collect. analyze. Utilize.

Digital and Data Solutions for Engineering
Applications

EUtech's digital and data solutions help engineering teams connect, structure and use technical data from machines, equipment, laboratories, simulations and enterprise systems to support analysis, transparency and informed decisions

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solution

Data-Driven Engineering

We design and implement digital and data solutions that make technical data usable across systems, teams and applications

Key Challenges

Hidden data makes existing knowledge difficult to find and reuse

Large data volumes require time-consuming manual evaluation

Different formats require manual preparation before data can be compared

Missing context limits understanding of real product behavior

Limited accessibility slows informed engineering decisions

Our Solution

Connected data sources make existing knowledge searchable and reusable

Consistent data evaluation supports extraction, comparison and anomaly detection

Consistent data structures connect information across tools and formats

Contextualized engineering data links test, simulation and field information

Decision-ready insights support product evaluation and engineering improvement

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25+ Years of Experience
End-to-End Support
Integrated Engineering and Data Expertise
competencies

Data Engineering Expertise

Data Integration

Connecting machines, test systems, simulations and existing data sources across technical environments

Data Modeling

Structuring data, metadata and technical relationships for consistent analysis and reuse

Data Management

Handling storage, versioning, access and traceability for reliable use of technical and engineering data

Time-Series Data Analytics

Analyzing large volumes of machine and process data to identify trends, deviations and technical relationships

AI and Machine Learning

Applying data-driven models for anomaly detection, prediction and advanced engineering analysis

From connected data to engineering insight, trusted expertise for data-driven decisions.

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benefits

Turning Data into Actionable Insights

Use of Existing Data

Unlock value from data that already exists across systems and teams

Reduced Workload

Reduce manual effort through connected data flows and digital workflows

Reliable Decisions

Build decisions on data that is usable, consistent and relevant

Trusted Partnership

Rely on experienced specialists with engineering and data competence

Applications

Proven Digital and Data Solutions

Make use of your industrial and engineering applications with digital and data solutions tailored to technical requirements, existing systems and practical implementation

Model-Based Engineering

Use simulation models, control logic and validation workflows to understand system behavior earlier and support reliable engineering decisions

Dynamic system and process models
Control logic validation
MiL and HiL workflows
Model-based analysis and optimization
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Virtual Sensors and Sensor Fusion

Derive additional process and condition information from existing measurements, models and system data where direct sensing is limited or impractical

Derived values from measurements and system data
Virtual sensing for process and condition monitoring
Model-based support for indirect measurement tasks
Use of operational and simulation data
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Predictive Maintenance

Use operating data, condition monitoring and analytics to detect degradation early and support maintenance decisions before failures occur

Early detection of deviations, wear and potential failure
Condition-based maintenance using machine and sensor data
Continuous monitoring of asset condition and operating behavior
Detection of anomalies in operational data
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Test Data Management

Manage test and measurement data with structured workflows, traceable results and interfaces for analysis, reporting and validation

Central access to test, measurement and validation data
Structured data acquisition, storage, evaluation and traceability
Connected workflows across test benches, systems and teams
Reliable data basis for analysis, reporting and validation
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Explore All Applications
Process

Ideas Need Energy

Requirements and Scoping

We clarify the task, objectives, framework conditions and the systems involved

Data and System Review

Existing data sources, interfaces and workflows are reviewed in their technical context

Concept and Solution Design

The right approach is defined in terms of scope, architecture and implementation priorities

Development and Integration

Solution components are developed, adapted and connected to the existing environment

Validation and Rollout

Functions, data flows and results are checked before practical deployment

Continuous Support

We support onboarding, further development and additional digital use cases

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Let's Talk About Your Project

Whether you are planning a new digital solution, improving an existing setup or looking for support in data analysis, integration or implementation, we help define the right approach for your technical environment

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Alexander Hlawenka

Manager Digital Solutions

digital@eutech.de+49 (0) 2408 713 42 30
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FAQ

Frequently Asked Questions

How can EUtech help us improve engineering data management?

EUtech supports engineering data management by connecting distributed data sources, structuring technical data and creating workflows for storage, access, versioning and traceability. This helps teams manage measurement data, test results, metadata, simulation outputs and operating data more consistently across systems, departments and sites.

Can EUtech connect data from our existing machines, test benches and software systems?

Yes. EUtech focuses on integrating existing data sources instead of replacing complete system landscapes. Machines, sensors, test systems, laboratories, simulations and enterprise applications can be connected through suitable interfaces, data flows and data models so technical information becomes easier to access, compare and use.

What makes test data management important for validation teams?

Test data management helps validation teams work with structured measurement data, traceable results and reliable reporting workflows. It reduces manual effort, improves reproducibility and makes it easier to compare current and historical test data from different benches, systems or component variants.

How can predictive maintenance be applied to our equipment or assets?

Predictive maintenance uses operating data, sensor signals and condition monitoring to detect deviations, wear or early signs of failure. EUtech can help structure and analyze this data so maintenance decisions are based on actual asset condition, anomaly detection and operating behavior rather than fixed service intervals alone.

Where do model-based engineering, virtual sensors and sensor fusion create value?

These methods are useful when engineering teams need deeper insight into system behavior or when direct measurement is difficult. Simulation models, control logic validation, MiL and HiL workflows, virtual sensors and sensor fusion can support indirect measurement, process monitoring, condition analysis and earlier validation of technical decisions.

What does a typical digital and data project with EUtech involve?

A project usually starts with requirements and scoping, followed by a review of existing data sources, systems, formats and workflows. EUtech then defines the data structures, interfaces and solution concept before development, integration, validation and rollout, with continuous support available when the solution needs to evolve.

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Connected Engineering Data in Testing, Analysis and Validation

Engineering data solutions help technical teams connect high-volume machine, sensor, test bench, simulation, field and production data. EUtech structures and contextualizes this information, links results to engineering requirements and supports advanced analysis for validation, troubleshooting and data-driven decisions

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Typical Applications and Use Cases

  • Test data management for high-sample time-series data, validation results, images and video
  • Linking test results to engineering requirements for traceable verification and validation
  • Root cause analysis across production data, process stages and quality results
  • Field data acquisition using configured data loggers in mobile validation fleets
  • Predictive maintenance through condition monitoring and anomaly detection
  • Continuous adaptation of simulation models using measurement and field data
  • Virtual sensors and sensor fusion for derived process and condition information
  • Data connectivity across test benches, machines, laboratories and production systems

How Our Customers Benefit

Connected and contextualized engineering data improves traceability, comparability and reuse across teams, systems and sites. Automated extraction, evaluation and anomaly detection reveal patterns and interactions within large time-series datasets.

EUtech combines data engineering with analytical engineering expertise. We investigate structural problems in production, identify possible root causes and relate test, field and production data to technical requirements and product behavior.

Existing data sources and system landscapes are integrated wherever practical instead of being replaced by another isolated tool. This creates reliable information flows for validation, troubleshooting, model development and engineering decisions.

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These solutions support engineering teams working with test systems, laboratories, production equipment, simulation models and operational assets. Typical fields include automotive and mobility development, energy systems, industrial equipment, research and validation environments.

Discuss your application with EUtech to identify the right digital and data approach for your engineering challenge.

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