We offer IIoT-based Solutions for

Holistic Stream Data Analytics & Process Mining

in Automated Production








Products & Services



Infrastructure & Integration

for Simplified Access of Existing Low Level Process Control and Sensor Data for Structured Stream Analytics

Process Analytics & Service Toolkits

for Data Driven Training of Digital Twins under Unified View on Systems, Processes & Products

Knowledge & Solution Transfer

for Automated and Prioritized Transfer of  Successful Analytics Services and Optimization Measures






Selected Use Case Scenarios




Process Mining in Automated Production Systems

Commissioning of automated production systems usually follows standardized, stability-oriented procedures. Hence, the resulting performance is limited and the potential to increase productivity often exceeds 10%. However, relevant factors (e. g. system parameters, environmental conditions) influencing the process are often unknown.

  • Problem

    • Relevant key figures for the quantitative assessment of system performance are not available.
    • Selection and prioritization of appropriate optimization measures require extensive time and expertise.
    • With increasing system complexity these tasks become even more challenging, even for experts.

  • Our Solution

    • Complexity reduction through centralization of system information, process characteristics as well as control and sensor data streams
    • Generic algorithms for automated training of hybrid process models based on discrete control events and continuous data
    • Analysis under holistic view on machines, products and processes reveals additional relevant information and system characteristics
    • Structured data orchestration providing a solid basis for targeted application of specific analytics services from our toolboxes or third parties

  • Benefits & Advantages

    • Gain deep insights into actual system behavior under interpretable visualization of discrete process flows and sensor data features through recurring process cycles
    • Simplified and reliable quantification of Key Performance Indicators (KPI) for profound evaluation of Process Integrity or Overall Equipment Effectiveness (OEE), Proofs of conformity for system and process certification 
    • Comparative assessment of real-world system behavior based on the initial system specifications (re-engineering of the PLC code)
    • Detection of critical process steps, system bottlenecks and unstable sequences to prioritize optimization measure




Benchmarking of Systems and Processes

Production processes of identical or similar lines, cells or machines often run in parallel, at the same or at a different location. Alternatively, equal processes are operated using similar systems from different manufacturers.

  • Problem

    • Root causes for deviations and occurring discrepancies in performance are often unclear
    • The given problem complexity is not manageable by conventional approaches

  • Our Solution

    • Data driven training of system and process models for direct and quantifiable comparison
    • Comparison of statistical key figures and data features to identify causes for occurring deviations
    • Localization of relevant sub-process steps and defective technical components

  • Benefits & Advantages

    • Minimized effort and time to identify deviations and detect causalities
    • Incentives for plant operators through measurable performance indication and competition
    • Increased overall performance through focused modification of underperforming systems
    • Transparency about proven potentials, validated by best performing counterpart




Online Process Monitoring & Anomaly Detection

Maintenance measures take place preventively or after fixed intervals. Furthermore, critical deviations of process and Products quality are detected only with delay, resulting in unexpected system downtime.

  • Problem

    • The majority of critical states is not detectable by local monitoring of subsystems (plus additional sensors are expensive)
    • Even slight deviations reduce overall performance excessively but are usually not detectable even by experienced personnel
    • Often system are too complex to centralize essential information to combine individual state information of subsystems

  • Our Solution

    • Structurization and centralization of accessible process and sensor data via heterogeneous interfaces
    • Software services to implement performant data stream pipelines based on IIoT infrastructures
    • Implementation of digital process twins integrating machines, product and process characteristics
    • Anomaly detection in physical and statistical behaviour of machine components and process sequences
    • APIs for standardized access to process and machine data for additional analytics and monitoring services

  • Benefits & Advantages

    • Messaging system for detected deviations lead maintenance teams to critical components with extended information
    • Traceability of product individuals with evaluation of process integrity
    • High-Sensitivity and Real-Time Monitoring of relevant key performance indices and individual data features
    • Web-Interfaces for Visualization and direct Integration to MES/ERP
    • Reduce downtime by up to 50%





Find out what's special



Existing Data

We initially extract knowledge from existing machine control data and supplement sensors only where needed.

Portability of Services

For flexible implementation of performant data analytics infrastructures for various environments and conditions.

System Independence

Flexibility and expandibility of our solution leads to high independence from manufacturers and technical applications.

Fusion of Data Streams

For structurized and continuous acquisition of heterogeneous data streams from various interfaces.

Generic Algorithms

For data driven training of interpretable digital process twins to structurize complex and heterogeneous data streams.

Complexity Reduction

Our approach provides the analysis under a unified view of machines, processes and the product.

Platform-Agnostic

Our Dockerized Services are implementable on various analytics platform solutions and data infrastructures.


Team Fine|alyze



Who we are

The High-Tech Startup Fine|alyze is a Spinoff Initiative from the Institute of Mechatronic Systems at the Gottfried Wilhelm Leibniz University Hannover.

Emerged from the Research Group for Integrated Systems and Machine Learning, it is now our Mission to Optimize Automated Production with Application of our Innovative and High Performant Digitalization and Data Analytics solutions.

Our Customers benefit from our Broad Technological and Methodical Expertise, Agile and Solution-Oriented Approaches as well as Extensive Experience from Research and Transfer Projects.



News


  • Fine|alyze @ Hafven Smart City Hub Batch#2

  • Fine|alyze @ NBank - Network Meeting for Business Angels and Investors

    Fine|alyze @ NBank - Network Meeting for Business Angels and Investors

  • Fine|alyze is Part of Batch#2 in the Hafven Smart City Hub

    Fine|alyze is Part of Batch#2 in the Hafven Smart City Hub

  • Fine|alyze is part of the 1st Tetramax Entrepreneurial TTX

    Fine|alyze is part of the 1st Tetramax Entrepreneurial TTX

  • Fine|alyze on Public Transport Passenger TV during #HM19

    Fine|alyze on Public Transport Passenger TV during #HM19

  • Fine|alyze wins @ FUTUR X PitchBoXing 2019.1

    Fine|alyze wins @ FUTUR X PitchBoXing 2019.1

  • Fine|alyze wins Second Prize @ the InnoEU Global Innovation Summit – Startup Pitch Competition

    Fine|alyze wins Second Prize @ the InnoEU Global Innovation Summit – Startup Pitch Competition

  • Futur X PitchBoXing

  • Hafven Smart City Hub – Startup Ceremony Batch#2

    Meet us personally

    finealyze
    IIP-Ecosphere Workshop "KI in der Produktion: Herausforderungen und Potentiale für KMU" @ Hafven (09:00)  

    more info: IIP-Ecosphere

    June 3, 2019
    finealyze
    Pitch @ NBank - Netzwerktreffen für Business Angels und Investoren (16:30)  

    more info: NBank 

    May 14, 2019
    finealyze
    Arbeitgeberforum 2019 - Niedersachsenmetall (10:00)  


    May 9, 2019
    finealyze
    Pitch @ NBank: Smarte Lösungen aus Niedersachsen (10:30)  

    Venue: tech transfer - Forum @ HANNOVER MESSE (Halle 2, Stand C02)

    more info: NBank

    April 5, 2019
    finealyze
    Startup Meetup #13 @ Hannover Messe 2019 (18:00)  

    more info: Xing Events

    April 1, 2019
    finealyze
    Demo @ Hannover Messe 2019 (09:00)  

    Model Factory Demonstration with Volkswagen Nutzfahrzeuge @ 5G-Arena (Halle 16, Stand D38)

     

    more info: Hannover Messe 5G-Arena

    April 1, 2019



    finealyze
    • Appelstraße 11a, 30167 Hannover

    • +49 511 762 4121

    • info@finealyze.com

    • http://www.finealyze.com

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    • mzh
    • imes
    • hafven
    • nbank
    • starting business
    • leibniz universität hannover
    • acatech - Plattform Lernende Systeme
    • AMA - Applied Machine learning Academy
    • Tetramax -TTX
    • venture villa
    • l3s Research Center