Maximum Grid Security for Offshore Wind Power
GE Vernova Relies on the iba System in Sofia Project
Learn more
Condition Assessment Using Meaningful Characteristic Values
Vibration Monitoring Made Easy
Reducing Complexity by Calculating KPIs From Vibration and Machine Data in ibaPDA Using ibaInSpectra
A customer from the aviation industry operates a friction welding machine for the production of engine parts.
The high and long-term availability of the machine is very important here. However, the previous vibration analysis system was outdated and the associated support contract with an external service provider had expired. This meant that the monitoring and diagnosis of the machine could no longer be guaranteed.
To ensure continued vibration monitoring of the machine at this point and to provide more transparency internally, the company finally decided to replace the old system. In addition to wear monitoring based on vibration data, more attention was also to be paid to the current operating status of the machine, without changing the existing measuring points. Another important requirement for the customer was that the system should provide easily interpretable data, prepare it for comparison and ultimately store it for long-term trends.
In the search for a suitable solution, the company finally opted for the iba system, which, in addition to its technical performance, scored points above all for its flexibility, openness and comprehensive data analysis capability: In the iba system, both control and vibration sensor data can be recorded synchronously and calculated into meaningful characteristic values (for example, the effective value of the vibration velocity or the crest factor). This allows different machine states, such as the warm-up run or welding processes with different flywheel masses, to be monitored easily and separately – even without in-depth knowledge of condition monitoring.
As a result, the work of the customer’s personnel is made easier and the reaction speed and diagnostic capability are increased in the event of a fault. In addition, the installation of the iba system has enabled numerous new requirements to be covered.
With ibaInSpectra, we can convert complicated signals into simple indicators and thus provide the customer with meaningful data on the machine condition.
Eugen Graz
Application & Consulting Engineer, iba AG
The Technology
Eight vibration sensors detect the vibrations along the rotary welding machine and log them in ibaPDA. In addition, the relevant process data of the machine is captured in ibaPDA, time-synchronized directly from the S7 PLC. The defined characteristic values are then calculated in ibaInSpectra and assigned to the respective operating status. These can be used to perform initial checks of the machine’s condition, such as comparing the vibration velocities with the corresponding alarm and warning values.
For trend analysis, a dashboard was also created for the plant operator, which filters and visualizes the data based on the respective operating setting. All recorded raw vibration data, KPIs and machine process data are automatically exported to the customer’s own database with iba data processing, using ibaDatCoordinator and ibaAnalyzer, and stored there for the long term. This enables trending over longer periods of time as well as subsequent detailed analysis on a raw data basis via drill-down, as this is particularly relevant for experts in the event of deviations or errors.
During the course of the project, iba provided support with system design, setting up and configuring the iba system, defining and calculating the necessary KPIs and creating an ibaAnalyzer profile for in-depth offline analyses.
Test the iba System Now!
Download the demo of ibaPDA and ibaAnalyzer and start optimizing your processes today. Try it free of charge for 30 days!
Request a ibaPDA-Demo LicenseUsed Functions
The following functions of the iba system are used in this success story.
- Process Connectivity
- Acquire & Store
- Analyze
- Share
Explore More Success Stories
Read more inspiring success stories of our satisfied customers.
From Scrap Basket to Heat Analysis
How Badische Stahlwerke Uses the iba System to Bring Transparency to Scrap Charging
Learn more
Badische StahlwerkeDigital Process Monitoring in Batch Annealing
From Paper Chart Recorders to Modern Data Acquisition: To ensure reliable analysis and visualization of furnace data, Aluminium Norf relies on the iba…
Learn more
Transparent Power Plant Monitoring with the iba System at FPCL
After the nationwide blackout in Pakistan on January 9, 2023, energy producers came under increasing pressure to enhance plant monitoring and to…
Learn more
Digital Process Optimization at thyssenkrupp Electrical Steel
At the cold rolling mill of thyssenkrupp Electrical Steel (tkES) in Gelsenkirchen, the team faced a familiar yet complex challenge.
Learn more
Large-Scale Small-Signal Excitation – Measured by iba
The energy transition is fundamentally reshaping power grids: decentralized generation, volatile energy sources, and increasingly dynamic grid…
Learn more
AI-Powered Coil Strap Detection with ibaVision
In the production of aluminum coils, proper strapping is essential to ensure safe handling and transport.
Learn more
Locating High-Speed Faults with iba
A mining company uses the iba system to maximize the availability of electric rope shovels.
Learn more
AI-generated ImageDigital Process Optimization in Steel Refining at LSV
The heat and surface treatment of steel is a complex and sensitive technical process. With the iba system, LSV implemented a comprehensive solution…
Learn more
A Quick Look at Historical Data
In order to analyze processes efficiently, Neuman Aluminium introduced the iba system in production in 2014. Due to its success, it was rolled out to…
Learn more
With a Unified View of All Process Data: Novelis Relies on the iba System
The commissioning of a new pusher type furnace at their Swiss location prompted Novelis to standardize the acquisition and analysis of process data.…
Learn more
Finding a Needle in a Haystack in Seconds: BILSTEIN Monitors Coils With ibaDatawyzer-ICC
Over 1,600 tons of metal, rolled into coils, pass through the BILSTEIN Group’s production facilities every day. To eliminate the risk of mix-ups, the…
Learn more
“With ibaHD-Server, we have direct access to seven years of historical data”
What began seven years ago with the replacement of paper chart recorders in a pusher-type furnace has evolved into a key pillar of quality assurance…
Learn more
Vibration Monitoring Made Easy: Condition Assessment Using Meaningful Characteristic Values
Reducing complexity by calculating KPIs from vibration and machine data in ibaPDA using ibaInSpectra.
Learn more
“ibaDaVIS gives all users easy access to the data and helps us resolve emerging issues more quickly.”
As the legacy system no longer met operational demands, the BILSTEIN GROUP had to seek out a new solution for process data visualization. Their…
Learn more
Frequently Asked Questions (FAQ)Raw vibration data can be converted into interpretable condition indicators by calculating standardized KPIs such as RMS (root mean square) or crest factor. With ibaInSpectra, this transformation is performed directly based on time-synchronously acquired data from sensors and control systems. The calculations are carried out contextually depending on the machine’s operating state. This reduces complexity and enables rapid assessment of machine condition.
A practical approach is to abstract complex signal patterns into easily understandable key metrics. ibaPDA acquires both vibration and process data in time synchronization, while ibaInSpectra automatically generates evaluable KPIs from this data. These KPIs can be directly compared with threshold values and visualized. This makes condition monitoring accessible even to operators without in-depth expertise in vibration analysis.
A differentiated analysis requires context-dependent evaluation of vibration data based on the operating point. With ibaInSpectra, KPIs can be assigned to specific states such as startup, warm-up, or production phases. This allows trends and deviations to be interpreted more precisely. In combination with ibaPDA, all relevant process parameters are incorporated into the evaluation.
Sustainable analysis requires a combination of KPI-based trending and raw data storage. Using ibaDatCoordinator and ibaAnalyzer, data can be automatically processed, exported, and stored long-term. KPIs enable fast trend analysis, while raw data remains available for in-depth investigations in the event of faults. This provides a robust foundation for continuous optimization and root cause analysis.
Early fault detection is based on continuous monitoring of defined KPIs against alarm and warning thresholds. ibaInSpectra calculates these KPIs in real time, enabling immediate evaluation. In combination with ibaPDA, relevant process context is taken into account, reducing misinterpretation. This increases response speed and sustainably improves plant availability.
Raw vibration data can be converted into interpretable condition indicators by calculating standardized KPIs such as RMS (root mean square) or crest factor. With ibaInSpectra, this transformation is performed directly based on time-synchronously acquired data from sensors and control systems. The calculations are carried out contextually depending on the machine’s operating state. This reduces complexity and enables rapid assessment of machine condition.
A practical approach is to abstract complex signal patterns into easily understandable key metrics. ibaPDA acquires both vibration and process data in time synchronization, while ibaInSpectra automatically generates evaluable KPIs from this data. These KPIs can be directly compared with threshold values and visualized. This makes condition monitoring accessible even to operators without in-depth expertise in vibration analysis.
A differentiated analysis requires context-dependent evaluation of vibration data based on the operating point. With ibaInSpectra, KPIs can be assigned to specific states such as startup, warm-up, or production phases. This allows trends and deviations to be interpreted more precisely. In combination with ibaPDA, all relevant process parameters are incorporated into the evaluation.
Sustainable analysis requires a combination of KPI-based trending and raw data storage. Using ibaDatCoordinator and ibaAnalyzer, data can be automatically processed, exported, and stored long-term. KPIs enable fast trend analysis, while raw data remains available for in-depth investigations in the event of faults. This provides a robust foundation for continuous optimization and root cause analysis.
Early fault detection is based on continuous monitoring of defined KPIs against alarm and warning thresholds. ibaInSpectra calculates these KPIs in real time, enabling immediate evaluation. In combination with ibaPDA, relevant process context is taken into account, reducing misinterpretation. This increases response speed and sustainably improves plant availability.
