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The Siemens factory in Amberg, a small town in Bavaria, is a glorious feat of engineering.

In fact, it’s probably the most efficient factory in the world.

The plant produces 15m units a year – industrial control systems that are used in everything from cars to wind turbines.

That’s a tenfold increase in production since the plant opened in 1989.

And the plants managers have done that expanding the building or adding to the 1,200 workers employed.

The defect rate is close to zero, as 99.9988% of units require no adjustment – highly impressive when you consider that there are thousands of varieties of components.

What’s their secret?

It’s all down to the factory’s “digital twin”: a virtual version of the physical facility that resides within a computer system.

Every process in the Amberg factory is simulated in this digital factory.

It starts with the design phase. A model is built of the car and engineers tease and test all the components and materials.

Does the car bodywork have the lowest possible air resistance?

Do the electronics work reliably?

And when the units go into production, every aspect from the machines to plant controllers is simulated first in the digital factory.

There are almost no errors.

The digital twin allows endless design iterations to be tried in the virtual world without having to stop the production line to see how they can be made.

Welcome to Mirrorworld

In fact, Gartner predicts that by 2021, half of large industrial companies will use digital twins.

And this is part of a huge and fascinating story.

Over the last decade, companies have discovered that by creating digital twins of things – whether it be machines, streets, houses or people – they can study, design and radically improve them, conducting experiments at very little cost and totally reimaging how they work or can be manipulated.

Take Google Maps and Street View.

In ten years of moving through our neighbourhoods and cities the white Google Maps cars have created a digital model that we use every day.

It helps us to negotiate cities – finding bars, restaurants or fast routes through traffic.

And this digital model has been a fantastic laboratory for Google.

They have used to train their self-driving vehicles…

To track our movements and behaviour…

Everything they simulated was subjected to the power of their every improving algorithms.

And now, says Kevin Kelly in a recent wired article, the plan is to make a digital twin of everything else: our bodies, emotions, microbiome, genes, homes, cars.

Kelly calls this emerging platform “Mirrorworld”: “every place and thing in the real world—every street, building, and room—will have its full-size digital twin in the mirrorworld.

“Piece by piece, these virtual fragments are being stitched together to form a shared, persistent place that will parallel the real world.”

Your Digital Twin

We already have several tools that can create a digital map of our body, both external and internal – using 3D laser scanners, radiography and MRI.

We also have a growing number of wearables, along with both contact and embedded sensors that can track what is going on in our blood, gut and respiratory systems.

It won’t be long before you have a complete digital image of yourself, which you can speak to each morning in the mirror, giving you an instant read on your health and offering a branching tree of decisions for your day.

You’ll be able to ask…

How bad is my flu?

How hungover am I?

What would my face looked like if I stopped drinking wine for three weeks?

These digital twins will be able to read subtle changes in your face: changes that betray your mood, blood pressure, heart rate.

By recognising skin colour changes on the cheek for example, we can determine cardio-health such as blood pressure and arterial stiffness.

Google and ST Micro are also developing contact lenses that can detect glaucoma and diabetes.

We’ll soon be able to watch a drug taking hold, watching blood flowing through veins and arteries, or food and water working its way through our digestive system.

And it won’t be long before we have useful simulations of the brain.

We’ve seen how companies such as Affectiva are monitoring emotional responses using the cameras in our phones, computers and cars.

And how the OpenWater project is looking to map brain diseases and stimulate parts of the brain that are in decay.

The next decade will see a massive project by the likes of Google, Amazon and Apple – who all have serious ambitions to move into healthcare – to create a rich digital model of our brain and biology, just as Google Maps simulated the outside world.

Generative Design

The arrival of simulation software is already transforming engineering and manufacturing.

And this might be the most interesting angle from an investment point of view.

For example the otherworldly General Motors seat bracket (pictured below), which no team of human design engineers could have come up with

You can click on this video to see how to it was made.

It looks weird, like something an alien might design.

It’s also 40% lighter than GM’s current seat brackets and 20% stronger.

It is the creation of an Autodesk (Nasdaq: ADSK) generative design software system (GDS).

Having been fed the requirements of a piece for performance and materials, the software can simulate the most efficient proportions, offering a set of design options that no human could offer in months let alone hours of work.

The design is encoded as a set of competing ‘genes’ within a Darwinian, survival-of-the-fittest algorithm that cycles through millions of design choices, testing configurations and learning from each iteration what works and what doesn’t.

The GM seat bracket is a start and our thesis is that this type of generative design with utterly change manufacturing.

It will move on to a steep adoption curve by the early 2020s as auto and aerospace companies in particular drive to ‘lightweight’ components.

Everything from home appliances to hand tools to prosthetic organs are suitable for the GDS treatment.

In the next three years, it will greatly impact the $12 trillion global manufacturing industry, progressively deploying GDS throughout their factories.

A company such as Autodesk will have huge work.

If you’ve not read Kevin Kelly’s article on this coming mirrorworld, it’s well worth a spin.