Powerful Analysis and Evaluation of Measurement Data

With ibaAnalyzer, users can directly open and view measurement files in DAT format, the native file type used within the iba system for storing time-synchronized process data. This capability allows engineers, analysts, and maintenance teams to quickly access both raw and calculated values without requiring conversion or data preprocessing.

Upon opening a DAT file, ibaAnalyzer provides immediate access to all recorded signals, metadata, and annotations. The software’s interactive interface lets users navigate through the timeline, zoom into areas of interest, and switch between different visualization modes such as trends, FFTs, or statistical overviews. Because DAT files maintain full time synchronization between channels, complex multi-signal analyses can be carried out with complete accuracy.

Key capabilities

• Load iba DAT files directly without conversion.
• Display synchronized multi-signal trends for detailed analysis.
• Access raw and calculated values easily side by side.
• Use advanced navigation tools like zoom, markers, and intervals.
• Leverage multiple signal domains including time, length, and frequency.

Typical use cases

• Reviewing recorded production process data.
• Analyzing fault events captured during operation.
• Performing in-depth post-process evaluations for quality assurance.
• Comparing measurement runs to identify process changes.

By opening DAT files natively, ibaAnalyzer ensures fast, accurate, and efficient access to rich process datasets for effective troubleshooting, optimization, and quality control.

ibaAnalyzer provides seamless access to historical process data stored in ibaHD-Server, enabling users to retrieve exactly the information they need for post-process analysis. Instead of working only with locally stored measurement files, analysts can connect directly to the central high-density data repository and query specific time ranges, signals, or events.

The query process is highly flexible: users can define time intervals, apply filters, and select multiple signals from large datasets without having to download entire archives. Retrieved data is loaded into ibaAnalyzer’s interactive environment, where it can be visualized, compared, and processed using the full range of analysis tools. Because ibaHD-Server stores data with precise time synchronization, queried results maintain full alignment across all channels for accurate evaluations.

Key capabilities

• Connect directly to ibaHD-Server from any ibaAnalyzer instance.
• Select specific time ranges and signals for targeted analysis.
• Filter historical data by event or process state.
• Maintain time-synchronized datasets across all channels.
• Work with central storage without copying entire data archives.

Typical use cases

• Investigating plant events from long-term historical archives.
• Comparing current production performance with past benchmarks.
• Performing root cause analysis on intermittent process issues.
• Extracting specific production cycles for quality reporting.

By enabling direct querying from ibaHD-Server, ibaAnalyzer turns historical data into an on-demand resource for troubleshooting, optimization, and performance monitoring.

ibaAnalyzer allows users to directly access and analyze data stored in SQL-based databases, integrating process measurements with information from external systems such as MES, ERP, or quality management platforms. This connection makes it possible to combine iba’s time-synchronized process data with operational, logistical, or quality datasets for a complete production overview.

Through its database interface, ibaAnalyzer can query specific tables and fields, and use conditions, retrieving exactly the records needed for the analysis task. Retrieved data can be visualized alongside measurement signals, enabling correlation between process events and business or quality data. The integration supports many common database systems including Oracle, Microsoft SQL Server, PostgreSQL, and MySQL, ensuring compatibility in diverse IT environments.

Key capabilities

• Connect directly to external SQL databases from ibaAnalyzer.
• Select and filter records based on custom query conditions.
• Combine database results with measurement data for unified analysis.
• Correlate process events with quality or production KPIs.
• Work with multiple database types in a single analysis session.

Typical use cases

• Linking process measurements with quality inspection results.
• Investigating production delays using MES and process data together.
• Analyzing energy consumption records alongside operational trends.
• Creating reports that merge process signals and business metrics.

By querying SQL databases directly, ibaAnalyzer extends its capabilities beyond measurement files, enabling data-driven decision-making that bridges production and business systems.

ibaAnalyzer can import and analyze process data from a wide range of external file formats, making it easy to integrate measurements from third-party systems into the iba analysis environment. This capability allows users to work with heterogeneous datasets without manual conversion, ensuring that valuable process information from different sources can be evaluated together.

Supported formats include standard text and CSV files, binary measurement formats such as Comtrade and Parquet, and application-specific exports from other analysis tools or data acquisition systems. Once imported, external data is treated like native iba data—meaning it can be visualized, synchronized, and processed using ibaAnalyzer’s full range of tools, including trend analysis, statistical evaluation, and frequency analysis.

Key capabilities

• Import multiple external formats such as CSV, TXT, and industry-specific measurement files.
• Combine imported data with iba DAT files or ibaHD-Server datasets.
• Synchronize signals from different sources for comparative analysis.
• Apply the full ibaAnalyzer toolset to external measurements.
• Facilitate cross-system evaluations without losing time on format conversion.

Typical use cases

• Merging third-party measurement results with iba recordings.
• Analyzing supplier test data alongside in-house process data.
• Comparing simulation output files with real production measurements.
• Incorporating laboratory test results into production quality reports.

By reading external file formats directly, ibaAnalyzer makes it possible to create a unified analysis workspace that bridges different measurement systems and data sources.

ibaAnalyzer can aggregate high-resolution measurement data, compute characteristic values and KPIs, and publish those results to SQL databases or standard external file formats. Calculations and pre-processing are done inside ibaAnalyzer so the values stored are traceable and ready for integration into MES, ERP or data-warehouse systems. For automated, scheduled, or event-triggered publishing, ibaDatCoordinator can run extraction jobs and push results to databases or files without manual interaction.

Key capabilities

• Aggregate and compute KPIs (time- or length-based) from raw and virtual signals before export.
• Write to SQL databases using standard ADO.NET connectors (MSSQL, Oracle, DB2, MySQL, PostgreSQL, SQLite, Access) with automatic table creation support.
• Export to external file formats (CSV, Parquet, TDMS, COMTRADE, Matlab, DAT) via the data extractor or ibaDatCoordinator tasks.
• Select extraction profiles to store average, min, max, standard deviation or single-value series and to control data volume and format (single values or BLOBs).
• Automate publishing workflows (batch, triggered, time-based) and include notifications or alarms using ibaDatCoordinator.

Typical use cases

• Feeding validated KPIs into MES or Data Warehouse for production reporting.
• Exporting length-normalized quality metrics for customer certificates.
• Publishing aggregated process parameters to analytics platforms or cloud services.

By pre-computing and publishing traceable KPIs, the iba toolchain ensures that downstream systems receive compact, meaningful, and auditable process information.

With ibaAnalyzer’s built-in Data Extractor, users can seamlessly transform and export high-resolution measurement signals into SQL databases or a wide range of standard file formats. This ensures that critical process and quality data from iba data files can be integrated into reporting systems, analysis platforms, or long-term archives without losing fidelity. Extraction can be performed interactively or automated using ibaDatCoordinator.

Key capabilities

• Extract to SQL databases via a dedicated database interface, supporting common systems like MSSQL, Oracle, DB2, MySQL, PostgreSQL, and more.
• Export to external formats such as CSV, Apache Parquet, Matlab, COMTRADE, and TDMS, enabling direct use in third-party tools.
• Configure archive profiles to define time- or length-based sampling, segment-based extraction, or use the signal’s native time base.
• Include computed columns and info fields so exported data already contains processed KPIs, min/max values, or metadata.
• Automate extraction workflows with ibaDatCoordinator, including scheduling, triggered execution, and logging.

Typical use cases

• Feeding signal data into SQL databases for integration with MES/ERP.
• Generating CSV or Parquet extracts for advanced analytics in Python, R, or Spark.
• Exporting COMTRADE files for fault analysis in power systems.
• Preparing long-term TDMS or Matlab archives for research and testing.

By enabling both database connectivity and flexible file export, ibaAnalyzer ensures that measurement data is always accessible in the right structure and format for downstream applications.

ibaAnalyzer includes powerful reporting capabilities that transform raw measurement data into clear, structured, and actionable reports. With ibaAnalyzer-Reportgenerator, recurring reports can be created automatically from predefined templates—ensuring that every analysis run produces consistent, high-quality documentation without repetitive manual effort.

Reports can contain signal trends, KPIs, statistical evaluations, maps, and synchronized video snapshots, all drawn directly from the analyzed datasets. Because the content is dynamically linked to the underlying data, reports always reflect the most current results. Users can customize layouts, incorporate company branding, and define event-driven or time-based triggers to automatically generate and distribute reports.

Key capabilities

• Automate recurring reports using customizable templates.
• Include rich visuals such as trends, FFTs, maps, and images.
• Integrate KPIs and computed values for immediate interpretation.
• Trigger reports automatically based on time schedules or process events.
• Distribute reports in standard formats for easy sharing.

Typical use cases

• Creating shift or daily production summaries.
• Generating quality certificates for coils, strips, or batches.
• Providing audit-ready documentation of plant incidents.
• Supporting management with KPI-focused performance dashboards.

By turning raw measurement data into structured reports, ibaAnalyzer helps organizations communicate insights effectively, ensuring that stakeholders at every level can make informed decisions.

ibaAnalyzer allows you to save complete analysis settings, including selected signals, display layouts, calculation formulas, and extraction profiles—for consistent reuse. This eliminates repetitive setup work and ensures evaluations are performed in a standardized, reproducible way across teams or over long periods of time.

For further efficiency, the optional ibaDatCoordinator takes stored analysis configurations and runs them automatically in the background. Jobs can be scheduled, triggered by events, or executed in batches. This means recurring analyses, data extractions, or report compilations happen reliably without manual interaction, freeing up engineers to focus on interpreting results instead of managing workflows.

Key capabilities

• Save analysis setups with signals, layouts, and formulas for easy reuse.
• Standardize evaluations across projects, shifts, or departments.
• Automate recurring tasks such as data extraction and report creation.
• Schedule or trigger jobs to run unattended in ibaDatCoordinator.
• Ensure reproducibility and consistency in long-term analysis workflows.

Typical use cases

• Running the same analysis automatically on new production data each shift.
• Standardizing KPI calculations for use in quality certificates.
• Automating extraction of datasets into SQL or file formats for integration.
• Generating recurring reports without manual intervention.

By combining reusable settings with automation, ibaAnalyzer and ibaDatCoordinator provide a robust framework for efficient, repeatable, and hands-free analysis workflows.

With its comprehensive visualization and analysis capabilities, ibaAnalyzer enables engineers to explore machine and process signals in detail. Signals can be displayed intuitively in multiple formats, compared across channels, and examined with mathematical and statistical tools to uncover patterns, deviations, or root causes.

This functionality forms the backbone of precise diagnostics and process optimization.

Key capabilities

• Visualize signals in time, frequency, and statistical domains with flexible chart options.
• Combine multiple channels for synchronized comparison of process and machine data.
• Apply analysis tools such as FFT, filters, envelopes, and spectral analysis.
• Use interactive cursors and zoom for detailed signal inspection.
• Perform calculations and transformations to derive key performance indicators.
• Automate recurring evaluations with configurable analysis templates.

These capabilities provide a deep understanding of machine behavior and process dynamics, ensuring that even complex interactions are made transparent.

Typical use cases

• Root cause analysis of production disturbances.
• Evaluating vibration and condition data for predictive maintenance.
• Comparing operating states under different loads or material conditions.
• Validating process optimizations through before/after signal analysis.
• Supporting commissioning and troubleshooting in industrial environments.

By combining clear visualization with advanced analytical methods, ibaAnalyzer empowers users to transform raw measurement signals into actionable insights for better performance and reliability.

ibaAnalyzer offers powerful tools to display and explore time series and signal data interactively, enabling users to understand process behavior at a glance. Whether working with measurements from DAT files, ibaHD-Server queries, or imported datasets, the software provides multiple visualization options to reveal trends, anomalies, and correlations.

Users can select classic trend charts, zoomable multi-signal displays, FFT frequency views, scatter plots, and specialized diagrams for deeper analysis. Interactive features—such as synchronized markers, scaling, and intervals—make it easy to focus on specific events or compare multiple signals. Because ibaAnalyzer maintains full time synchronization between channels, even complex datasets can be analyzed with complete temporal accuracy.

Key capabilities

• Display multi-channel time series with full zoom and navigation controls.
• Switch between visual formats including trends, FFTs, and scatter plots.
• Use synchronized cursors and overlays for detailed comparisons.
• Highlight and annotate significant process events.
• Work with both raw and calculated values in the same view.

Typical use cases

• Investigating faults through time-synchronized signal visualization.
• Comparing production runs for performance differences.
• Visualizing frequency spectra for vibration or power analysis.
• Reviewing long-term trends for process optimization.

With its versatile visualization capabilities, ibaAnalyzer turns raw time series and signal data into clear, actionable insights for troubleshooting, optimization, and quality assurance.

ibaAnalyzer makes it easy to explore process data at different levels of detail by offering intuitive zoom and drill-down functionality. This allows users to move seamlessly from a high-level overview of long-term trends to detailed views of individual events, all within the same dataset.

Using zoom, operators can quickly focus on specific time intervals or signal regions, while the drilldown feature enables a stepwise transition to higher-resolution data—such as moving from aggregated hourly averages to second-by-second values. All navigation maintains time-synchronized alignment across signals, ensuring that relationships between variables remain visible at every scale.

Key capabilities

• Zoom in and out for precise focus or broad overviews.
• Drill-down into higher-resolution data without reloading.
• Aggregation of measurement data to see wider process trends while keeping event context.
• Maintain synchronization of all signals during navigation.
• Work across aggregation levels from long-term historical data to raw samples.

Typical use cases

• Investigating a fault event starting from weekly production data.
• Moving from summarized KPI views to raw sensor readings.
• Analyzing power consumption peaks in both daily and millisecond detail.
• Reviewing product quality metrics at plant, line, and sensor levels.

By enabling smooth navigation across multiple aggregation levels, ibaAnalyzer lets users connect the big picture with fine-grained details, making analysis faster, clearer, and more accurate.

ibaAnalyzer provides a comprehensive set of tools to evaluate and relate multiple datasets—whether they originate from different measurement runs, plant sections, or external sources. Users can directly compare signals side by side, quantify differences through statistical metrics, and perform synchronization or alignment to ensure time and positional consistency.

Correlation functions allow analysts to identify relationships between variables, while aggregation tools combine multiple datasets into meaningful summaries, such as averages, sums, or key performance indicators (KPIs). These capabilities make it possible to merge and evaluate diverse data sources in a single environment, enabling a complete and unified view of process behavior.

Key capabilities

• Compare datasets from different measurements or time periods.
• Quantify deviations using statistical calculations.
• Synchronize and align signals for accurate temporal or positional matching.
• Correlate variables to identify cause-and-effect relationships.
• Aggregate multiple signals to produce summary values or KPIs.

Typical use cases

• Comparing pre- and post-maintenance performance.
• Aligning measurement files from different plant locations.
• Correlating process parameters with quality outcomes.
• Aggregating production data for monthly performance reporting.

By enabling precise comparison, alignment, correlation, and aggregation, ibaAnalyzer ensures that complex, multi-source datasets become coherent, actionable insights for process optimization and quality control.

ibaAnalyzer enables users to convert signals seamlessly between different domains—time, length, and frequency—so that data can be analyzed in the most relevant context for the process. Time-based measurements can be transformed into length-related views for product-specific evaluation, or into the frequency domain using FFT for vibration, power quality, or other spectral analyses.

Beyond domain transformations, ibaAnalyzer offers powerful calculation tools to derive metrics and Key Performance Indicators (KPIs) directly from measurement data. Users can compute averages, maxima, standard deviations, or custom formulas, as well as process-specific quality measures. These results can be displayed alongside original signals or exported for use in reports and higher-level systems.

Key capabilities

• Transform data between time, length, and frequency domains.
• Apply FFT analysis for spectral evaluation of signals.
• Compute statistical measures such as average, min, max, and standard deviation.
• Define custom KPIs relevant to production and quality targets.
• Display calculated results in synchronization with raw data.

Typical use cases

• Evaluating coating thickness along product length instead of over time.
• Performing frequency analysis on vibration signals for machine diagnostics.
• Calculating production efficiency KPIs from process parameters.
• Monitoring quality compliance using automatically computed metrics.

By combining domain transformation with KPI calculation, ibaAnalyzer empowers engineers to view, interpret, and quantify process performance from multiple analytical perspectives.

ibaAnalyzer allows users to apply operations to signals and instantly see the results through its WYSIWYG (What You See Is What You Get) interface. Whether performing arithmetic calculations, filtering noise, scaling values, or combining multiple signals, changes are reflected immediately in the visualization, enabling fast, iterative analysis without guesswork.

This interactive approach makes it possible to test different processing methods—such as smoothing, integration, or differentiation—while directly observing their effects on trends, spectra, or other graphical views. Because all transformations maintain full time synchronization, users can confidently evaluate the impact of signal processing steps before finalizing calculations or generating reports.

Key capabilities

• Apply signal operations like addition, subtraction, scaling, and filtering.
• Preview results instantly without leaving the analysis view.
• Test multiple processing methods to find optimal analysis settings.
• Maintain full time synchronization between processed and original signals.
• Combine and transform multiple signals in real time.

Typical use cases

• Filtering noise from sensor data for clearer trend evaluation.
• Scaling measurements to physical units during analysis.
• Combining process parameters to calculate derived performance indicators.
• Comparing raw and processed signals side by side for validation.

With immediate, visual feedback on signal operations, ibaAnalyzer turns data processing into an interactive, transparent, and efficient process, ensuring confidence in every analytical step.

ibaAnalyzer can be expanded beyond its standard toolset by creating custom macros and computation modules tailored to specific analysis needs. This flexibility allows engineers and analysts to embed their own logic, formulas, or processing routines directly into the analysis workflow, ensuring the software adapts to unique plant processes or quality requirements.

Macros can automate repetitive analysis steps, standardize evaluations across teams, or integrate plant-specific KPIs into every dataset. Custom computation modules extend the mathematical and statistical capabilities of ibaAnalyzer, enabling advanced calculations, condition-based logic, or integration with external algorithms. These extensions work seamlessly with all ibaAnalyzer visualization and synchronization features, ensuring that user-defined results remain aligned with raw and processed signals.

Key capabilities

• Create reusable macros to automate common analysis tasks.
• Define custom formulas or algorithms for specialized evaluations.
• Integrate plant-specific KPIs directly into analysis workflows.
• Combine custom outputs with native ibaAnalyzer tools and views.
• Share macros and modules across teams for consistent evaluations.

Typical use cases

• Automating daily or shift-based quality reports.
• Embedding industry-specific compliance checks into data analysis.
• Calculating proprietary process performance indicators.
• Standardizing troubleshooting procedures for recurring issues.

By extending its core functions with user-defined macros and computation modules, ibaAnalyzer becomes a fully adaptable analysis platform that grows with the needs of the plant and its processes.

ibaAnalyzer makes it easy to share analysis results instantly by allowing users to copy signal data or charts directly to the clipboard. This enables fast transfer of trends, graphs, or numerical datasets into emails, documents, or presentations without exporting files or performing additional formatting.

Charts can be copied exactly as they appear on screen, preserving zoom levels, colors, annotations, and overlays for clear communication. Likewise, numerical signal data can be copied in a structured format, ready to paste into spreadsheets or reports for further use. This quick sharing capability speeds up collaboration between operators, engineers, and management, ensuring that insights are communicated while they are still actionable.

Key capabilities

• Copy charts to clipboard with full visual formatting.
• Transfer numerical signal data for immediate spreadsheet use.
• Preserve annotations and overlays in copied charts.
• Enable instant sharing without exports or file transfers.
• Support fast communication across teams and departments.

Typical use cases

• Sending a fault event chart to maintenance via email.
• Including process trends in a shift handover report.
• Pasting KPI trends into a management presentation.
• Sharing analysis snapshots during remote troubleshooting sessions.

By enabling rapid sharing via the clipboard, ibaAnalyzer ensures that critical process insights can be communicated quickly and effectively, improving collaboration and decision-making.

ibaAnalyzer integrates seamlessly with ibaCapture, enabling users to analyze process sensor data and video recordings in perfect synchronization—either by time or by product length. This powerful combination allows operators and engineers to correlate visible process events with underlying measurement signals, creating a complete picture of what happened and why.

In a synchronized view, video frames align precisely with the corresponding data points from the process, making it possible to identify the exact moment of defects, equipment malfunctions, or process deviations. Users can zoom, navigate, and compare signals and video footage together, ensuring no detail is overlooked. Length-based synchronization adds an additional layer of accuracy for continuous products, allowing visual inspection to match exact positions along the strip, sheet, or coil.

Key capabilities

• Synchronize video and sensor data by time or by product length.
• Correlate visual events with measurement signals for deeper insight.
• Zoom and navigate both video and signals in parallel.
• Identify root causes by combining visual and analytical evidence.
• Support length-based defect localization for continuous products.

Typical use cases

• Detecting the cause of strip surface defects in rolling or coating lines.
• Investigating intermittent machine faults by combining visual and signal evidence.
• Performing quality verification through synchronized process review.
• Training operators using real-world video linked to measurement data.

By combining sensor and video data in a synchronized analysis, ibaAnalyzer with ibaCapture delivers unmatched clarity and context, turning process monitoring into actionable insight.

The Maps view in ibaAnalyzer displays GPS positions and routes alongside high-resolution measurement data, so you can see when and where events occurred. Simply record longitude and latitude signals, then correlate location with process behavior in a dockable map. The map view supports different map types, route styling, two-way coupling with markers, and integrated playback for time-synchronized review. Maps can also be included in ibaAnalyzer-Reportgenerator reports.

Key capabilities

• Display configurable routes on various map types with adjustable color and thickness.
• Correlate location and signals by coupling movable markers between maps and trends.
• Analyze time trends with playback while following asset movement on the map.
• Embed geospatial visuals in reports using ibaAnalyzer-Reportgenerator.
• Track multiple assets simultaneously with flexible configuration of position and labeling data.

Typical use cases

• Monitoring vehicles, ships, or mobile machines and linking routes to process signals.
• Pinpointing location-dependent anomalies (e.g., vibration peaks at specific sites).
• Creating audit-ready reports that show what happened, when, and where

By bringing GPS data onto the same canvas as your process signals, ibaAnalyzer turns geolocation into a powerful diagnostic dimension, so you can see what happened, when it happened, and exactly where.

ibaAnalyzer-InCycle provides specialized tools to visualize,analyze and evaluate cyclical and rotating machinery, making it easier to understand vibrations, harmonics, and other periodic phenomena. Signals from turbines, motors, drives, or gearboxes can be transformed into the frequency domain, overlaid with harmonic markers, or displayed as orbit and order spectra to reveal mechanical conditions that are hidden in standard time trends.

Users can configure monitoring profiles tailored to specific machine characteristics, including operating speeds, bearing frequencies, or critical harmonics. This enables fast detection of imbalance, misalignment, or wear, and supports condition-based maintenance strategies. Combined with length- and time-based analysis, cyclical monitoring delivers both short-term diagnostic insight and long-term trend visibility.

Key capabilities

• Visualize vibrations and harmonics with FFT and order analysis.
• Configure monitoring parameters for rotating machinery (speed, orders, markers).
• Display orbit and shaft movement diagrams for mechanical diagnostics.
• Detect faults early such as imbalance, misalignment, or bearing damage.
• Combine time, length, and frequency views for comprehensive evaluation.

Typical use cases

• Monitoring turbines, compressors, or large motors in production plants.
• Identifying early-stage bearing or gearbox failures.
• Correlating vibration peaks with process conditions.
• Supporting predictive maintenance with historical trend comparisons.

By offering configurable analysis of cyclical and rotating processes, ibaAnalyzer ensures early fault detection and reliable machinery monitoring, reducing downtime and protecting critical assets.

ibaAnalyzer-InSpectra provides dedicated functions to visualize, analyze and evaluate vibration signals, supporting both detailed diagnostics and long-term monitoring. Using high-resolution data, vibrations can be examined in time, frequency, and order domains, giving a complete picture of machine behavior under varying operating conditions.

Analysts can configure vibration monitoring by defining characteristic frequencies, orders, and thresholds relevant to bearings, shafts, or housings. The software supports FFT analysis, orbit diagrams, envelope detection, and statistical evaluations, enabling early detection of faults such as imbalance, misalignment, or bearing damage. These vibration insights can be combined with process signals to directly link mechanical issues with operational events.

Key capabilities

• Perform FFT and order analyses for detailed vibration evaluation.
• Configure monitoring parameters (e.g., frequencies, thresholds, harmonics).
• Visualize orbits and shaft movement for rotating machinery diagnostics.
• Apply envelope detection and statistical tools for fault detection.
• Correlate vibration signals with process data for root cause analysis.

Typical use cases

• Continuous monitoring of motors, gearboxes, and turbines.
• Detecting early-stage bearing wear or shaft imbalance.
• Identifying vibration-related causes of product defects.
• Supporting predictive maintenance and asset health initiatives.

With its configurable vibration analysis, ibaAnalyzer helps engineers to detect mechanical issues early, reduce downtime, and optimize maintenance strategies.