It’s regarded as one of the costliest errors in aeronautic history: When ESA, the European Space Agency, deployed the first uncrewed Ariane 5 launch vehicle it exploded only a few seconds after liftoff.

The reason for the disaster was that the rocket was still internally operating with Ariane 4’s control software but the new engine was a lot more powerful than that of the previous model – so powerful that during liftoff the old software identified totally unexpected acceleration ratios. Instead of stabilizing its own flight path the automatic control unit ordered the vehicle to swerve with increasing vehemence and ultimately activated the self-destruction mechanism. Ironically, wrong data about the properly functioning engines led to the loss of the rocket.

That catastrophe served as a lesson for engineers: All the key components of a system should always be stored in the related software as a current data model. That applies not only to rocket engines because in some cases, especially small components play a major role. Rolling bearings are a case in point.

Billions of rolling bearings around the world set technology in motion in low-friction and low-wear ways. Today, no robotic arm, no wind turbine, no aircraft engine, no train, and no computer drive would move, and where there’s motion, Schaeffler is typically involved. Schaeffler, the motion technology company, is one of the world’s major rolling bearing manufacturers. Its portfolio extends from miniature bearings the size of just a few millimeters for dental drills to special-purpose designs for the mining market to high-temperature bearings for aerospace applications.

40,000 rolling bearings – 40,000 different characteristics

Schaeffler offers some 40,000 standard rolling bearing products, plus many customized specialty solutions. Even so, every rolling bearing has individual characteristics. That’s why detailed knowledge of the specifications of the rolling bearings they install is important for customers.

That’s where the Data-as-a-Service (DaaS) cloud solution comes into play. Schaeffler’s customers can obtain information about Schaeffler’s rolling bearings via a precisely defined data interface. The available information covers engineering, manufacturing, and logistics.

Engineering information is provided by Schaeffler’s engineering design departments. That information describes the bearings in terms of their mechanical properties including geometry, calculated performance data as well as details about the composition, material properties, and components of a rolling bearing. This information enables customers to simulate Schaeffler’s rolling bearings and to virtually install them in their own systems as early as in the system design stage.

“The information provided goes beyond pure CAD data and becomes particularly relevant for enhancing the efficiency of industrial gearboxes or electric motors. Here, the customer can quickly evaluate various rolling bearing configurations to cover different performance requirements such as load and rotational speed,” says Wolfgang Czarnach, Vice President, Regional Business Unit Power Transmission Industrial Division at Schaeffler Technologies.

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“Initially, customers didn’t see the massive value of data because they’re not tangible like other industrial products. Data are immensely important and one of the major raw materials of digitalization.”

To complement the design data of its bearings, Schaeffler provides measurement data from the factory floor. This service is special in that all measurement data can permanently be traced back to an individual rolling bearing. For this purpose, all bearings are marked with a so-called Data Matrix code, a two-dimensional, computer-readable code. Consequently, customers not only know the calculated performance of the individual rolling bearings in their applications but also have measurement data from the factory floor for specific types of bearings – thanks to the data interface of the Bearing Data Service – even before the product itself has arrived at the customer’s site.

Pre-sorting components before the customer has received them

By means of the measurement data rolling bearings can be systematically pre-sorted. For instance, bearings with particularly small manufacturing tolerances can be selected for machines or operating environments with particularly high loads such as those in the aerospace sector. Conversely, bearings with identical measurement values can be combined and installed in a single machine respectively. As a result, they’ll wear more evenly in subsequent operation.

Similar selection methods have existed for a long time in the semiconductor industry where light diodes, whose luminous colors always slightly vary due to their production process, are systematically sorted by their real luminous colors during a process called binning.

The source of the third component of the data that Schaeffler supplies is logistics. Here, customers learn where the rolling bearings they’ve ordered are currently located, for instance in preparation for shipping or already enroute to the customer. A connection of the warehouse products packaged on a loading aid with the pallet itself is available as well. That provides customers with complete end-to-end tracking of all the components of their subsequent products and enables faster response to fluctuating demand.

Digital twins in computers simulate real-world assemblies

By means of these three information streams from engineering design, the factory floor, and logistics via Data-as-a-Service Schaeffler’s customers can even create digital twins of their products. The machines to be built are fully stored as data models in the customers’ own systems.

This information is subsequently available also for maintenance jobs. For instance, when a rolling bearing is exchanged, its exact manufacturing data and the tolerances it had at that time can be retraced and matched. In some cases, like reconditioning axle bearings for rail applications, Schaeffler itself uses its historic data of rolling bearings. In that case, the specific bearing is identified by means of the Data Matrix code and the digital history of the bearing supplemented with information from the reconditioning job. Among other things, it includes job order data from the reconditioning process as well as information pertaining to the rolling bearing itself. In that way, a rolling bearing and its digital history can be identified and supplemented over and over for years. That means the information is always up to date and can be made available to the customer as an additional service.

Patrick Kalisch, Head of Bearing – Product Data, Configurators & Standards, explains what that means for Schaeffler’s customers: “With our digital solutions in the Data-as-a-Service environment such as Bearing Data Service we make a direct integration of machine-readable rolling bearing product data possible for our customers. As a result, our customers can automate their business processes and reduce manual work.”

The first customers, including major original equipment manufacturers from the industrial gearbox and electric motor production sectors, have already ordered the still young Data-as-a-Service product, and rolling bearings from Schaeffler along with the corresponding data. That’s how transparent data and high-grade rolling bearings jointly ensure that machines run longer and downtimes are shorter.

Data-as-a-Service: added value due to data linking

Schaeffler’s data service for customers of rolling bearings shows that information is one of the most important resources for Industry 4.0. Originally, DaaS was developed strictly as a data management strategy for secure data storage in the cloud and retrieval as needed. However, since then it has become obvious that DaaS offers significantly more potential.The major cloud service providers have long responded to this trend as well. Companies like Amazon and Google offer DaaS cloud storage solutions to businesses and are recording rapidly growing demand.

Schaeffler has responded to that trend and the demands from the markets as well and uses a performance cloud infrastructure for merging and editing data. Customers can retrieve the information via an interface and integrate it directly into their systems and processes.

Whether geographic information, weather data, or stock market reports – more and more specialized services providers offer their information via DaaS. Customers access such data via the internet and program their own data interfaces for that purpose to feed the information directly into their systems.

The data streams obtained as DaaS become even more valuable by interlinking. An automaker or freight hauler, for instance, can retrieve diagnostic and motion data of vehicles in real time and interlink them with a data stream for current weather conditions. By means of DaaS they can access huge data packets that break down the temperatures and weather conditions for practically any place on Earth.

As a result, the user obtains fine-grained information about how its vehicles perform in what kind of weather and under what ambient conditions there’s an increase in breakdowns or accidents, for example.

Lifetime diary for machines

What works for automobiles works equally well for ships, aircraft, or construction machines: By means of DaaS, data linking creates a lifetime diary for machines that even years later provides conclusions about when and under what working and environmental conditions the technology was used. In that case, for instance, an insurance company can grant discounts if the technology was employed only under specific, pre-defined operating parameters.

Big-Data-as-a-Service (BDaaS)

A big advantage of DaaS is the fact that even huge data volumes can be stored and retrieved in next to no time. That, in turn, makes DaaS attractive also for big-data applications. In that case, mammoth amounts of data such as diagnostic data of industrial systems are collected. It’s not uncommon for several gigabytes of sensor data to be generated per machine per day. These data packets are subsequently examined by means of relevant algorithms and artificial intelligence.

Schaeffler performs such big-data analyses too. Now, the conditions of thousands of machines and industrial systems are transmitted for processing into the Schaeffler cloud via an operations center. Specialty software identifies even the minutest irregularities in the mammoth data volumes and derives recommended actions from them. Consequently, DaaS helps optimize maintenance intervals and reduce machine downtimes.

DaaS doesn’t reinvent technology but makes its utilization smarter, reduces downtimes, and provides customers with greater transparency about the assemblies they employ: from the smallest rolling bearing to the airliner engine that weighs several tons. With the right data provided by DaaS the technology becomes more efficient, reliable, and durable.