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Active Monitoring of PROFINET Networks and Its Potential

At the start of this project, it was necessary to simplify the monitoring and maintenance of PROFINET POF fibre optic cables in the welding shop. Today, we monitor the quality of approximately 140,000 metres of fibre optic cable and about 15,000 PROFINET stations, through a single user-friendly system. By implementing our own software tools and ThingWorx visualisations, we were able to produce a solution which, apart from showing the quality of signal in individual PROFINET POF cables, provides information about PROFINET stations, their firmware versions, data flows, corrupted packets, current topology and more. In addition, the solution allows for the monitoring of FESTO CPX valve terminal diagnostic events. To deliver the full potential of our solution, we continue to think of additional functionalities.

  • Above all, our solution enabled quick localisation of a damaged POF cable and its prompt repair.


Condition Monitoring of the Biggest Press Lines in Czechia

The aim of this project was to develop a brand-new condition monitoring system for monitoring ŠKODA's Schuler PXL press lines and thus help its maintenance department monitor key press line devices and values. Currently, the FIOT condition monitoring system monitors two PXL press lines and compressed air parameters and consumption, electric power consumption, the flow rates and temperatures of cooling water, the temperatures of the main motors, pressing force values, vacuum, PROFINET networks and more. The system, which is based on OPC communications and the ThingWorx IoT platform, can easily be extended to include mobile phone visualisations, an alert subsystem, augmented reality and links to relevant documentation. Simply put, capabilities that can enhance the user experience.

  • And the benefits? Both PXL lines are continuously monitored by the FIOT. It helps ŠKODA's maintenance monitor the biggest and most modern press lines in Europe, on-site as well as remotely.


Replacing Manual Data Collection with Wireless Technology

Třinecké železárny (Třinec Ironworks) needed to optimise and automate regular temperature measurement in many places on the shop floor. In the end, the customer and we agreed to deploy Monnit wireless sensors, which use a frequency of 868 MHz.

The sensors were connected to an IoT gateway. This gateway enables the customer to transmit data to the KEPServerEX platform. KEPServerEX then stores the data to a database, allowing for data visualisation. Using this architecture, we can easily extend the system to include further measurement sites. In addition, the system is able to store and process also historical data.

  • Thanks to the time saved by having switched from manual to automated temperature measurement, Třinecké železárny expects to achieve a return on its investment within 18 months.


Wireless Monitoring of 24 V Supply Voltage Quality

In ŠKODA AUTO a.s. Mladá Boleslav, we deployed a solution for wireless monitoring of 24 V quality in control cabinets. For this project, our company developed its own system for continuous monitoring of supply voltage, called the FIOT Sensor. The FIOT Sensor measures voltage in individual wires. At set intervals, it takes the maximum, minimum and mean voltage values and wirelessly transmits them to an IoT gateway, using a frequency of 868 MHz. The data is then sent to the ThingWorx platform for processing and visualisation.

  • Already during the trial run, users were provided with information that enabled them to plan measures for improving 24 V supply voltage quality. Many shop floor sites have benefitted from the solution, as it has helped identify the causes of downtime. Finally, the system allows for temperature monitoring in control cabinets.


Active and Passive Monitoring of the PROFINET Network

When developing this project for one of ŠKODA AUTO’s assembly lines, we faced a considerable challenge in that we had been asked to provide a solution for continuous active and passive PROFINET network monitoring. Specifically, it involved monitoring stations on the PROFINET network by regular scanning, as well as providing maintenance with real-time alerts and information about PROFINET station failures. To develop this solution, we used our own software tools. Visualisation and business logic were created in the ThingWorx platform.

  • Even the slightest improvement in maintenance response time is clearly beneficial. In the assembly process, virtually every minute counts – every single minute means a new vehicle.


Wireless Data Collection as the First Step towards Condition Monitoring

Having identified the need for condition monitoring, the management of Česká zbrojovka (Czech Arms Factory) asked us to deliver a pilot project. The aim of this project was to assess the applicability of pilot project data and to set priorities for a comprehensive solution. With this aim in view, the customer and we agreed to use Monnit wireless sensors, an IoT gateway and standard visualisation of real-time and historical data. The result met the client's expectations – the optimum selection and installation of sensors, including further project stages planned. Most importantly, our solution enabled the customer to achieve cost savings by monitoring compressed air quality.

Building on the success of the pilot, we developed a robust FIOT solution, using OPC communications and the ThingWorx platform. Today, we monitor the operation of 4 compressor rooms. In addition, the customer is assessing the potential benefits of a CNC machine condition monitoring pilot. The pilot focuses on collecting data from CNC machines with the FANUC control system. Nevertheless, thanks to our own OPC servers we can also collect data from Heidenhain, Fidia and Sinumerik control systems.

  • We recommend a similar approach to other companies. Its main advantages include modularity, which enables you to modify, extend and move the solution, as well as self-sufficiency during the installation of components. Finally, this approach offers maintenance staff the opportunity to gradually learn how to leverage technological data.


Frequency Inverter Data as Drive Condition Indicator

A very important and common component in the ŠKODA AUTO welding shop is the SEW frequency inverter. The idea behind this project was the premise that the worsening condition of the mechanical parts of the technology, which were driven by the SEW drive, would result in an increase in the frequency inverter's output current. We, therefore, decided to continuously monitor the inverter's output current values and their development (e.g. gradual increases and sudden changes). This enabled us to infer unwelcome changes to the condition of the technology's mechanical components. To collect the necessary data, we developed our own OPC server for SEW frequency inverters. For data processing and visualisation, we used the ThingWorx platform.

  • Soon after deployment, this continuous drive load monitoring allowed the customer to predict an imminent mechanical fault in the technology behind the drive.


Continuous PROFIBUS DP Network Diagnostics

For the ŠKODA AUTO Kvasiny paint shop, we have developed a solution for continuous monitoring of PROFIBUS DP network quality. To collect data about PROFIBUS stations and telegrams, we use ComBricks hardware modules from PROCENTEC. In addition, using the ThingWorx platform, we have developed a visualisation that displays available and lost stations, repeated, corrupted and diagnostic messages, as well as information from the event log about communication issues.

  • The deployed ComBricks solution is a modular system that can be modified, extended and moved at any time during its lifetime, which means there is great potential to be realized in the future.


Implementation of Innovative Data Visualisation in Maintenance

Bosch is a company which is very active in implementing Industry 4.0 principles. This enabled Bosch employees to closely cooperate with our specialists and develop a brand-new hands-on solution. How does it work? You have a tablet or a mobile phone. It displays a real object or a 3D model with controls (icons) that provide a whole range of information about the object (almost 250 measured values). All this information is available in one system, there is no need to leave the site. In addition, the object can be manipulated. You can also inspect it, without using sophisticated equipment or spending hours disassembling it. Apart from the monitoring of technological data, you are provided with the monitoring of thresholds, batch visualisation and access to relevant documentation.

  • The biggest success in the project was positive feedback of first potential users on the solution and their ideas for using it in everyday maintenance. We believe that this next stage will come soon.


Monitoring Electric Power Consumption and Quality

The idea for this project came from ŠKODA's green factory scheme and its need for greater cost-efficiency. The aim of the project was to create a system that would allow for the measurement, visualisation and comparison of electric power consumption values for given time periods in specific parts of the technology (machines, centres and departments). During the first implementation stage, we installed almost 100 three-phase network analysers in 3 switch rooms. Data from the analysers (electric power consumption and electricity network quality – current, voltage, input, power factor and harmonic voltage distortion) is transferred to the KEPServerEX platform via the Modbus protocol and then communicated to the unified FIOT smart maintenance platform.

  • We delivered a user-friendly solution for the monitoring of electric power consumption in specific shop floor areas for given time periods. In addition, by reviewing the history of collected data, the staff can better predict future consumption and optimise production.


Online System for Managing Scheduled Maintenance

Although we strive to work with hard data as much as possible, what adds real value to it and what our customers benefit from immensely is soft data. That is why ŠKODA AUTO asked us to extend its existing press line condition monitoring system by developing a subsystem for managing and monitoring scheduled maintenance of the press lines. What it effectively meant was the combination of prevention and prediction.

The key functionality of this subsystem is the ability to notify the user of the upcoming scheduled press line maintenance. The notification is determined either by a pre-defined value of the variable that is being monitored (e.g. the number of lifts) or by the time that has elapsed since the last maintenance check. In addition, the user is provided with information about maintenance task history, can set email alerts and more.

  • The subsystem was enthusiastically embraced by ŠKODA AUTO employees and is now being utilised to the full. Its key functionality greatly removes potential for human error and reduces the risk of unplanned downtime. Furthermore, it allows maintenance staff to optimise maintenance by informing them about upcoming scheduled maintenance tasks.


Real-Time OEE Monitoring

What we are seeing more and more is requests for interfacing maintenance and production data. As part of our Engine Block CNC Machining Condition Monitoring project, we developed an OEE monitoring system, with the aim of collecting and analysing data from the Sinumerik 840D (e.g. production and non-production times, as well as the number of parts produced) and obtaining information about the machine's operation. The system enables the user to gain insight into the operation and performance of the production line. In addition, it includes visualisation of the production line's power consumption, breakdown history and variable fluctuations. To collect data from the Sinumerik 840D, FOXON developed its own OPC DA server – the FOXON OPC DA Server for Sinumerik 840D.

  • The system does not only provide detailed information for the production and maintenance personnel. The visualisation that the system offers has informed decisions at the managerial level, leading to power and compressed air savings.


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