The use of digital technologies, big data, and machine learning in industrial companies is a relatively simple and well-established process that is based on well-known algorithms. However, to make it truly effective, we must change our approach to handling data, which, in turn, will eventually lead to a major shift in culture.
There is no need to yet again emphasize that digitalization is an all-important megatrend, one that is absolutely impossible to ignore. Regardless of a company’s area of expertise, it can find its place in the market, and maintain it in the future, only if the company knows how to implement and use state-of-the-art digital technologies and solutions in the most successful and efficient way.
We are already seeing the second wave of implementation of products and solutions obtained at the junction between engineering, manufacturing, and digital technologies, which creates value for the product. Air transportation and aircraft construction are the industries that are at the frontier of these changes. I feel really proud that Russian airlines are among the world leaders in the field of digital technologies and digital solutions. Thus, everyone is familiar with the success of the national air carrier, Aeroflot, as a service company. At the same time, almost no one knows that it is one of the few airlines in the world whose onboard internet store sales are its second-largest revenue item after ticket sales. In reality, Aeroflot is a world leader in the introduction of digital technologies, not only in passenger services but also in aircraft fleet servicing. And the record figures the company demonstrates in the operation of Western aircraft are directly linked with the introduction of digital technologies in all aspects of its life.
For some time now, it has been impossible even to imagine the effective production of aircraft without digital technologies. When Boeing began to develop the B-777 model in the late 1990s, we were the first to make a completely digital airplane. We abandoned drawing boards, we did not have a full-scale layout, and everything was done with the help of computers. That’s when we understood that engineers and programmers are merging into a new profession.
In the same way, in the last five years, the company’s engineers, programmers, and big data analysts joined forces to become people who create new aircraft. Today, Boeing has fully embraced the new technology called data engineering. Virtually 30–40% of our engineering decisions are now made on the basis of artificial intelligence. All of this significantly speeds up the design time and reduces the need to have a large number of engineering personnel.
In aircraft production, digital technologies have led to a real revolution. Production of titanium parts at the Russian Boeing plant in the Urals serve as a great example. Robotic complexes have been installed here, and they process the elements that make up the Boeing Dreamliner’s wing structure in parallel on the five spindles of six-axis machines. The main chassis beams are manufactured in a similar way. These are very large, complex, and extremely expensive parts. The cost of a defect or an error in their manufacture is incredibly high.
In the last two years, desperate to simulate the production of these elements using physical models, we began to use big data. For this purpose, all the information relating to the manufacturing of parts was put into computers, including data on all cutting modes, production time, and even the age and sex of the operators servicing these systems at the plant. Nobody knows why, but in the end, we were given recommendations on altering the manufacturing process. By following them, we managed to significantly decrease the percentage of faulty parts. In other words, the use of a new technology – big data analysis – let us get answers to the questions that we could not have modeled earlier.
A similar effect from the use of big data can be obtained in other areas that are not directly related to product manufacturing. Thus, we began to use big data and other digital technologies to manage Boeing personnel in Russia and in the United States. This has also yielded notable results. Boeing’s largest engineering center outside the US is located in Moscow, employing 1,500 people. Now, we are inputting about half a million data entries per year that are related to the quality of the projects we implement there. And these are separate from the entries that have to do with the personnel. The comparison and analysis of the data accumulated in such a way has made it possible for us to obtain incredibly interesting recommendations. Using them, we have dramatically improved the quality of decisions in HR management – in personnel training and team formation. And this, among other things, helped us to reduce staff turnover and increase the involvement index.
It goes without saying that it is now impossible even to imagine both air traffic control processes and aircraft operation processes without digital technologies. Today, it is a $1 trillion-per-year market that is growing as the global fleet of aircraft grows. In the next 20 years, world aviation will need about 42,000 civilian aircraft – this is the only sector of the world economy that has a guaranteed, stable demand. Every year, it grows by seven percent. However, in Russia, this is happening three times faster – here, it grows by 22% every year. According to Boeing, in this huge business – which, in its own way, is also a factory (specifically, an air transportation factory) – digital technologies will save at least 10% of direct operating costs. This is a huge resource badly needed by mankind. We all need it. Passengers need it.
As we see, collecting and analyzing big data sets gives companies significant advantages. Unfortunately, in most cases, this potential is not fully used. According to last year’s survey by McKinsey, businesses today use only about one percent of the information they collect. In other words, industrial companies have already learned how to collect data, but they don’t really know how to use it in the most efficient way.
However, it is only a matter of time until the effective use of big data becomes the norm and a new standard of business. History knows such examples. When ‘lean manufacturing’ technology was invented in Japan, there were, at first, a lot of skeptics around it. Now, it is taken for granted that no industrial company can do without this technology.
We are going to see something very similar with big data. Today, we are at a turning point. The corporate sector is already actively involved in these issues. At Boeing, we train tens of thousands of employees to apply new digital technologies, much in the same way that we very recently taught them the basics of lean manufacturing.
We are going to see their mass application in the very near future. The main thing is that people understand that the information they have access to is real gold. They need it themselves because it allows them, firstly, to make decisions faster and, secondly, to reduce the risk of a wrong decision. Therefore, it is necessary to train people to collect and store information – but not just any information; they need to learn how to single out relevant information. And most importantly, it is necessary to teach specialists to be responsible for analyzing this information.
In fact, big data and machine learning are very simple processes that involve the use of well-known and not very new algorithms. They have become fully operational only recently, because computer resources have become incredibly powerful, very light (thanks to cloud computing), and very cheap. However, we still do not have a culture of storing big data and the understanding that it is people who save this information that need to act as ‘final’ experts – to help these fairly simple and well-known algorithms. Also, a small group of mathematicians and programmers should be given recommendations on the improvement of technological processes.
All of this is a cultural issue. It seems to me that our industry as a whole lags behind in understanding this.
The digital revolution can help solve another important, though perhaps not so obvious, problem: increasing the responsibility of people. It is vital not only for their work efficiency but also for their security, including cyberthreat security. This is a very hot topic in the context of the digital revolution. Statistics show that the overwhelming majority of incidents in this area are due to the notorious human factor – the careless behavior of certain people. And this is yet another cultural issue. For example, in Japan, there exists this culture of discipline, while in Russia, we unfortunately sometimes lack this culture.
How can digital technologies dramatically change this state of affairs? Here is just one example: Last year, Boeing announced the launch of a full-service aviation training and research campus in Russia’s Skolkovo Innovation Center. Here, there are four flight simulators to train pilots. Right next to it, we installed a big data hub. Now, all information related to the process of pilot training will be recorded in the electronic passport of each pilot – from the moment of admission and throughout their entire professional career. When all information related to a pilot’s training or behavior in critical situations is always stored and can be objectively analyzed, if necessary – by his or her employer, for example – it turns out that mere fact leads to an increase in the pilot’s responsibility. And the contribution to safety issues of responsible behavior – from operators, pilots, and people in charge of the largest robotic complexes – is much larger in terms of scale. And that is exactly what can be done and is done by digital economy. It has already arrived.
The article is based on Sergey Kravchenko’s speech at the INNOPROM-2017 industrial trade fair in Ekaterinburg.
