“We need to understand the value of data.”

“We need to understand the value of data.”
Marginal Column
Prof. Dr.-Ing. Matthias Putz

Prof. Dr.-Ing. Matthias Putz,
Head of the Fraunhofer Institute for Machine Tools and Metal Working (IWU) and is responsible for the academic fields of machine tools, production systems, and machining. He holds the chair in machine tools and metal working at the TU Chemnitz and is Honorary Professor of integrated manufacturing at the HTW Dresden. He studied mechanical engineering, specializing in hydraulics and automation. He is a member of the International Academy for Production Technology (CIRP) and coordinator of the Fraunhofer flagship project E3 production

Copyright Photo: Fraunhofer-IWU

Content

March 2017

 

Professor Matthias Putz believes that Big Data brings major opportunities for production technology – and calls for an open but targeted approach.

Big Data sounds like a promise of salvation that will offer the manufacturing industry a golden future. Are expectations too high?

I don’t think so. Big Data means managing complexity and using it to our advantage, whether it is in society, biology, weather research, or production technology. There are links that we previously had to ignore because we were unable to process them and thus had to rely on simplifications. But modern information technology is enabling us now – and even more so in the future – to draw conclusions that go beyond the classic cause and effect principle. We can use IT tools to change things in mechanical engineering that have grown over decades or even centuries. Chief amongst these is the division of labor in the production process.

Data is an important element of Industry 4.0. How can it best be utilized in the future?

For me, Industry 4.0 means turning data into information, turning information into knowledge and turning knowledge into value. Speed is required. If companies say that they will generate benefits from Industry 4.0 in five years, it will be really difficult because they will have missed the boat - the topic is developing at tremendous speed.

How do companies know which data is important?

That’s an interesting question. We don’t really know the full answer yet. In Chemnitz, we are setting up a research group to look at this precise issue. We want to work with information technologists and mathematicians to look at very specific production processes and think about what data we need to get value-adding knowledge. It is very important not to start with the data like Google and Apple – but to think as a production engineer about the usability of the data from a value creation perspective.

Is it not too big an issue for SMEs?

It’s only too big an issue if no value is created at the end. Any SME will make every conceivable effort if it brings added value for their business model. This is exactly what the task involves – investigating the possibilities of Big Data in their business model. All I can do is call on companies to make use of the existing network between industry and research.

What else is needed for industry to make effective use of its data?

First of all, we should not fall into the trap of believing we already have all the data. I would advise every company to consider how it can generate more data and link it to its products. There are a number of possibilities. One of them involves the traceability of products. For example, we should mark sheet metal parts from the formation of the material through to scrapping, and then be able to use this data. We will definitely be able to solve these challenges – we don’t need another Einstein, just a bit of time and investment.

What will change the most in data handling - the recording, transfer, or evaluation?

The beginning and the end - in other words data generation and evaluation. In terms of generation, I have great hopes that we will develop new types of sensors. To take advantage of this massive potential, we need to look beyond our practical engineering view and consider the fundamental research work being done. Issues that we have not yet thought of are being addressed, for example, sensors at a microscopic level, or using the structure of materials as coding. When it comes to evaluation, the already mentioned inclusion of data value should guide our thinking. For the saying, "data is the crude oil of the future" is not without some justification.

You are skeptical about the idea of being able to produce one-off products at mass production costs - why is that?

Did I really say that? This great world of data comes up against an issue that we are not yet so aware of. In the virtual world, where we create non-material systems, we can resolve the issue of time and space. Data is just one of the issues. We have to ask ourselves how we can manage to produce individualized products under large-scale conditions. Logistics experts are already thinking about it. In the past, it was inconceivable to get things delivered within 24 hours. As production engineers, we need to look at this now.

Who will data belong to in the future?

I think there is data that is common property, and this is already a reality. For example, if we are doing a research project with the German Research Association, this is a basic requirement. But otherwise, the person who generates the data needs to ensure that they retain their ownership rights to that data. If we as production engineers provide data, this enables others to analyze that data and use it for their business model. But it remains our intellectual property. We are providing the crude oil for refinement processes, so to speak.

Are data transparency and data security not contradictory?

Firstly, we should all be aware that data has a value. Data protection is definitely important, but we should not hide behind it. At the Institute, we are thinking in very specific terms about how we can make data available. Of course, security does play a role, but our guiding principle is the concept of data as a value and making it usable as a commodity. The Fraunhofer Institute is running a major data security initiative – the Industrial Data Space. Along with industry and other interested parties, they are considering how data can be sent as a container that cannot be manipulated but provides the recipient with all the information about the data.

What are the perspectives around the world?

Throughout Europe and also in China they have their own concepts with a similar orientation to that what we call Industry 4.0 in Germany. For example, the Chinese take a much more restrictive approach to their data. On the other hand, we have information technology centers on the West coast of the USA, where they have known for a long time how to make money from data. But if we look a little closer, this question is becoming more and more superfluous as companies operate internationally anyway.

How much will the boundaries between different parts of companies become blurred?

The Smart Factory is becoming the state of the art approach. Companies are increasingly developing strategies to create a streamlined process. Division of labor is no longer the major issue, rather networking - and how it can be used to achieve greater speed and efficiency. This issue is one of the key competitive factors even though not everyone has understood this yet.

If everything is controlled by data and algorithms, what role will people play?

This is the subject of heated discussion. At Fraunhofer, we have been thinking about this since the beginning of digitalization. We developed the E3 project for sustainable production. The three “E’s” initially stood for “efficient technologies”, “emission-neutral and energy self-sufficient factories”, and “ergonomics”. The final point has since turned into “employee involvement”. Within this, we consider questions of motivation, ergonomics, and also the role of people in digitalized production. One thing is certain. We will still need human intuition in the future. Someone has to develop the appropriate business models and make decisions in a particular context. Yes, there will be professions in which this is critical. But we should not be afraid of this change, as we have the opportunity to help shape it.