Metrology and Quality Assurance in Industry 4.0

Overview

Industry 4.0 and the Industrial Internet of Things (IIoT) are two terms that tend to appear together when the topic turns to the future of manufacturing. This is because the two concepts are closely linked: the increased interconnectivity that comes with the IIoT is a key component of the smart factories of Industry 4.0.

As a result, advancements in IIoT technology are rapidly making Industry 4.0 a reality, and the ensuing paradigm shift will have a profound impact on every aspect of the manufacturing sector, from machine tools to metrology.

Gisela Lanza has a unique perspective on the IIoT, Industry 4.0 and the new role of metrology for quality assurance they engender. For four years, she worked simultaneously as the first incumbent of the shared professorship of Global Production Engineering and Quality at the Karlsruhe Institute of Technology (KIT), and at Daimler AG in strategic planning.

Lanza shared her insights with journalist Nikolaus Fecht in a recent interview.

How is Industry 4.0 influencing quality assurance and metrology?

Thanks to the increasingly important influence of sensor technology, we will definitely be able to collect much more measured data, and thus improve our detection of causal connections. I would even venture the hypothesis that in the future we will be recording 100 percent of all important measured values. 100 percent testing means that quality data (i.e., all critical parameters) will no longer be acquired by random sampling, but rather through 100 percent coverage. This signifies a radical change in quality control, because now we can get much closer to the tolerance limits.

 

What will the quality control of the future look like, in your opinion?

I’m predicting intelligent, adaptive quality control strategies.

One example here might be a revival of pairing strategies, which production people often hate because of the complicated mathematical approach and the logistical outlay involved. Here, components with different quality features are used in pairs, to jointly provide the functions of an assembly with very high tolerance requirements. Pairing strategies are an obvious option if not every component produced is able to meet the specified tolerances.

One example here is the injectors used in engines, which have to work with an operating pressure that may reach 3,000 bar in the future. Rigorous deployment of inline metrology will enable even more intelligent, component-specific pairings to be used in conjunction with dynamic modification of production parameters, which will open up many new options.

 

So will data be increasingly acquired inside the production line?

Yes. There’s an ongoing trend toward more inline metrology, or even toward process-integrated measuring instruments, permitting minimized control loops.

Measurements are no longer taken in a separate measuring room, but directly in the production process. This is increasing the demand for metrology applied in a modularised mode in plants and production lines, while standard measuring instruments are becoming less sought after.

Metrology is turning into a project business, in which the customized application is the crucial competitive factor.

 

On the subject of sensor integration: Can a machine tool be converted into a measuring machine?

This goal has been around for some time, and it continues to be a very exciting task. But there are still numerous challenges involved, such as high costs and interference factors from the production process such as temperature or dirt.

What’s more, typical metal-cutting parts often require a very high degree of measuring accuracy. Users also want an independent metrological framework, which ideally enables measurements to be taken in parallel to machining – this is known as concurrent measurement. Measuring with the machine tool, however, is already standard procedure for high-precision products. One example here is the production of diesel injectors at Bosch.

 

When a machine tool is able to acquire more data with the aid of sensor technology, what does that mean for signal processing in regard to real-time capability?

In terms of technology, individual sensors are being replaced by distributed sensor networks, because a networked infrastructure is an essential precondition for using the potentials of inline measurements with maximised efficiency. Users want intelligent, interlinked evaluation of the data concerned. Experts on this topic speak of a fusion of data from several different sensors, which leads to a combined metrological result. In order to explain the complex causal connections of a process, data mining algorithms such as neural networks are well suited. So the main consideration is that the meaningful data correlations need to be filtered out.

 

What role will quality data generated in the factory of tomorrow play? Can the big data thus created be meaningfully managed and mastered?

At present that’s still not easy to assess. The basic precondition here is a harmonized software architecture. Once this has been established as a base, with harmonized data structures and interfaces, I’m expecting it to be design-enhanced by a gradual increase in complexity – from data acquisition all the way through to adaptive, self-learning control loops.

 

Can the shop floor (the machine tool industry), networking (the web) and hardware and software (metrology) all be fruitfully reconciled?

Because the classical automation pyramid, from the process itself all the way up to the corporate level, is disappearing, cross-level information interchange is essential. In this context, the Manufacturing Execution System (MES) operating close to the process is gaining steadily in perceived importance.

Unfortunately, it would appear impossible in the next few years to directly utilize and evaluate the data from sensors without an MES. What’s more, we need harmonized interface standards like OPC/UA, a standard that is currently gaining wide acceptance for automation technology.

 

But the alleged necessity for real-time control now appears to be hampering progress. Does everything really have to be run in real-time?

No, that would just mean there are three non-conforming parts until I’m once again manufacturing specification-compliant parts.

 

Can you cite an example of best practice?

I see the Bosch Group as a leading key user, embracing full-coverage, harmonized use of its own MES and IoT software, which it also sells as a key vendor, so as to link up process, measured and order data.

 

You’re also familiar with global production strategies. Where are there international differences in terms of quality assurance?

In what are called the “emerging markets,” meaning the present-day low-cost nations, testing is still often being performed in the traditional manner at the end of the process chain. But the sheer speed of change here is breath-taking. In China, particularly, there is enormous receptiveness for Industry 4.0. The predominant attitude there is, if I’m investing, then I’m going to spend my money on the very latest technology.

 

Speaking of China; as the Director of the Global Advanced Manufacturing Institute (GAMI) in Suzhou, you’ve also had a good look at the quality assurance operations there. What differentiates the strategies of the Chinese production facilities from those of Europe’s industrial sector?

In Europe, the dominant category is the older brownfield plants, which equip their existing lines with sensor technology. In China, there’s a major trend towards new greenfield plants, which fit their new lines with large amounts of imminent sensor technology.

In China, I’m observing a readiness to make very substantial investments in Industry 4.0. They are spending a whole lot of money on hardware – often in conjunction with automation. However, I see this as problematic, because Industry 4.0 and the requisite system competence are not things you can buy. After all, what use is even the best of measuring machines if I don’t understand the system involved?

It’s auspicious for China, however, that the significantly younger workforce there is much more receptive to IT applications. But often, there’s still a lack of basic comprehension of how control loops actually work.

 

In the autumn of 2017, the EMO will be held in Hanover. What role does this event play for you and your staff?

As a specialist in production technology, I would be going to the EMO 2017 anyway. But because metrology is increasingly being integrated into the processes and machines involved, and production technology is merging with metrology, it is becoming progressively more relevant for metrologists as such.

In this context, by the way, I was also gratified to note the “Quality Area” at the METAV 2016. This is the right approach, true to the motto of “Get out of the test room and into the production line.”

 

For more information on EMO Hannover 2017, click here.

You can find the full article on ENGINEERING.com here

 

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  • AUTHOR
  • Author Ian Wright
    Author Title Accelerating the Adoption of Industrial Internet of Things.
    Guide Type Technology
    Date 02/07/2017
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