solid mechanics, American Society of Mech. Engineers, New York, 2006.

European Committee for Standardisation (CEN), Validation of computational solid mechanics models, CEN Workshop Agreement, CWA 16799:2014 E.

Hack E & Lampeas G (Guest Editors) & Patterson EA (Editor), Special issue on advances in validation of computational mechanics models, J. Strain Analysis, 51 (1), 2016.

http://www.engineeringvalidation.org/