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Our Latest Insights
Articles, webinars, videos and case studies on asset performance management: control valves, pumps and heat exchangers, alarm management, predictive maintenance and the practical use of AI in industrial operations.
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SMITZH ‘OI4 Demonstrator’ Project
Following the OI4 guidelines, a digital ecosystem for APM applications was built with plug-and-play, generic access to industrial asset data.
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4 Secrets to Make Smart Devices Work Successfully in Industry
APM Studio embedded in the device provides diagnostic, prognostic and advanced control functions on streaming data for the FOCUS-1 smart…
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The Myth of Predictive Maintenance?
Is Predictive Maintenance with Machine Learning (ML), Artificial Intelligence (AI) and analysis on streaming data revolutionizing maintenance and Industry 4.0?
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Wie schließt man die „Lücke“ zwischen den Sensordaten und der Instandhaltung?
Praxisbeispiele, wie sich Arbeitsprozesse in der Instandhaltung mit Datenanalyse, Machine Learning und IoT automatisieren lassen.
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FAQ Data Science for predictive maintenance
Data science structures asset data into valuable insight for predictive maintenance. KNIME is a simple tool for building and deploying…
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APM Studio Integrated With PTC ThingWorx
APM Studio’s integration with PTC ThingWorx brings real-time condition monitoring and predictive maintenance to your asset base.
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Workshop – Data Exploration and Analytics
Part of the Technohub programme: master classes and workshops on big data and predictive analytics, with hands-on steam turbine data…
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An Introduction to Applying Artificial Intelligence in Operations and Maintenance
What artificial intelligence is and how to apply it embedded in your devices or at the edge, deploying real-time predictive…
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Mythos Predictive Maintenance?
Daten, neue Sensoren und KI sollen die Instandhaltung revolutionieren. Wir schlagen die Brücke zwischen Hype und Realität.
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The Power of Bow Ties
The BowTie method explained for maintenance: what it is, how to apply it, and a step-by-step example, plus the truth…
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Wie berechnen Anlagenbetreiber Business Cases für Data Driven Services?
Gibt es einen Business Case? Die entscheidende Frage bei der Einführung neuer Tools wie Predictive Maintenance oder virtuellen Sensoren.
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Digital Twins for Data Driven Maintenance?
Apply digital twin technology for data-driven maintenance: create digital copies of your assets and run real-time predictive analytics securely.
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Automation with Cobots!
UReason and its Technohub partners run workshops on big data, IoT and AI in manufacturing. This one introduces cobot technology…
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Wie Daten die Instandhaltung planbarer machen?
Wie führende Unternehmen Predictive Analytics pilotieren und implementieren, um Stillstände zu vermeiden und die Produktionskapazität zu erhöhen.
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Analytical and Machine Learning Models on Live Streaming Data
Machine learning in maintenance: the main algorithms and tools, exchanging models produced by data mining, and model deployment and management.
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Was bedeuten Edge Computer für die Wartung und Instandhaltung?
Edge Computing ermöglicht die Analyse von Daten in Echtzeit nahe an Maschinen, Instrumenten und Armaturen – und optimiert so die…
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AI, ML & LLMs, Alarms & Diagnostics, APM Studio & Platform, Data & Connectivity, Heat Exchangers & Process, Pumps & Rotating EquipmentUnderstanding Time Series: ARMA – Auto Regressive Moving Average
Learn how the ARMA (Auto Regressive Moving Average) model can predict anomalies in process data and raise alarms before failures…
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Webinar: Technology, Processes and Organization: kickstart your asset performance improvements
UReason, MaxGrip and Ultimo explain how you can implement and utilize real-time, condition-based and predictive maintenance solutions in an organization.
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Smoothing your Predictions with Splines
See how pump flow rate prediction with smoothing splines detects clogging early and supports predictive maintenance.
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Open Source Data?!
Open source data sets can boost predictive maintenance and condition monitoring. See top repositories and examples.
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Hands-on Workshop: Data Analytics
A hands-on workshop: data exploration in Jupyter notebooks, AI classification of equipment dysfunction with KNIME, and deployment in APM Studio.
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Ultimo and UReason Close the Loop From Asset Data to Automatic Work Order Generation
Ultimo and UReason integrate to provide real-time asset condition monitoring, predictive and prescriptive maintenance capabilities.
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Condition Monitoring als Grundlage für ein digitales Service-Geschäftsmodell?
Die kontinuierliche Zustandsüberwachung senkt Kosten und steigert die Verfügbarkeit – und eröffnet Herstellern neue digitale Services.
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PMML: What Is It and Why Should You Care About It?
Predictive Model Markup Language (PMML) makes it easier to move machine learning models between systems and into production.
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Dashboards of critical assets from real-time data
Create Drag & Drop dashboards in minutes that visualise asset information and Key Performance Indicators (KPI) on live data to…
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Predictive Maintenance Online Knowledge Days
Data-driven maintenance, automated work-order generation to CMMS such as Ultimo, Maximo and SAP, and the AI, cloud and edge technologies…
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Einsatz von virtuellen Sensoren auf allen Ebenen der Automatisierungspyramide
UReason entwickelt mit Kunden virtuelle Sensoren für Messinstrumente, Armaturen, Edge-Anwendungen und Cloud-Plattformen.