Machines that autonomously detect when they need spare parts. Production systems that run their own quality control during operation, reducing inspection outlays. Robots that autonomously recognize and move components. Scenarios like these are gradually becoming a reality in industrial production.

They’re founded on future technologies like artificial intelligence (AI) and edge computing. These offer immense opportunities for the discrete and process industries because they open up new business models and productivity potential. This makes them indispensable to ensure industrial companies’ competitiveness in the world of tomorrow.

Data as the foundation for new technologies

The technologies of the future will be founded on the availability of data. And those data are becoming available in abundance, thanks to the digital transformation of industry. Digital solutions like Siemens’ Digital Enterprise portfolio are already reflecting every step in industrial production – from a product’s design, to its production, to its use – in virtual form, with what’s known as a digital twin.

What’s more, these steps are getting better and better interlinked to one another digitally, to yield extensive data pools. Future technologies now make it possible to analyse and exploit these data pools in entirely new ways.

Image: Siemens

The example of AI clearly shows what that means. In itself, AI isn’t especially new. Siemens, for example, installed neural networks in steel mills as far back as the 1990s. But the technology has made enormous progress since then.

Computing power has increased many times over. Algorithms have become much better. Hardware in factory halls performs better. And data transfer has accelerated immensely. That means the rising volume of available data can be collected and analysed many times faster and more comprehensively than before, and data analysis has become much more sophisticated.

To that end, we need platforms like MindSphere, Siemens’ open, cloud-based operating system for the Internet of Things (IoT).

Getting industry ready for future technologies

On a platform like this, users can do more than gather and view data – they can also analyse them using AI algorithms, and make their production processes more efficient on that basis.

For example, AI algorithms at Siemens’ Amberg plant use data from milling machines to tell when the machines’ spindles are reaching the end of their service lives and need to be replaced. That keeps unscheduled downtime to a minimum, saving costs of around €10,000 per machine each year.

And AI need not run exclusively on IoT platforms in the cloud. Thanks to higher-powered computers and higher-performance hardware, it can increasingly also operate in the factory hall itself – meaning right on the machine.

This technology is known as edge computing. Its advantage: intelligent applications can run on-site, with short transfer paths and almost real-time data processing. Besides that, data relevant to operations remain protected within the local environment – a connection to the cloud is needed only to update the AI applications.

Edge computing is already at work at Siemens’ Amberg plant, in quality control for circuit boards, for example. AI algorithms can tell from production data which circuit boards might be defective, so that only these identified components need to be inspected with X-rays. That has cut inspection costs by about 30%.

Image: Siemens

AI is also opening up entirely new possibilities for autonomous handling systems. To take just one example: it used to be necessary to engage in the time-consuming task of training robots with known objects, defining each movement and programming it in meticulous detail.

But AI enables handling systems to recognize even unknown objects, and to calculate the best gripping points for them. That capability finds its application in fully automated assembly lines for complex products like cars – lines that have to be as flexible as possible. To do that, robots must also be able to locate and move different components.

These future technologies are already a reality. But they still have far greater potential for making production more reliable, more efficient, and most importantly, more flexible. That’s the only way to meet the demand for increasingly customized products in small quantities, all the way down to lot size one – and what’s more, to do it quickly, with high quality, and at an attractive price.

Future success takes many actors working together

One thing is important in this context – future technologies always call for new paths in research and development. They can only be implemented successfully when companies of all sizes and in all industries work together, on an equal footing.

The key here is to combine digital and industrial expertise. Specific sectors have built up a deep knowledge of their industrial applications over decades, and that understanding is indispensable in applying digital solutions and artificial intelligence, edge computing and autonomous handling systems in industrial environments. What’s more, this complex topic calls for the skills of a very diverse range of actors from business, science and government.

Government must provide impetus for research, infrastructure, IT security, and education

It’s important to have the right regulatory impetus from government, in a coordinated form, across national borders. Four aspects are especially crucial here:

1. What’s needed is an ecosystem where innovations can grow – through support for application-related research and investments. That’s the only way future technologies can quickly be turned into usable products.

2. An area-wide IT infrastructure and fast internet access are basic requirements. Industry 4.0 needs, not just more bandwidth, but also very fast transfer times, combined with maximum availability. That’s indispensable for the future of industry. How should a small or medium-sized company, for example, get access to the digital future if its region does not have adequate access to the internet? This is where government needs to act.

3. IT security is essential to the success of Industry 4.0. Digitalization and cybersecurity have to go hand in hand. That’s why, early this year, Siemens and a number of partners developed what’s known as a Charter of Trust for cybersecurity. The aim is to establish general minimum standards for cybersecurity that are state of the art. At present, the Charter of Trust is supported by 16 companies and organizations.

Image: Siemens

4. All levels of education have to be reoriented to the new digital developments. Expanded skills in IT, software, programming, communications technology, IT security and data analysis will be indispensable for future industrial applications. That’s not something that can be procured overnight. We need to bring today’s and tomorrow’s employees along with us on this path to the future. This is the only way we’ll be able to take advantage of the vast opportunities that these future technologies have to offer.

Future technologies must fulfill a social purpose

Amid all this, technologies must never be considered purely in isolation. Of course they have to contribute to companies’ economic success. But they must also fulfill a social purpose, by contributing towards improving people’s lives.

Ultimately, people must always be the focus of attention. New technologies like artificial intelligence and edge computing can make people’s work less error-prone and create more room for creative tasks. But, contrary to an often-voiced opinion, they won’t replace people. Rather, these are simply technologies that will enable us to stay successful, especially in the B2B sector, and thus strengthen our business locations.

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