The next manufacturing revolution is here

22

September

2016

5/5 (1)

Nowadays, growth is fading away and it’s a big deal. Our global economy stops growing and it’s not new. Growth has actually declined over the last 50 years. If we look at the history of growth, times of big growth have always been fueled by big manufacturing revolutions. It happened three times, every 50-60 years. The steam engine in the middle of the 19th century, the mass-production model in the beginning of the 20th century – thanks, Mr. Ford. And the first automation wave in the 1970s. Those manufacturing revolutions have created huge growth, because they have improved productivity. It’s rather simple: in order to grow, we need to be producing more, putting more into our economy. Each time, productivity has been the growth lever.

Over the last years we failed at reinventing the manufacturing space, and large technological innovations have played away from it. But the fourth manufacturing revolution will combine manufacturing and technological innovations and it’s already happening right now. Major technologies are entering the manufacturing space and will boost industrial productivity by more than a third which will create growth.
Here are some examples of the manufacturing revolution at play:
• Manufacturing robots that will collaborate with humans and can be programmed in order to perform complex, non-repetitive tasks. Today 8% of the tasks are automated and by 2025, 25 percent of the tasks will be. So advanced robot will contribute to 20 percent additional growth.
• Additive manufacturing, 3D printing. 3D printing has already improved plastic manufacturing and it’s now making its way through metal. Those are not small industries. Plastic and metals represent 25 percent of global manufacturing production.
• Other like: horizontal/vertical integration, augmented reality, simulation, big data and analysis, …

The new manufacturing revolution is not only about more productivity but also about producing better, smarter products. It’s about scale customization. Imagine a world where you can buy the exact products you want with the functionalities you need, with the design you want, with the same cost and lead time as a product that’s been mass produced. The new manufacturing revolution makes it possible.
It will also create a huge macroeconomic shift: factories will be relocated into our home market and those will be smaller and agile. Scale does not matter anymore, flexibility does. They will be operating on a multi-product, made-to-order basis. The change will be drastic.

This fourth manufacturing revolution is a chance for all of us. If we play it right, we’ll see sustainable growth in all of our economies.

Source:
• https://www.atkearney.com/documents/10192/5992684/3D+Printing+A+Manufacturing+Revolution.pdf/bf8f5c00-69c4-4909-858a-423e3b94bba3
• https://www.ted.com/talks/olivier_scalabre_the_next_manufacturing_revolution_is_here
• https://www.youtube.com/watch?v=yjuzeLsoGSo
• http://www.nextmanufacturingrevolution.org/
• http://www.mckinsey.com/business-functions/operations/our-insights/digital-manufacturing-the-revolution-will-be-virtualized
• https://www.linkedin.com/pulse/20140915075150-11691688-the-evolution-of-the-digital-manufacturing-business
• http://www.criticalmanufacturing.com/de/newsroom/blog/posts/blog/industry-4-0-the-next-revolution-is-here#.V-OL5KKLRcw

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Data into actions

15

September

2016

5/5 (1)

Today’s information has no limit. Each day the world generates about 2,5 trillion bytes of data such that 90% of the data in the world were created in the last two years. Those data come from everywhere and takes the form of anything: form of messages, updates and images posted to social networks; readings from sensors, GPS signals from cell phones and much more.
There are different ways/models to deal with those data in order to transform input (data) into output (knowledge). And based on this knowledge we can take actions.

Artificial Intelligence

Big data can be used in artificial intelligence. A famous example is Alphago, which is an informatics program that plays the game « go » using an algorithm based on deep learning. This program developed by Google Deepmind has beaten Lee Sedol, one of the best players worldwide, in March 2016. Nevertheless, it is more correct to say that a player with a computer has beaten a player without computer than to say that a computer has beaten a player.
There are always and there will always be people behind the model. An informatics model can deduce, but it doesn’t mean that it will ever be able to induce where people can do both. Concepts, strategies are built through the induction where hypothesis are elaborated from observations. While consequences are build from premises through deduction. Therefore artificial intelligence would not be able to run a company on his own.

Business decisions

Over the last year, we have observed a change regarding the quality of service. Company used the available data to learn more about their clients and truly understand their needs. This lead to offer a better quality service which is beneficial for both companies and clients. For the future, we could expect a lot more of changes based on the amount of data that will be generated.
Could it be possible that companies would know so much about us that they would be able to satisfy our needs before we could actually think about it?
It seems that autonomous cars are likely to be part of tomorrow’s world. So, e.g., could I get out of my house at 8pm to go play tennis, like every Monday, and get an autonomous car that would be waiting for me in front of my house without having to reserve it? Could we go to the supermarket to pick up a food package that is waiting for us without having given the details ourselves? Moreover, could we even find it in front of our door in the morning?

How will the service of tomorrow look like with the influence of big data?

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