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Inevitable futures – manufacturing

I recently finished Kevin Kelly’s “The Inevitable” – it’s good, positive, often revealing. But I want to work through some of the ideas and see what scenarios they might open up. First up – manufacturing.

When I left university in the late 1980s, I worked for a small multinational manufacturing conglomerate, and I saw a fair few factories on the inside. They were dirty, noisy places, with humans and machines interacting to transform one thing into another – aggregate, lime and cement into concrete, wood, laminate and hardware into kitchens, etc. The factories were large, and housed multiple specialized machines, storage areas for raw materials, intermediate products and finished goods. Human beings both controlled the process and did the work machines could not – from driving forklift trucks to cleaning the machines, or fixing them when they broke. Controlling the process was a big deal – most of the factories I worked in had roughly the same number of “administrative” staff as shop floor workers. Even though the factories made similar or even identical products every day, there were regular crises – machines breaking down, suppliers delivering late, customers changing their orders at the last minute.

Recently, I was lucky enough to visit the Rolls Royce Motor Car factory in the Sussex countryside. The contrast was amazing – it’s quiet, clean, controlled. Even though every car they produce is different, the process was almost serene. Far less of the factory was dedicated to “storing stuff”, and there were far fewer dedicated machines.

Of course, that’s because Rolls Royce mostly assemble and finish cars in their factory – most of the components that go into the car are made somewhere else. At Goodwood, they are put together, painted, polished, and generally glammed up with leather, wood, and all the other items that make a luxury car.

Now, I also got to have a look inside the engine plant of a motorcycle manufacturer a few years ago. I was expecting much more industrial grit – after all, engines are big, complicated things, made out of metal. Surely there would be lots of noise, and flashing lights and…well, no. Turns out that building an engine is also mostly assembling components delivered by suppliers.

I’m pretty sure it’s turtles all the way down.

The modern factory is possible only because we can process and exchange data across the globe, instantaneously. In the late 80s, we would fax or phone through orders to our suppliers; I spent a few months in the “planning” department, working out different ways to sequence customer orders to optimize production efficiency by shuffling index cards on a big felt board. We would then feed those plans into our manufacturing resource planning software, which in turn would spit out purchase orders (which we’d fax or phone through to our suppliers). We had lots of people throughout the factory collecting data (usually with a clipboard), and then feeding that into the computer.

Today, of course, most companies communicate orders directly, and factories gather their own data; the computer is much better at optimizing production capacity than a human could ever be, and as a result, the role of the human is increasingly about doing the things machines can’t do (yet).

I’m also pretty sure that this is just the beginning.

Once we have robots that can do tasks only humans can do today, self-driving lorries, 3D printing and nano manufacturing it’s easy to imagine lots of different scenarios. I’d like to consider one.

The local manufactury.

Right now, the cost of labour determines where we make most things – and as that’s cheap in China, Vietnam, Mexico, etc. our global economy takes raw materials, sends them (usually over great distances) to those cheap labour places where they get transformed into products we want to buy, and then ship them halfway around the world again for consumption in the West.

What happens once robots can replace that cheap labour?

Of course the other reason to have a “car factory” or a “shoe factory” or a “phone factory” is to have a store of knowledge and skills. Some of those skills are directly related to the product – welding, sewing, assembling small electrical components. Many of those skills are organisational – “how do we do things around here?”. Some relate to design – the development of new products.

It’s not ridiculous to imagine that much of this knowledge – especially the skills and organisational skills – can migrate into computers.

If these trends continue, maybe the cost of shipping things around the world becomes critical. Maybe every neighbourhood gets a local manufactury – a building with pluripotent robots, 3D printers and nano-bots, managed by a scheduling AI, integrated into a supply network. Customers choose a product – from an “off-the-shelf” design, or by customizing a design, or by commissioning a design from a specialist, and send the order to the manufactury. The manufactury looks at the bill of materials, and places orders with its supply network; self-driving vehicles deliver the materials, and the manufactury schedules the robots to build the finished product, which – of course – is then delivered to the customer using a self-driving delivery van. Or a drone.

To create a shirt, the manufactury would order cotton, buttons, etc. – either in bulk (if the purchasing algorithm decides that keeping a stock of cotton makes sense) or “just enough”. The nanobots would create dies to colour the cotton, and a robot would follow the pattern to cut the cotton into the components for a shirt, and stitch it together.

You could easily imagine such a manufactury making clothes, furniture, electrical components, household goods etc.

The economics would be interesting – but I imagine that the price of an object would be driven partly by the cost of the design and raw materials, and partly by the time the customer is prepared to wait. The economies of scale don’t go away – clearly making dozens, hundreds or thousands of the same product would be much cheaper than one-offs. You could imagine clever scheduling algorithms, aggregating demand from multiple neighbourhoods, so that when the threshold is reached for a particular product, one of the manufacturies configures itself to satisfy that demand. Of course, this could apply to finished goods and to intermediate products – manufacturies converting raw cotton to thread, thread to cloth etc. You can also imagine how specialized equipment – weaving looms, injection moulding presses etc. – would continue to offer significant cost advantages.

When? How?

This is just speculation. There are many leaps of faith – I’m pretty sure I made up “pluripotent robot” as a phrase, and while 3D printing and nano-materials are not purely speculation, they’re also not yet ubiquitous. Lights-out factories are still not mainstream, let alone factories that can re-configure themselves every day.

But ecommerce and digitisation means we’re all spending less time on the high street, and becoming more accustomed to ordering stuff on the internet and have it turn up. Amazon especially is innovating logistics and supply chains – I can order coffee beans and printer ink on my phone, and they will deliver it within 2 hours.

So, if this happens, I’d bet it would be a company like Amazon who leads the way – they already have highly automated distribution centers, so the jump to manufacture isn’t quite such a big one. They have the computing power, and the customer insight.

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