I've got a fantastic second keynote speaker, Professor Rob Miller.
So Rob is the chair and Aristotle, technology director of the Little Lab at the University of Cambridge,
director of the Rolls Royce University Technology Centre at the University Campus, as well.
He's also a member of the Department for Transport Science Advisory Council,
and his research focuses on the decarbonisation of the aerospace and power generation sectors and works closely with industry in his work.
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,
which brought a huge amount of insight into how he might accelerate the development of solutions to tackle climate change.
He's learnt a lot from these lessons. What lessons from his experiences?
So with that, I hand over to rob I. We look forward to your talk. Thank you very much, Thomas.
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.
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,
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.
Next slide. So to give you a bit of background to the Western laboratory, I think it's summed up by this photograph,
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.
Emma is mostly Cambridge team who went off and invented the jet engine in nineteen thirty seven.
You can see on the left this is the John Horlock who did a lot of the early design
methods at Rolls and was the first director of the lab on his direct right.
You've got. And so William Hawthorne,
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,
who was let his Whittles design team and then went off and founded land based gas turbines at Rustan's.
Now Siemens UK and Lincoln, and the importance of this slide, I think,
is that these people were as happy in academia as they were in industry, and they crossed the boundaries frequently.
And that was really the driving influence to a lot of the technologies, the primary technologies in universities,
making it into the product over the last sort of 50 years we've built at the Weta lab on this on the right,
you'll see Rolls-Royce, Mitsubishi and Siemens, and we've been major industrial partners.
That's 50 years Dyson for eight years, Boeing, Lilium and reaction engines.
Recently and pre-pandemic, any day you'd walk into the Weta lab and around the table, you would see designers in these companies.
And similarly, if you were in these companies, you'd see with a lot of people hanging around.
Which brings in just under 10 percent of the entire university's industrial income.
And, you know, many people would say you either do sort of industrially focussed work or academic research,
but for us it's brought sort of academic success that the the big prise in the field is called Gas Turbine Award,
given once a year by the American Society of Mechanical Engineers.
It's 1963 and and the Whistle Lab is one it 10 us less last 16 years.
And I think that really is down to those industrial links, allowing us to find the real problems.
OK, next slide. So what's what's what's the what's the problem that government industry academic boundary is trying to tackle?
Well, we have to decarbonise by 2050, as you know, and this is an interesting graph you can see here.
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.
The dashed red line going forward is the ikos prediction of what the emissions from aviation will be.
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.
And that's tough because over the last 20, 30 years, we've only achieved 1.5 percent with everybody working really hard.
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.
You know, there's billions of dollars being put into investment to get the graph even as good as it is.
So we're going to have to do something dramatically different if we want to get onto that green curve.
Now I'm going to argue that to decarbonise by 2050,
we're going to going to need to develop more technologies of a wider variety of types in a shorter timescale.
So the question is, how do we do that? Next slide. So and what happens at present and what is the limit?
Why are we on that top graph?
Well, the aviation sector has been stable for about 40 years, and that has led to a sector in which the sub system boundaries.
And when I say subsystem boundaries, I mean the divide between the people who make the engines,
the people who make the planes, the people who do the airports, all within the companies,
the people who design the compressors or just turbines or combust as those subsystem boundaries have been frozen for decades.
And the result is a research network that has encouraged each person, each silo, to specialise and optimise what they're doing.
And I'd argue this has two major consequences.
So if you look on the left, this is a typical technology developments process and used by the aerospace industry,
and you can see the technical technology development silos in it.
So this shows the y axis is technology readiness level and the x axis is yes.
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.
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.
This is a sort of a higher technology readiness of medium speed regs.
So at a different country, and this might be it coming to a UK aerospace company to do some design.
And then it's got the big rig test has to be manufactured and then it might go off to Germany to test.
And this whole process is slowing and putting it across the boundaries is where the 10 years come from that comes from.
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.
And I can tell you from my work with Mitsubishi or Siemens, this is not unusual.
Around eight years from its product, it's the norm.
The second problem is on the right, and that's discipline silos.
So typically, if you have an idea for a new zero carbon technology,
we've analysed those technologies that the future ones that will be needed for flight.
And we found that 92 percent of them were highly multidisciplinary in nature.
So it's very hard to fit them into any of the research labs at the moment that a relatively specialist.
And so I would argue that the current technology development system will take a long time to move.
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.
Next slide. OK, so we're going to try and I want to show you some progress we're making on these two issues.
So first, our success in breaking down technology development silos, this is the idea of taking TRL zero through to TRL six.
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,
this was that was an error tester at Red Bull and and he asked me what I'd been doing.
And at the time, I just we just developed a team of us at the Whittle, the second generation of three dimensional compressor blades,
the Rolls Royce, and I explained how they worked and he thought they were really good.
And then he asked me, When will they make engine? And I said six years and we set aside.
And then I asked him what he'd been doing that day at Red Bull,
and he tested 20 rear wings and he didn't understand how they worked, but he fitted a surface through the results.
They predicted what the best was. They built it, tested it.
It was the best. And he just emailed it to track and this was a Thursday night.
And by track Red Bull have manufacturing tools and they made it overnight and it was on the car for practise the next day.
And at that point, the penny dropped and Tony Dickens.
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.
And since then, everything at the Whittle has changed. There's two major changes.
The first one is that we now run small shop focussed teams that help to break down human communication barriers.
And you can see one of our teams here made up of industry and academia multiple disciplines.
We remove all top down management and bureaucracy. Milestones and deliverables go.
And we have clear and objectives and which encourages fast, bold action.
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.
You have to design it into a product, make it test it and learn.
And you know, we're reasonably good at it in the world. But it was taking us six months to go around that loop.
And so we focussed on each one of the circles in design.
We've moved a lot more towards augmented and AI based design runs on running on graphics cards, the computer gaming,
and that speeded the design process up by more than the factor of 100 in terms of rapid manufacture.
3D printing is very good, but the real breakthrough was to move the supply chain in-house.
Actual procurement was the real killer, and we actually connect the manufacture tools directly to the design tools.
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.
And then finally,
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,
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.
And we first cut the test times down four months to days.
And with pick teams, we can do, we can rebuild and test the rig in 15 minutes.
We did a formal trial funded by the Aerospace Technology Institute and with Rolls-Royce in 2017,
and we took four technologies across the Rolls-Royce family around this loop in less than a week.
And in 2005, that's taken us two years to do so.
We named it 10 times quicker. But but but we ended up with 100 times quicker.
And this is really important because if you're going to explore these new design spaces compete differently in spaces,
you've got to fail fast, you've got to have the overhead on taking an idea into products and testing.
It's got to draw. OK. Next slide. OK, so now success in breaking down disciplinary silos.
I'd like to give you a number of examples.
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.
And we've had quite a lot of success in putting together structural engineers as electrical
engineers and aerodynamics to tackle those problems right from the beginning of the design process.
In the middle, you can see this is work with Lilium on that design system and a company called Blue Badge,
a small company in the UK which is building electric propulsion.
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.
This is called a project called Project Inception, funded by the Aerospace Technology Institute,
and it involves a series of small companies from sort of Formula One and electric
drive teams to people who specialise in batteries to people who specialise in
noise to the wet lab on aero and around this team when moving geometries from place
to place really quickly and changing the way that those problems are tackled.
So the rapid technology teams sort of span those problems.
And then on the right, we've had quite a lot of success working with the Turing Institute and Rolls-Royce,
linking together machine learning and aerodynamics.
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.
And you'll see in this team you've got a Rolls-Royce fellow James Taylor.
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.
And they are literally all around the rig and the AI system is telling them which geometries to test,
and they're changing the rig around life to do the test, to populate the A.I. system.
So this approach is having sort of impact across a range of areas.
Next slide. So I thought I'd give you a little more detail on on,
I think two of the most challenging problems we've taken on in spanning the discipline silos and the first one was at the
start of the pandemic and this is called the of the ventilator project or open source ventilation system initiative.
And the aim here was sort of at the start of the pandemic when we thought we would need ventilators.
We decided that we would put together a team to try and build the first clinical grade ventilator
that could work all the way from CPAP through to clinical grade ventilation ventilation.
Could we do that with it manufactured in Africa at about a tenth of the cost of other ventilators?
And we switched our rapid technology development teams over from climate change to to the pandemic.
And you can see the members of the team we had in the top circle.
These are people from Cambridge departments.
We then had people from Adam Brooks, who are specialists in ventilation and from South Africa and one of their chief medical people.
We have start-ups from the Cambridge cluster who volunteered.
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.
And you can see one of our teams in the photograph.
On the left, you can see two wet lab academics on the right.
You see three from start ups in Cambridge and in the background.
On the video link, you can see people from DfI and Jindal in South Africa.
And so these teams were working virtually and physically on rapidly building components and testing them for the ventilator,
and they were successful in the first 20.
Ventilators came off the production line in South Africa,
and the project was awarded a president's special award medal from the Royal Academy of Engineering.
Next slide. So here's another one, and this is this is another challenge.
It's called the Aviation Impact Accelerator,
and this originated when the Prince of Wales visited the Weta lab and ran a roundtable on decarbonising aviation.
And he followed this up with another roundtable at Clarence House that you can see in the photograph.
And the Prince of Wales had been very impressed with the rapid technology teams and said,
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?
And that's exactly what we've done. So you can see the group of partners here.
It has departments from across Cambridge in our in our airspace and sustainable leadership,
the Judge Business School, the Bennett Institute Chemical Engineering Institute.
But we also have teams from UCL working on the network modelling and Melbourne University working on field productions.
And this is funded by the World Economic Forum and is association with the Prince of Wales Sustainable Markets Initiative.
And we also have a range of industrial advisers now. These aren't industrial advisers that you meet once a year.
What we've done here is we have access to the deep technology within those teams,
so we're working very closely with the technologists in there to make sure the models grounded.
The aim of the model is to produce a David Mackay model.
How many of you have heard of sustainable energy without the hot air?
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.
So it goes from power generation all the way through fuel production, through distribution to the journey.
And you can see one of the prototype models up and running here.
Next slide. So hopefully you can see some of the success in the past and going forward.
Our aim is to build what we understand into a UK integrated technology accelerator.
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,
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.
OK, next slide. So first of all, around the central courtyard, we have a range of disciplines,
so we are co-locating as well as our and I'm assistant fermenting nemesis chemistry policy,
electrical deep learning and the the the Advanced Manufacturing Centre in Sheffield will have a satellite office in it to look at the manufacturing.
And then we have a challenge space which allows those people to come together in a digital environment to explore at the early stage.
The systems design issues of various components with industry.
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.
And we have the basic centre of doctoral training in future power and propulsion embedded in the heart of the building.
And that will take the first year PhD students from Oxford, Cambridge and Loughborough.
Little will all embed themselves that first year in this culture.
Next slide. Finally, these teams have got to have access to be able to realise things and test them in the digital
world and the physical world at speed to then compare them in with the digital world.
And so we have the data laboratories, we have the rapid manufacturing capability, we have a rapid assembly garage and then a test facility,
which will allow us to move around the space very quickly, rapidly testing concepts.
OK. Next slide, please. So this building will cost just under 50 million.
We've raised 25 million of it through government, industry and academia.
Unfortunately, the pandemic has made the rest of the fundraising incredibly difficult.
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.
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.
It will show you what we're trying to do. OK, next slide.
I thought I would end by just going through some of the things which seem to work.
It's very hard to sort of come to firm conclusions, but I can tell you things that work.
So the first thing is culture that's so important.
If you don't get the culture right in the building, there's no point in even trying to get pace and simplicity.
The second one is to embed Real-World experience, industry and policy in the teams from day one.
So you get the right industrialists, the right policy, people in that team, then you can really ask the right question.
Third, make sure your teams are small and sharp focussed.
That really helps to break down human communication barriers.
As soon as you start scaling the meetings, kill you for removal of top down management and bureaucracy encourages fast, bold action.
So you really need to remove milestones and deliverables.
And you need to start all the management meetings and you need to really focus on on
on allowing the team to move in a flexible way fast focussed delivery of funding.
So when you find a good opportunity, funding needs to be delivered quickly.
So long funding processes don't work at zero friction legal framework, so you really need for us.
The Rolls-Royce relationship is really useful for this,
but you need to be able to connect with somebody and start a project within a day and legal usually stops that.
Access to high level industrial strategy, if you going to ask the right questions, you've got to know what the real problems are.
And again, relationships like one between the wetland roles are invaluable in that.
Finally, like communication overheads, so we tend to run.
We only have meetings which are technically focussed and we communicate rapidly in WhatsApp groups.
That's that's much better than having any management meeting.
OK, next slide. So finally, I thought I'd leave you with three questions, as you'll be discussing things this afternoon.
The first one is funding a charity. Funding agility is key.
Can funding be based on good taste? So the normal way would be peer review.
And when I took over at the witl, I analysed back analyse a lot of the projects which had been successful and made engine.
And what I found to my surprise was that the projects which had worked were mostly projects where Rolls-Royce or
Mitsubishi had had good taste in choosing the person and the projects to do or being involved in that process.
And that, through peer review, peer review will not allow you to ask really adventurous questions in that way.
So who are you going to trust to put the money in? Second one operational agility.
So can we switch from a mine milestone and deliverable based world to an objective based world?
So if you're going to ask adventurous questions, you've got to change the question frequently.
And milestones and deliverables will lock you into one way of seeing the world and say, doom you to failure.
Really, silo agility is not not a great phrase, but and you know, if you're going to bridge barriers,
either bringing new small companies together with large companies to see the world differently than there is massive legal barriers in doing that.
How would you do that more quickly? And then finally, at 42, you know,
Douglas Adams fans in the audience will know what that means in Hitchhiker's Guide to the Galaxy they
invent of incredibly large computer that takes millions of years to discover the meaning of life.
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.
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.
And that's incredibly insightful because actually,
the difficult thing when you're moving into novel design spaces is to know what the question
is and usually answering the question once you've articulated it properly is relatively easy.
So you need in all of these things to find ways of allowing people to change completely.
The questions their acts, asking maybe hundreds of times before they really get the results that you want.
OK, thank you. Thank you very much, Rob, for that incredibly interesting and insightful talk.
I think there's a lot of interesting chat on the stage.
There's lots of questions things will come out of that and really helps set up the discussions later in the breakout groups.