With the ability to execute tasks triggered by DAT files, ibaDatCoordinator ensures seamless automation in handling recorded measurement data. Instead of manual intervention, defined processes can be started automatically whenever new data files are available, ensuring consistency and efficiency across projects.

This functionality creates a reliable bridge between raw measurement acquisition and subsequent analysis, reporting, or archiving tasks.

Key capabilities

• Automatically detect DAT files as triggers for defined workflows.
• Execute post-processing routines such as analysis, conversion, or report generation.
• Flexible configuration of task chains tailored to project requirements.
• Error handling and logging to ensure full traceability of automated runs.

By connecting measurement results directly with automated actions, users can significantly reduce repetitive work and ensure that critical evaluations are always executed in a timely and standardized manner.

Typical use cases

• Launching ibaAnalyzer immediately after recording a DAT file.
• Trigger computations, data extractions, or standardized reports once new measurement data is available.
• Automatically archiving or transferring data to central servers.
• Supporting continuous monitoring workflows with minimal manual steps.

This function turns measurement data into an immediate trigger for action, streamlining workflows and improving responsiveness.

With its scheduling functionality, ibaDatCoordinator enables users to execute tasks automatically at defined times or intervals. This eliminates the need for manual starts and ensures that recurring processes such as data analysis, conversion, or reporting run consistently and on time.

By integrating scheduled triggers, measurement workflows become more reliable and predictable.

Key capabilities

• Define time based schedules for automatic task execution.
• Configure recurring intervals (daily, weekly, or custom cycles) to match operational needs.
• Run complex task sequences without manual intervention.
• Ensure reliability with logging and status feedback for every scheduled run.
• Combine with conditions for maximum flexibility.

This automation reduces human error, guarantees timely processing, and keeps projects running smoothly even during unattended operation.

Typical use cases

• Daily generation of reports summarizing measurement results.
• Weekly data archiving to central servers.
• Periodic recalculation of KPIs for continuous performance monitoring.
• Automatic export of analysis results to external systems at fixed times.

Scheduling in ibaDatCoordinator ensures that critical tasks are performed automatically, reliably, and exactly when needed.

The integration of ibaDatCoordinator with the ibaHD-Server allows tasks to be triggered automatically by defined time periods within the high-performance data archive. Instead of exporting or analyzing data manually, processes can be initiated directly based on historical or continuous recording intervals, ensuring efficient and targeted data handling.

This functionality combines long-term data storage with automated evaluation and reporting.

Key capabilities

• Trigger tasks directly based on time periods stored in ibaHD-Server.
• Automate extraction and analysis of historical measurement data.
• Enable large-scale batch processing of archived signals without manual interaction.
• Integrate results seamlessly into reporting or higher-level systems.

By linking automation to archived measurement periods, companies can systematically evaluate long-term trends, support compliance reporting, and enhance predictive maintenance strategies.

Typical use cases

• Targeted re-analysis of specific production shifts or campaigns.
• Long-term trend evaluation for wear and performance monitoring.

Time based triggers from ibaHD-Server transform archived data into a dynamic driver for automated processes, maximizing the value of stored measurements.

With event-based triggers from the ibaHD-Server, ibaDatCoordinator can automatically execute tasks whenever defined events occur in archived or live process data. Instead of relying solely on fixed schedules, actions are launched precisely when relevant conditions are met, making workflows faster, smarter, and more efficient.

This capability transforms measurement events into direct drivers of analysis, reporting, or alerting tasks.

Key capabilities

• Detect predefined events in ibaHD-Server data as task triggers.
• Initiate automated workflows immediately upon event occurrence.
• Support complex conditions to refine when actions are executed.
• Ensure traceability through logging and monitoring of triggered actions.

By linking automation to real process events, users achieve faster response times, reduce manual effort, and improve the relevance of generated results.

Typical use cases

• Trigger immediate computations, data extractions, or report generation when critical process limits are exceeded.
• Launch defined actions after fault or alarm conditions.
• Automate notifications to maintenance teams upon irregular machine behavior.
• Support predictive maintenance by processing events linked to early fault indicators.

Event-driven execution in ibaDatCoordinator turns raw process signals into actionable intelligence, helping teams react instantly and proactively.

The conversion capability in ibaDatCoordinator allows users to transform external measurement and process data into the standardized DAT file format. This ensures that heterogeneous data sources can be integrated into the iba ecosystem, making them available for further analysis, visualization, or archiving with maximum compatibility.

By unifying data formats, companies gain a consistent and reliable basis for evaluation across all systems.

Key capabilities

• Import external file formats such as CSV, COMTRADE, TDMS, Parquet, or MATLAB.
• Convert data automatically into the standard DAT file structure.
• Ensure compatibility with the iba ecosystem.
• Configure batch processing to handle multiple external files in one run.
• Automate conversions for newly generated files.

This functionality eliminates manual conversion work and secures a continuous flow of data into existing monitoring and analysis processes.

Typical use cases

• Integrating third-party measurement systems into iba-based workflows.
• Converting CSV data files from external sensors into DAT files for trend analysis.
• Preparing external process data for correlation with iba monitoring results.

Converting external formats into DAT files ensures that all relevant measurement data, regardless of its source, becomes part of a unified and analyzable dataset.

With built-in file operation capabilities, ibaDatCoordinator can automatically copy, move, delete, or clean-up files across local storage or SMB network shares. This ensures that measurement data is always available at the right place, while keeping storage systems organized and efficient.

By automating routine file handling, engineering teams reduce manual workload and prevent data clutter in long-term projects.

Key capabilities

• Copy or move DAT files and reports to designated directories or network shares.
• Automate clean-up tasks by removing outdated or temporary files.
• Support SMB/CIFS shares for seamless integration into existing IT infrastructures.
• Combine file operations with triggers (new files, schedules, events) for full workflow automation.
• Maintain order and efficiency in large-scale data environments.

These operations ensure data is securely stored, redundant copies are avoided, and disk space is managed effectively without manual intervention.

Typical use cases

• Automatically transferring analysis results from local machines to central servers.
• Cleaning-up temporary files after batch processing runs.
• Archiving data to shared storage while freeing local capacity.
• Deleting obsolete intermediate files to comply with retention policies.

Automated file operations in ibaDatCoordinator keep measurement data organized, accessible, and under control, both locally and across networked environments.

ibaDatCoordinator streamlines reporting by automatically generating structured reports from measurement data and, if desired, distributing them directly via email. This ensures that stakeholders receive up-to-date information without manual intervention, supporting faster decisions and more transparent communication.

By embedding reporting into automated workflows, data becomes actionable and consistently available.

Key capabilities

• Automatically generate reports from DAT files or other process data.
• Flexible output formats tailored to documentation and analysis needs.
• Optional email distribution to predefined recipient groups.
• Integrate report creation into scheduled, event-based, or file-triggered workflows.
• Ensure traceability with logging of report generation and delivery status.

This functionality saves time, eliminates repetitive manual reporting tasks, and guarantees timely distribution of critical insights.

Typical use cases

• Daily shift reports automatically sent to production teams.
• KPI summaries distributed weekly to management.
• Condition monitoring reports forwarded to maintenance staff when limit violations occur.
• Compliance documentation generated and archived on a recurring basis.

In essence, automated reporting with email distribution ensures the right people receive the right insights – reliably, consistently, and on time.

With its powerful extraction capabilities, ibaDatCoordinator enables users to export time based or length-based data directly into SQL databases or various file formats. This provides maximum flexibility for integrating measurement data into enterprise IT systems, analytics platforms, or long-term archives.

The function ensures that both raw signals and calculated values can be transformed into formats that are ready for external processing and reporting.

Key capabilities

• Extract measurement data from DAT files using time or length intervals.
• Write results directly into SQL databases for enterprise-wide access.
• Convert data into multiple file formats such as CSV, Parquet, COMTRADE, TDMS, or MATLAB.
• Configure archiving profiles to define sampling rates and data sets.
• Automate recurring extractions with schedules, file triggers, or events.

By publishing iba measurement data to databases and external formats, this functionality ensures smooth data exchange between production systems and higher-level IT environments.

Typical use cases

• Storing daily data samples into SQL for dashboard visualization.
• Extracting reduced datasets for long-term trend analysis.
• Converting machine test results into CSV or MATLAB for further research.
• Providing compliance-relevant data subsets in standardized exchange formats.

In short, extraction into databases and file formats makes ibaDatCoordinator a central hub for distributing valuable measurement data across the entire organization.

ibaDatCoordinator offers the ability to run consecutive tasks conditionally, ensuring that complex workflows only continue when predefined criteria are met. Instead of executing every task in sequence blindly, conditions can be set to govern whether subsequent steps should proceed, be skipped, or follow an alternative path.

This provides users with fine-grained control over automated processes and ensures efficiency in large-scale data handling.

Key capabilities

• Define conditions for whether follow-up tasks are executed or skipped.
• Chain multiple tasks into structured workflows with logical dependencies.
• Integrate error handling so failed steps prevent invalid downstream actions.
• Optimize processing time by avoiding unnecessary operations.
• Ensure reliable automation with clear traceability in logs and status monitoring.

By applying conditional logic, automated workflows become more intelligent, adaptable, and aligned with real operational requirements.

Typical use cases

• Generate reports only when limits or anomalies are detected in extracted data.
• Skip unnecessary tasks if they are no more required for required for further processing.
• Trigger notifications solely when preceding tasks have completed successfully.

This functionality allows ibaDatCoordinator to go beyond linear automation, enabling smarter decision-driven workflows tailored to each application.

With its upload functionality, ibaDatCoordinator enables seamless transfer of measurement data to cloud platforms, remote storage locations, or even other ibaDatCoordinator instances. This makes it possible to integrate plant-level data collection into centralized IT environments or distributed monitoring systems without manual effort.

The feature ensures that valuable information flows reliably from local measurement sources to higher-level infrastructures.

Key capabilities

• Upload DAT files and reports directly to cloud systems or remote servers.
• Support remote storage targets including cloud storages, network shares, and FTP/SFTP.
• Synchronize data across multiple ibaDatCoordinator instances for distributed processing.
• Combine uploads with automation triggers such as file arrival, schedules, or events.
• Guarantee data integrity with logging and configurable retry mechanisms.

By integrating secure and automated data transfers, companies can simplify cross-location workflows and ensure that measurement data is always available where it is needed.

Typical use cases

• Centralizing production data in a corporate cloud environment.
• Forwarding measurement sets to remote engineering teams for further analysis.
• Distributing archived results between multiple ibaDatCoordinator installations.
• Ensuring redundancy by storing data both locally and on remote servers.

This capability turns ibaDatCoordinator into a hub for reliable data distribution across modern hybrid infrastructures.

With its publishing functionality, ibaDatCoordinator can forward computed values directly to a variety of target systems, including Kafka, OPC UA, SNMP, and SQL databases. This makes it possible to transform measurement results and KPIs into actionable information streams for IT, OT, and enterprise analytics environments.

The feature ensures that key indicators derived from measurement data are not only calculated but also seamlessly shared with higher-level platforms.

Key capabilities

• Publish processed or computed values to standard interfaces like Kafka, OPC UA, SNMP, or SQL.
• Integrate results into enterprise applications, dashboards, and monitoring tools.
• Enable real-time or scheduled publishing, depending on workflow needs.
• Support IT/OT convergence by providing measurement data to industrial and business systems.
• Ensure reliability with configurable logging, error handling, and monitoring.

This direct publishing capability connects measurement insights with systems that drive decision-making, monitoring, and automation.

Typical use cases

• Forward KPIs to a central SQL database for management reporting.
• Stream computed process values to Kafka for integration into big-data platforms.
• Provide OPC UA outputs for SCADA or MES systems.
• Expose SNMP values for IT monitoring tools to track plant performance.

By making computed values immediately available in widely used platforms, ibaDatCoordinator helps close the gap between data acquisition and actionable insight.

ibaDatCoordinator allows the seamless integration of custom scripts into automated processing chains. This means that user-defined logic, calculations, or external applications can be embedded directly into processing workflows, giving engineers full flexibility to adapt automation to specific project needs.

By combining standard tasks with script execution, workflows can be tailored to cover unique requirements that go beyond built-in functions.

Key capabilities

• Execute external scripts (e.g., Python, PowerShell, batch files) as part of task sequences.
• Pass parameters and data files to the scripts.
• Integrate external applications or services into automated measurement evaluation workflows.
• Apply conditional execution to run scripts only when defined criteria are met.
• Enhance flexibility by extending standard automation with project-specific logic.

This functionality makes it possible to enrich automated workflows with custom intelligence and to tightly integrate ibaDatCoordinator into broader IT and OT ecosystems.

Typical use cases

• Running a Python script for advanced data analytics after file extraction.
• Triggering a batch process to launch third-party tools.
• Executing PowerShell commands for IT-related tasks such as file management or system checks.
• Embedding machine learning models into the measurement workflow for predictive evaluations.

With script execution embedded in task sequences, users gain a powerful extension point to adapt ibaDatCoordinator precisely to their operational environment.

ibaDatCoordinator can expose the live status of jobs and task executions directly through SNMP or OPC UA server nodes. This gives IT and OT systems immediate visibility into automation workflows, allowing operators, monitoring tools, and higher-level applications to track progress, detect failures, and confirm successful completions in real time.

By integrating status updates into standard industrial and IT protocols, process transparency and operational reliability are significantly enhanced.

Key capabilities

• Publish task and job execution states (running, completed, failed, pending) as SNMP or OPC UA nodes.
• Integrate seamlessly with monitoring tools.
• Enable proactive actions by providing real-time feedback on task execution.
• Support centralized dashboards with up-to-date information on all automated workflows.
• Facilitate IT/OT convergence by using widely adopted communication standards.

This ensures that both production engineers and IT administrators can supervise automation processes without needing direct access to ibaDatCoordinator.

Typical use cases

• Integrating task execution states into monitoring dashboards via OPC UA.
• Feeding job status into network monitoring systems through SNMP.
• Providing real-time visibility for operations teams during automated data processing.
• Alerting IT/OT staff immediately when automated workflows fail.

By offering real-time feedback through SNMP and OPC UA, ibaDatCoordinator makes automation processes fully transparent and easier to supervise across diverse system landscapes.

ibaDatCoordinator offers a robust logging system that records all task executions and system activities in detail. To make analysis efficient, the logs can be filtered by time, task type, status, or error conditions, enabling users to quickly find the information they need without wading through irrelevant entries.

This ensures maximum transparency in automated workflows and provides a solid foundation for troubleshooting and compliance.

Key capabilities

• Record complete execution history of tasks and workflows, including timestamps and results.
• Filter logs dynamically by status (success, warning, error), task category, or time ranges.
• Support fast troubleshooting by isolating problematic tasks.
• Ensure traceability across complex, multi-step automation sequences.

With these capabilities, users can easily monitor performance, identify bottlenecks, and demonstrate accountability for automated processes.

Typical use cases

• Investigating failed jobs by filtering logs for errors only.
• Analyzing performance trends by reviewing recurring warnings.
• Simplifying root cause analysis with time based log filters.

The combination of detailed logging and intelligent filtering empowers engineering teams to maintain clarity, reliability, and control over every automated workflow.