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Browse by topic Maintenance Strategy
138Control Valves88APM Studio & Platform86AI, ML & LLMs44Servitization & Business Case37FMEA, Bowtie & Risk34Pumps & Rotating Equipment33Alarms & Diagnostics32Energy & Sustainability29Digital Twin, DPP & AAS27Company News11P&ID & Process Insights6Heat Exchangers & Process5
Upgrading an old plant to Industry 4.0 need not mean heavy investment. Practical Industry 4.0 prevents shutdowns using the data you already have.
Is All the IIoT and Industry 4.0 Hype Real? Using Practical Industry 4.0 Read Post »
Get to know a quick, technician- and operator-friendly way to figure out which valves and actuators are going to fail soon and prepare beforehand.
It is Turnaround Time! Read Post »
Start with Practical Industry 4.0 by identifying the bad actors that cause troubles in your factory and using a specialized app to solve this.
The Industry 4.0 Disconnect Read Post »
This article explains the concept of Digital Twin, what a Digital consists of and how you can implement it for solving operational problems.
How Creating a Digital Twin Helps Plants Run Better Read Post »
Institutional knowledge leaves with retiring workers. Emerging technologies let plants substitute for the expertise that has walked out the door.
The People Side: Retaining Institutional Knowledge Read Post »
How do you go from many stand-alone pilots to one organisation-wide data-driven maintenance strategy? The challenge Dutch water company Vitens faced.
Predictive Maintenance: Drinking Water Company Vitens Shares Learnings Read Post »
The article discusses the Problems of Aging Plants, what to do with multiple generations of systems and assets and how to get to Industry 4.0
Digitization and Asset Management in a Brownfield Plant Read Post »
Asset Performance Management helps enterprises stay profitable and agile: start with an inventory of plant assets and smart instrumentation.
Agility and Industry 4.0 Read Post »
Regulation for asset owners is increasing, and so is risk. Handled properly, regulation can drive more production, more profit and more uptime.
Regulation and Risk Read Post »
Ein Team von Kuka und UReason zeigt im Rahmen der Open Industry 4.0 Alliance, wie schnell sich messbare Ergebnisse erzielen lassen.
IIoT Projekt in 3 Monaten: Produktion im mannlosen Betrieb um 10% gesteigert Read Post »
In 20 Minute erklären wir, warum „Smart Data“ besser sind als „Big Data“ und wie man ohne Daten in 3 Monaten robuste Algorithmen entwickeln kann.
Industrie 4.0 – Keine Daten? Kein Problem! Read Post »
Edge computing analyses asset data close to the source – valuable for both asset owners and equipment manufacturers building APM solutions.
Edge Computing: Why Should You Care? Read Post »
How the FOCUS-1 smart valve with APM Studio embedded provides diagnostic, prognostic and autonomous control functions to avoid unexpected failures.
How Smart Machines Reduce Maintenance Costs, Energy Usage and Outages? Read Post »
Webinar: the project flow of an APM project, from selecting critical assets and collecting historian data to deploying predictive maintenance.
How to Turn Data from your Process Historian into Value Read Post »
Industrie 4.0, IIoT und KI bieten erhebliches Potenzial. Erfahren Sie, welche Fehler Sie bei Ihren IIoT-Projekten vermeiden können.
Instandhaltung 4.0 Read Post »
Ultimo und UReason zeigen, wie man Maschinendaten für die Instandhaltungsplanung nutzt: weniger Kosten bei höherer Verfügbarkeit der Anlagen.
IoT in der Instandhaltung: Maschinendaten für die Planung nutzten Read Post »
A Technohub workshop on streaming intelligence: a hands-on exploration and analysis of steam turbine data to get valuable insights.
Workshop – Data Exploration and Analytics Read Post »
Praxisbeispiele, wie sich Arbeitsprozesse in der Instandhaltung mit Datenanalyse, Machine Learning und IoT automatisieren lassen.
Wie schließt man die „Lücke“ zwischen den Sensordaten und der Instandhaltung? Read Post »
Data science structures asset data into valuable insight for predictive maintenance. KNIME is a simple tool for building and deploying AI models.
FAQ Data Science for predictive maintenance Read Post »
APM Studio’s integration with PTC ThingWorx brings real-time condition monitoring and predictive maintenance to your asset base.
APM Studio Integrated With PTC ThingWorx Read Post »
Part of the Technohub programme: master classes and workshops on big data and predictive analytics, with hands-on steam turbine data analysis.
Workshop – Data Exploration and Analytics Read Post »
Machine learning in maintenance: the main algorithms and tools, exchanging models produced by data mining, and model deployment and management.
Analytical and Machine Learning Models on Live Streaming Data Read Post »
Edge Computing ermöglicht die Analyse von Daten in Echtzeit nahe an Maschinen, Instrumenten und Armaturen – und optimiert so die Instandhaltung.
Was bedeuten Edge Computer für die Wartung und Instandhaltung? Read Post »
Learn how the ARMA (Auto Regressive Moving Average) model can predict anomalies in process data and raise alarms before failures occur.
Understanding Time Series: ARMA – Auto Regressive Moving Average Read Post »
A hands-on workshop: data exploration in Jupyter notebooks, AI classification of equipment dysfunction with KNIME, and deployment in APM Studio.
Hands-on Workshop: Data Analytics Read Post »
Data-driven maintenance, automated work-order generation to CMMS such as Ultimo, Maximo and SAP, and the AI, cloud and edge technologies behind it.
Predictive Maintenance Online Knowledge Days Read Post »
UReason entwickelt mit Kunden virtuelle Sensoren für Messinstrumente, Armaturen, Edge-Anwendungen und Cloud-Plattformen.
Einsatz von virtuellen Sensoren auf allen Ebenen der Automatisierungspyramide Read Post »
Soft sensors are AI models that calculate parameters you cannot measure directly, deployable on-premise, embedded or in the cloud.
Using Soft Sensors to Monitor Critical Process Measurements Read Post »
A time-series data set recorded by UReason and the Flow Center of Excellence from the XCaliber Flow Loop’s Schneider SCADA system.
Data Sets on the Xcaliber Flow Loop at the Flow Center of Excellence Read Post »
Discover how a soft sensor helps monitor critical process measurements and spot anomalies using real-time data and algorithms.
Monitoring Critical Process Measurements Using Soft Sensors Read Post »
Edge computing at the second level of the automation pyramid: how APM Studio analyses asset data at the edge without shipping high-frequency data.
Automation Pyramid: Control Level Infographic Read Post »
With the Bowtie method you can turn your existing FME(C)A and failure models into real-time cause consequence models that monitor asset failures.
How to do real-time, data driven, risk assessment on your asset base? Read Post »
What data you need to build real-time condition monitoring, and how to deploy AI and machine learning algorithms on streaming data.
Preventing Asset Outage with Historical Data Read Post »
With Krohne Altometer, Valk Welding, Damen Shipyards and others, UReason develops master classes on big data and predictive analytics.
Technohub Initiative Read Post »
UReason is now a corporate member of the Institute of Asset Management, raising awareness of data-driven asset management and its benefits.
UReason Joins the Institute of Asset Management Read Post »
Running predictive analytics on streaming data allows you to optimise process availability, detect equipment dysfunctions early and improve asset integrity.
Using Streaming Data from your Assets to Prevent Outages Read Post »
Where process historians fit in an APM project: selecting critical assets, choosing failure models and deploying predictive maintenance.
How to Turn Data from your Process Historian into Value Read Post »
How predictive models move from data mining into production, and what it takes to deploy and manage machine learning on live asset data.
Analytical and ML Models on Live Streaming Data Read Post »
Discover what Asset Performance Management means and how it reduces downtime with predictive and prescriptive insights.
Asset Performance Management: Explanation and Benefits Read Post »
Thinking of investing in predictive maintenance? Learn the ROI, risks, and how to choose the right assets.
Invest in Predictive Maintenance? Benefits and Risks of Investing in PdM Read Post »
UReason joined the OI4 Alliance to help OEMs and asset owners adopt Industry 4.0 through interoperable end-to-end reference frameworks.
UReason Joins the Open Industry 4.0 Alliance Read Post »
Explore 3 myths about data and AI in manufacturing that shape how teams approach data, decision-making, and smarter asset performance.
Three Myths About Manufacturing in the Times of Big Data and AI Read Post »
Discover how citizen data scientists are transforming IoT and CEP solutions using operational intelligence and real-time analytics.
Citizen Data Science – a Driver for Better IoT and CEP Solutions Read Post »
Start your CBM or PdM project with confidence. Learn how process, ambition, and leadership shape successful PoC or PoV outcomes.
Starting a CBM/PdM Project – Key Learnings Read Post »
Explore IoT Connectivity in IIoT Communication. Learn about SigFox, LoRaWAN, and key protocols for cross-border deployments.
IIoT Communication Readiness – What You Need to Know Read Post »
Explore how the Industrial Internet of Things in manufacturing enhances efficiency, reduces downtime, and improves asset performance.
The Industrial Internet of Things – Hype or Reality? Read Post »
