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I've got a fantastic second keynote speaker, Professor Rob Miller.

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So Rob is the chair and Aristotle, technology director of the Little Lab at the University of Cambridge,

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director of the Rolls Royce University Technology Centre at the University Campus, as well.

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He's also a member of the Department for Transport Science Advisory Council,

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and his research focuses on the decarbonisation of the aerospace and power generation sectors and works closely with industry in his work.

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Now, having spoken to Rob, having looked at some of his is what he's led a number of really amazing initiatives over the years,

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which brought a huge amount of insight into how he might accelerate the development of solutions to tackle climate change.

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He's learnt a lot from these lessons. What lessons from his experiences?

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So with that, I hand over to rob I. We look forward to your talk. Thank you very much, Thomas.

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OK, so thank you for that kind introduction and really everything I'm going to talk about today, hopefully is going to end up in the building.

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You can see behind you on the first slide, which really is everything we've sort of learnt at the wet lab has been put into this new building,

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which we, we hope will enable us to drive innovative solutions at pace and scale to tackle the climate crisis in flight and land based power.

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Next slide. So to give you a bit of background to the Western laboratory, I think it's summed up by this photograph,

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you can see and this is the opening at the lab 50 years ago. And you can see Frank Whittle in the middle and really the team around.

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Emma is mostly Cambridge team who went off and invented the jet engine in nineteen thirty seven.

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You can see on the left this is the John Horlock who did a lot of the early design

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methods at Rolls and was the first director of the lab on his direct right.

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You've got. And so William Hawthorne,

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who developed the combustion chamber on the first engine had of engineering in Cambridge and on the far right Bob Fielden of Kings College Cambridge,

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who was let his Whittles design team and then went off and founded land based gas turbines at Rustan's.

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Now Siemens UK and Lincoln, and the importance of this slide, I think,

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is that these people were as happy in academia as they were in industry, and they crossed the boundaries frequently.

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And that was really the driving influence to a lot of the technologies, the primary technologies in universities,

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making it into the product over the last sort of 50 years we've built at the Weta lab on this on the right,

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you'll see Rolls-Royce, Mitsubishi and Siemens, and we've been major industrial partners.

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That's 50 years Dyson for eight years, Boeing, Lilium and reaction engines.

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Recently and pre-pandemic, any day you'd walk into the Weta lab and around the table, you would see designers in these companies.

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And similarly, if you were in these companies, you'd see with a lot of people hanging around.

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Which brings in just under 10 percent of the entire university's industrial income.

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And, you know, many people would say you either do sort of industrially focussed work or academic research,

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but for us it's brought sort of academic success that the the big prise in the field is called Gas Turbine Award,

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given once a year by the American Society of Mechanical Engineers.

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It's 1963 and and the Whistle Lab is one it 10 us less last 16 years.

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And I think that really is down to those industrial links, allowing us to find the real problems.

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OK, next slide. So what's what's what's the what's the problem that government industry academic boundary is trying to tackle?

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Well, we have to decarbonise by 2050, as you know, and this is an interesting graph you can see here.

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The y axis is CO2 emissions from aviation. And then you've got year on the x axis and the solid red line you can see is affected data.

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The dashed red line going forward is the ikos prediction of what the emissions from aviation will be.

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So you see it nearly doubling by 2050, and that graph has got in it an assumption of a two percent improvement in reduction in fuel burn per year.

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And that's tough because over the last 20, 30 years, we've only achieved 1.5 percent with everybody working really hard.

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And the graph we've got to get to is the green one. And as energy, you know who work in industry, the hardest thing is picking a graph.

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You know, there's billions of dollars being put into investment to get the graph even as good as it is.

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So we're going to have to do something dramatically different if we want to get onto that green curve.

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Now I'm going to argue that to decarbonise by 2050,

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we're going to going to need to develop more technologies of a wider variety of types in a shorter timescale.

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So the question is, how do we do that? Next slide. So and what happens at present and what is the limit?

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Why are we on that top graph?

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Well, the aviation sector has been stable for about 40 years, and that has led to a sector in which the sub system boundaries.

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And when I say subsystem boundaries, I mean the divide between the people who make the engines,

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the people who make the planes, the people who do the airports, all within the companies,

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the people who design the compressors or just turbines or combust as those subsystem boundaries have been frozen for decades.

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And the result is a research network that has encouraged each person, each silo, to specialise and optimise what they're doing.

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And I'd argue this has two major consequences.

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So if you look on the left, this is a typical technology developments process and used by the aerospace industry,

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and you can see the technical technology development silos in it.

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So this shows the y axis is technology readiness level and the x axis is yes.

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So if somebody has an idea down at the zero and it shows it takes 10 years to get back to a point where you can take it into a product.

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And the reason for that is you'll see, you know, in the blue, this is like a PhD going on in a specialist lab and then it moves over to the red.

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This is a sort of a higher technology readiness of medium speed regs.

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So at a different country, and this might be it coming to a UK aerospace company to do some design.

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And then it's got the big rig test has to be manufactured and then it might go off to Germany to test.

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And this whole process is slowing and putting it across the boundaries is where the 10 years come from that comes from.

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And this is not abnormal. So there was a report in 1999 by NASA where they analysed a range of technologies and they found an average of eight years.

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And I can tell you from my work with Mitsubishi or Siemens, this is not unusual.

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Around eight years from its product, it's the norm.

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The second problem is on the right, and that's discipline silos.

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So typically, if you have an idea for a new zero carbon technology,

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we've analysed those technologies that the future ones that will be needed for flight.

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And we found that 92 percent of them were highly multidisciplinary in nature.

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So it's very hard to fit them into any of the research labs at the moment that a relatively specialist.

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And so I would argue that the current technology development system will take a long time to move.

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These technologies might get product and will miss the best solutions in new areas in the design space that don't fit with the silos.

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Next slide. OK, so we're going to try and I want to show you some progress we're making on these two issues.

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So first, our success in breaking down technology development silos, this is the idea of taking TRL zero through to TRL six.

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Now there's a story here, because about eight years ago, I was out with a colleague in Cambridge for a drink and this this this colleague or friend,

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this was that was an error tester at Red Bull and and he asked me what I'd been doing.

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And at the time, I just we just developed a team of us at the Whittle, the second generation of three dimensional compressor blades,

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the Rolls Royce, and I explained how they worked and he thought they were really good.

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And then he asked me, When will they make engine? And I said six years and we set aside.

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And then I asked him what he'd been doing that day at Red Bull,

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and he tested 20 rear wings and he didn't understand how they worked, but he fitted a surface through the results.

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They predicted what the best was. They built it, tested it.

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It was the best. And he just emailed it to track and this was a Thursday night.

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And by track Red Bull have manufacturing tools and they made it overnight and it was on the car for practise the next day.

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And at that point, the penny dropped and Tony Dickens.

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We apply for money for the government to take his left Red Bull, and this is him sitting in one of our technology development teams at the witl.

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And since then, everything at the Whittle has changed. There's two major changes.

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The first one is that we now run small shop focussed teams that help to break down human communication barriers.

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And you can see one of our teams here made up of industry and academia multiple disciplines.

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We remove all top down management and bureaucracy. Milestones and deliverables go.

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And we have clear and objectives and which encourages fast, bold action.

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If you look on the left, here we have what we call a learning loop. Now this is you have an idea and you have to take this idea.

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You have to design it into a product, make it test it and learn.

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And you know, we're reasonably good at it in the world. But it was taking us six months to go around that loop.

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And so we focussed on each one of the circles in design.

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We've moved a lot more towards augmented and AI based design runs on running on graphics cards, the computer gaming,

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and that speeded the design process up by more than the factor of 100 in terms of rapid manufacture.

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3D printing is very good, but the real breakthrough was to move the supply chain in-house.

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Actual procurement was the real killer, and we actually connect the manufacture tools directly to the design tools.

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So a designer playing with a model can realise the model in the real world in about eight hours when it did take three months.

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And then finally,

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we do a value stream analysis on the whole testing process and we instead of instead of trying to improve the quality of each bits of the test,

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the accuracy we strip out time out of each of the processes, and we found we've changed about 95 percent or removed 95 percent of the processes.

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And we first cut the test times down four months to days.

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And with pick teams, we can do, we can rebuild and test the rig in 15 minutes.

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We did a formal trial funded by the Aerospace Technology Institute and with Rolls-Royce in 2017,

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and we took four technologies across the Rolls-Royce family around this loop in less than a week.

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And in 2005, that's taken us two years to do so.

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We named it 10 times quicker. But but but we ended up with 100 times quicker.

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And this is really important because if you're going to explore these new design spaces compete differently in spaces,

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you've got to fail fast, you've got to have the overhead on taking an idea into products and testing.

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It's got to draw. OK. Next slide. OK, so now success in breaking down disciplinary silos.

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I'd like to give you a number of examples.

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So first of all, on the left, you can see there's a lot of air propulsive configurations which are very different than conventional aircraft.

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And we've had quite a lot of success in putting together structural engineers as electrical

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engineers and aerodynamics to tackle those problems right from the beginning of the design process.

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In the middle, you can see this is work with Lilium on that design system and a company called Blue Badge,

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a small company in the UK which is building electric propulsion.

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And we've done a lot of whole system modelling and in fact, the bottom one, the blue bar exam place is a really good one, this one here.

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This is called a project called Project Inception, funded by the Aerospace Technology Institute,

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and it involves a series of small companies from sort of Formula One and electric

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drive teams to people who specialise in batteries to people who specialise in

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noise to the wet lab on aero and around this team when moving geometries from place

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to place really quickly and changing the way that those problems are tackled.

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So the rapid technology teams sort of span those problems.

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And then on the right, we've had quite a lot of success working with the Turing Institute and Rolls-Royce,

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linking together machine learning and aerodynamics.

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And you can see in the top left corner, this actually is some work done on damaged blades and the effect they have on engines.

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And you'll see in this team you've got a Rolls-Royce fellow James Taylor.

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You've got Bryce Conduite, who's one of the senior A.I. members at Rolls-Royce, and Harry Simpson, who is a Rolls-Royce compressor designer.

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And they are literally all around the rig and the AI system is telling them which geometries to test,

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and they're changing the rig around life to do the test, to populate the A.I. system.

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So this approach is having sort of impact across a range of areas.

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Next slide. So I thought I'd give you a little more detail on on,

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I think two of the most challenging problems we've taken on in spanning the discipline silos and the first one was at the

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start of the pandemic and this is called the of the ventilator project or open source ventilation system initiative.

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And the aim here was sort of at the start of the pandemic when we thought we would need ventilators.

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We decided that we would put together a team to try and build the first clinical grade ventilator

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that could work all the way from CPAP through to clinical grade ventilation ventilation.

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Could we do that with it manufactured in Africa at about a tenth of the cost of other ventilators?

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And we switched our rapid technology development teams over from climate change to to the pandemic.

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And you can see the members of the team we had in the top circle.

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These are people from Cambridge departments.

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We then had people from Adam Brooks, who are specialists in ventilation and from South Africa and one of their chief medical people.

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We have start-ups from the Cambridge cluster who volunteered.

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And then we had finally big companies such as Beco in Turkey, DfI in South Africa, Denel in South Africa and Prodrive Racing Team in the UK.

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And you can see one of our teams in the photograph.

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On the left, you can see two wet lab academics on the right.

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You see three from start ups in Cambridge and in the background.

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On the video link, you can see people from DfI and Jindal in South Africa.

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And so these teams were working virtually and physically on rapidly building components and testing them for the ventilator,

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and they were successful in the first 20.

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Ventilators came off the production line in South Africa,

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and the project was awarded a president's special award medal from the Royal Academy of Engineering.

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Next slide. So here's another one, and this is this is another challenge.

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It's called the Aviation Impact Accelerator,

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and this originated when the Prince of Wales visited the Weta lab and ran a roundtable on decarbonising aviation.

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And he followed this up with another roundtable at Clarence House that you can see in the photograph.

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And the Prince of Wales had been very impressed with the rapid technology teams and said,

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Would it be possible to use these teams to take on the whole system's challenge of how you could unlock change in the larger aviation system?

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And that's exactly what we've done. So you can see the group of partners here.

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It has departments from across Cambridge in our in our airspace and sustainable leadership,

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the Judge Business School, the Bennett Institute Chemical Engineering Institute.

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But we also have teams from UCL working on the network modelling and Melbourne University working on field productions.

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And this is funded by the World Economic Forum and is association with the Prince of Wales Sustainable Markets Initiative.

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And we also have a range of industrial advisers now. These aren't industrial advisers that you meet once a year.

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What we've done here is we have access to the deep technology within those teams,

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so we're working very closely with the technologists in there to make sure the models grounded.

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The aim of the model is to produce a David Mackay model.

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How many of you have heard of sustainable energy without the hot air?

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It's a simple model, but it allows you to put the whole energy system and of the UK, and we're building a similar system for flight.

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So it goes from power generation all the way through fuel production, through distribution to the journey.

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And you can see one of the prototype models up and running here.

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Next slide. So hopefully you can see some of the success in the past and going forward.

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Our aim is to build what we understand into a UK integrated technology accelerator.

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And you can this is a cut through that, that building and I would view that building not as a building, but really as a machine,

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because it's every part of it has been designed to try and optimise what I've talked about with technology development silos and silos.

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OK, next slide. So first of all, around the central courtyard, we have a range of disciplines,

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so we are co-locating as well as our and I'm assistant fermenting nemesis chemistry policy,

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electrical deep learning and the the the Advanced Manufacturing Centre in Sheffield will have a satellite office in it to look at the manufacturing.

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And then we have a challenge space which allows those people to come together in a digital environment to explore at the early stage.

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The systems design issues of various components with industry.

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Next slide. So the next thing is we need to embed at the heart of this process, training the next generation of leaders in the field.

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And we have the basic centre of doctoral training in future power and propulsion embedded in the heart of the building.

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And that will take the first year PhD students from Oxford, Cambridge and Loughborough.

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Little will all embed themselves that first year in this culture.

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Next slide. Finally, these teams have got to have access to be able to realise things and test them in the digital

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world and the physical world at speed to then compare them in with the digital world.

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And so we have the data laboratories, we have the rapid manufacturing capability, we have a rapid assembly garage and then a test facility,

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which will allow us to move around the space very quickly, rapidly testing concepts.

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OK. Next slide, please. So this building will cost just under 50 million.

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We've raised 25 million of it through government, industry and academia.

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Unfortunately, the pandemic has made the rest of the fundraising incredibly difficult.

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And if we can't raise the remaining twenty four and a half million, then quickly, then I'm afraid this project won't happen.

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So we, if there's any help on that, please let us know and you can see there's a link at the bottom that you can look at.

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It will show you what we're trying to do. OK, next slide.

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I thought I would end by just going through some of the things which seem to work.

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It's very hard to sort of come to firm conclusions, but I can tell you things that work.

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So the first thing is culture that's so important.

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If you don't get the culture right in the building, there's no point in even trying to get pace and simplicity.

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The second one is to embed Real-World experience, industry and policy in the teams from day one.

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So you get the right industrialists, the right policy, people in that team, then you can really ask the right question.

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Third, make sure your teams are small and sharp focussed.

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That really helps to break down human communication barriers.

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As soon as you start scaling the meetings, kill you for removal of top down management and bureaucracy encourages fast, bold action.

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So you really need to remove milestones and deliverables.

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And you need to start all the management meetings and you need to really focus on on

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on allowing the team to move in a flexible way fast focussed delivery of funding.

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So when you find a good opportunity, funding needs to be delivered quickly.

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So long funding processes don't work at zero friction legal framework, so you really need for us.

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The Rolls-Royce relationship is really useful for this,

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but you need to be able to connect with somebody and start a project within a day and legal usually stops that.

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Access to high level industrial strategy, if you going to ask the right questions, you've got to know what the real problems are.

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And again, relationships like one between the wetland roles are invaluable in that.

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Finally, like communication overheads, so we tend to run.

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We only have meetings which are technically focussed and we communicate rapidly in WhatsApp groups.

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That's that's much better than having any management meeting.

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OK, next slide. So finally, I thought I'd leave you with three questions, as you'll be discussing things this afternoon.

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The first one is funding a charity. Funding agility is key.

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Can funding be based on good taste? So the normal way would be peer review.

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And when I took over at the witl, I analysed back analyse a lot of the projects which had been successful and made engine.

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And what I found to my surprise was that the projects which had worked were mostly projects where Rolls-Royce or

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Mitsubishi had had good taste in choosing the person and the projects to do or being involved in that process.

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And that, through peer review, peer review will not allow you to ask really adventurous questions in that way.

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So who are you going to trust to put the money in? Second one operational agility.

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So can we switch from a mine milestone and deliverable based world to an objective based world?

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So if you're going to ask adventurous questions, you've got to change the question frequently.

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And milestones and deliverables will lock you into one way of seeing the world and say, doom you to failure.

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Really, silo agility is not not a great phrase, but and you know, if you're going to bridge barriers,

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either bringing new small companies together with large companies to see the world differently than there is massive legal barriers in doing that.

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How would you do that more quickly? And then finally, at 42, you know,

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Douglas Adams fans in the audience will know what that means in Hitchhiker's Guide to the Galaxy they

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invent of incredibly large computer that takes millions of years to discover the meaning of life.

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And the answer comes out 42 is 42, and when they all look around in a puzzled way, the computer tells them that the answer is the easy thing.

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It's the question that's difficult. And they build a new biological, even bigger computer of the Earth to try and solve that problem.

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And that's incredibly insightful because actually,

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the difficult thing when you're moving into novel design spaces is to know what the question

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is and usually answering the question once you've articulated it properly is relatively easy.

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So you need in all of these things to find ways of allowing people to change completely.

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The questions their acts, asking maybe hundreds of times before they really get the results that you want.

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OK, thank you. Thank you very much, Rob, for that incredibly interesting and insightful talk.

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I think there's a lot of interesting chat on the stage.

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There's lots of questions things will come out of that and really helps set up the discussions later in the breakout groups.