Production systems that run their own quality control during operation, reducing inspection outlays. Robots that autonomously recognize and move components.
They’re founded on future technologies.This makes them indispensable to ensure industrial companies’ competitiveness in the world of tomorrow.
Data as the foundation for new technologies
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.
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.
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
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.
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.
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.
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
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.
Manufacturing the future: The next era of global growth and innovation
Manufacturing the future: The next era of global growth and innovation, a major report from the McKinsey Global Institute, presents a clear view of how manufacturing contributes to the global economy today and how it will probably evolve over the coming decade. Our findings include the following points:
Manufacturing's role is changing. The way it contributes to the economy shifts as nations mature: in today's advanced economies, manufacturing promotes innovation, productivity, and trade more than growth and employment. In these countries, manufacturing also has begun to consume more services and to rely more heavily on them to operate.
Manufacturing is not monolithic. It is a diverse sector with five distinct groups of industries, each with specific drivers of success.
Manufacturing is entering a dynamic new phase. As a new global consuming class emerges in developing nations, and innovations spark additional demand, global manufacturers will have substantial new opportunities—but in a much more uncertain environment.
Manufacturing's role is changing
Globally, manufacturing continues to grow. It now accounts for approximately 16 percent of global GDP and 14 percent of employment. But the manufacturing sector's relative size in an economy varies with its stage of development. We find that when economies industrialize, manufacturing employment and output both rise rapidly, but once manufacturing's share of GDP peaks—at 20 to 35 percent of GDP—it falls in an inverted U pattern, along with its share of employment. The reason is that as wages rise, consumers have more money to spend on services, and that sector's growth accelerates, making it more important than manufacturing as a source of growth and employment.
The sector is also evolving in ways that make the traditional view—that manufacturing and services are completely separate and fundamentally different sectors—outdated. Service inputs (everything from logistics to advertising) make up an increasing amount of manufacturing activity. In the United States, every dollar of manufacturing output requires 19 cents of services. And in some manufacturing industries, more than half of all employees work in service roles, such as R&D engineers and office-support staff.
As advanced economies recover from the Great Recession, hiring in manufacturing may accelerate, and some nations may even raise net exports. Manufacturers will continue to hire workers, both in production and nonproduction roles (such as design and after-sales service). But in the long run, manufacturing's share of employment will remain under pressure as a result of ongoing productivity improvements, faster growth in services, and the force of global competition, which pushes advanced economies to specialize in activities requiring more skill (Exhibit 1).
Manufacturing is not monolithic
The largest segment by output (gross value added) includes industries such as autos, chemicals, and pharmaceuticals. These industries depend heavily on global innovation for local markets—they are highly R&D intensive—and also require close proximity to markets. The second-largest segment is regional processing, which includes industries such as printing and food and beverages. The smallest segment, with just 7 percent of global manufacturing value-added, produces labor-intensive tradables (Exhibit 2).
Manufacturers and policy makers need new approaches and capabilities
Companies must develop a highly detailed understanding of specific emerging markets, as well as the needs of their existing customers. They will also require agile approaches to the development of strategy—using scenario planning rather than point forecasts, for example. And they will have to make big bets on long-range opportunities, such as tapping new markets in developing economies or switching to new materials, but must do so in ways that minimize risk.
A critical challenge for manufacturers will be to approach footprint decisions in a more nuanced way. Labor-intensive industries will almost always follow the path of low wages, but others, with more complex needs, must weigh factors such as access to low-cost transportation, to consumer insights, or to skilled employees. The result could very well be a new kind of global manufacturing company—a networked enterprise that uses "big data" and analytics to respond quickly and decisively to changing conditions and can also pursue long-term opportunities.