From Big Data to Smart Data

From Big Data to Smart Data

From Big Data to Smart Data

From Big Data to Smart Data

From Big Data to Smart Data

From Big Data to Smart Data

Predictive maintenance allows for scheduling maintenance work in due time before drive failures occur. This means higher system availability, reduced costs and prolonged service life of drives.

Predictive maintenance usually uses data from external sensors such as light barriers, temperature sensors, oil sensors or vibration sensors. However, predictive maintenance is also possible using virtual sensors. With intelligent mathematical algorithms including product data and many years of engineering expertise, the integrated PLC evaluates operating data available in the frequency inverter such as motor current consumption and actuation frequency and thus allows for conclusions on the condition of the geared motor and the driven application.

Trends towards condition degradation (e.g. due to wear) or even acute faults (e.g. failure of a motor fan) can be detected quickly and the user can take appropriate countermeasures immediately. This also allows for an assessment of the degree of use of the gear oil and the predicted date for the oil change. When it comes to large industrial gear units, vibration sensors in particular provide advantages. For all bearings which are installed in industrial gear units detailed manufacturer databases exist which provide the characteristic vibration frequencies of the components as well as product-specific parameters. The individual frequencies can therefore be clearly identified and attributed to particular components.

Data analysis instead of just data reading

Each conveyor belt drive within an intralogistic system is subject to different loads depending on its task (different loads, inclines, curves, transfer stations, continuous operation, interval operation etc.). In a learning phase during which it is essential to include the customer's application expertise, the electrical data is determined on the new conveyor system – in unloaded and loaded state –, and defined as reference values. If these values are then exceeded within a defined time frame in real operation, algorithms detect that something has changed in the mechanical system.

This can be caused by increased friction, wear, an already damaged bearing or gear unit, or a trapped foreign body (packaging material, adhesive tape). In addition, threshold values can be defined, the exceeding of which signals increasing wear. If the mathematical parameters of the system are known and have been converted into validated intelligent algorithms for data evaluation, predictive maintenance for the drive technology becomes possible even without any real sensor being present.

Smart data with intelligent algorithms

As a system supplier, Nord Drivesystems delivers drive systems in the right size and precisely matched to the customer's application. Condition monitoring for predictive maintenance based on intelligent algorithms and software in an IIoT environment (Industrial Internet of Things) creates added value for the customer: The networked drive units can be operated with all common bus systems, collect their condition data within the inverter’s own PLC and transmit it together with data of connected sensors and actuators to an edge device. There, data of all subsystems is managed as well as processed and evaluated using intelligent Nord software.

It is then available as pre-selected and edited smart data for further use, which can take place locally, within a customer cloud, the Nord cloud or at a third-party provider. Following the path via the edge device, data processing, management and control will be significantly more efficient while data traffic and mains load are reduced. Furthermore, drive data is disconnected from the central control system. This increases data security for the operator. Only relevant data is transmitted, for example, if values have changed or threshold and alarm values have been exceeded. Due to local conversion of the data flood into smart data within the edge device, the system is intelligent, enclosed and secure. System, data and expertise are protected against manipulation and unauthorised external access.

IIoT applications in pilot projects

The requirements on a predictive maintenance concept are as individual as the customer applications. Therefore, there are no predictive maintenance solutions off the rack. Each project is customised and implemented in a way that meets the customer’s infrastructure and processes. Currently, Nord Drivesystems is implementing IIoT concepts for this area with large-scale customers on a global level.

In a baggage handling system, Nord drives are monitored via data processing and saving using a PC as edge device, as well as via local data visualisation on a touch monitor and via signal tower. No cloud solution was selected here, following the customer's request. Pre-processing of data and threshold monitoring is carried out via a software inside the frequency inverter’s PLC. The data is transmitted via Ethernet using the UDP protocol with an update interval of approx. 0.2 seconds. For vibration monitoring of the application, hardware sensors are also read in and processed.

Safe connection via edge device

Another customer is running a large intralogistics installation with NORD drives, whose IIoT system is modelled on Nord's own application test area. Ten drive parameters are read via UDP, pre-processed inside the inverter and then – like in the first example – processed and saved via edge device. At the same time, an LTE transmission into the customer cloud takes place. The customer visualises them from there. Oil aging of each single drive is monitored via virtual sensors in order to determine the optimum oil change time. The internet connection has been equipped with a special security concept.

In another project featuring Nord drives, data is collected locally and transmitted to a cloud with an update interval of approx. two seconds via LTE router. Data is then visualised in the web browser.

Virtuality heading towards reality

All in all, the use of the Industrial Internet of Things is still in its infancy. Future developments will tend towards a digital twin of entire systems, allowing for virtual commissioning and the possibility to simulate drive dimensioning and demand-oriented operation in advance. This way, costs for commissioning and operation will be reduced. Nord Drivesystems is looking forward to pursuing this path together with its customers and is noticing the significantly growing interest in pilot systems for customised IIoT solutions in drive technology and intralogistics. Depending on industry and expertise focus, companies need specific professional support. The application experts from the company are ready as partners.


"In the future, encoders will offer secondary functions and collect data. With value-added functions, customers will save themselves expensive additional sensor technology."

Lothar and Gebhard Kübler, Kübler Group