OTTAWA, ON - Gastops is pleased to announce that it has been selected by the U.S. Naval Sea Systems Command (NAVSEA) to provide a Propulsion System Dynamic Response Analysis (PSDRA) for the U.S. Coast Guard Cutter POLAR STAR.
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ABB Ability™ Condition Monitoring for belts collects and tracks data from conveyor belts to provide real time information about the health of the equipment, enabling planned and timely maintenance
ZURICH, SWITZERLAND – ABB has launched ABB Ability™ Condition Monitoring for belts, an advanced digital service to enable mine operators to track speed, misalignment, damage, thickness and wear, slippage and temperature of conveyor belts in real time.
New hydrogen detector samples transformer oil in real time, equipping utilities with more health information for faster, more confident decisions
MARLBOROUGH, MA -- Doble Engineering Company, a leader in power grid diagnostic solutions and subsidiary of ESCO Technologies Inc., today announced the release of Calisto™ H1. The new hydrogen detector takes real-time measurements for quick intervention against faults and gives power and utility teams the flexibility to monitor a greater number of assets more cost-effectively.
A recent acquisition of PRUFTECHNIK just made sense to Fluke and the industry. This integration allowed the transition of focus to connected reliability and Fluke Reliability Solutions.
Direct Access to Secure and Actionable Information with i-ALERT Can Reduce Downtime and Extend Machine Health
SENECA FALLS, N.Y. – ITT Inc.’s (NYSE: ITT) i-ALERT brand is adding a new best-in-class automated machine health diagnostics offering to its portfolio, a game-changing expansion of its wireless condition monitoring capabilities widely used by oil & gas, chemical, power, and general industries.
For the last 40 to 50 years, the industry standard to monitor bearing wear or machine problems on the most process critical and expensive equipment in each plant has been the proximity probe. A new revolutionary Insight Force Detection Sensor creates a cost-effective and easy-to-install alternative.
When it comes to the reliability of equipment in process facilities, it is imperative that operators, managers, and maintenance teams have a clear picture of each machine’s health in real-time. A
This session will share case histories and lesson learned from deploying artificial intelligence (AI) and Internet of Things (IoT) condition monitoring systems in coal and gas fired power plants.
As the North American oil and gas infrastructure ages, changes made to facilities during their lifetime may not have been transferred to the official recorded drawings of the facilities.
A new generation of point artificial intelligence (AI) solutions will prove themselves within the next year. They’ll build new trust, urgency and an understanding of what AI actually is, and show just how much AI can deliver.
If you work for an asset intensive organization and your role involves ensuring value from assets, you are unlikely to organize the world by software applications as software marketing professionals or software analysts’ do in order to describe these applications and functions to chief information officers, IT leaders or other chief officers.
In manufacturing, a smart plant refers to a connected digital factory. However, when you look inside a typical plant today, you often see older infrastructure and assets. Common challenges that prevent manufacturers from achieving smart, fully connected plants can range from location – remote facilities sometimes without even basic Internet service or low connectivity – to issues of older assets that aren’t inherently IIoT-enabled. In the industrial world, these environments lead to stranded assets and up to 40 percent of a plant’s assets fall into this category.
The modern transformation of the logistics outlook increasingly changes the world and sets new tasks in the development of information technologies for production management and infrastructure operation.
Steam systems are vital to the smooth operation of so many manufacturing plants and other facilities. Numerous components are at work to ensure this smooth operation, but none more important than steam traps. Yet, despite their critical function, the majority of plants rely on time- and labor-intensive manual inspections. Yet, with the emergence of industrial Internet technology, steam traps make ideal candidates for automated sensing technology.
A call about a line outage or a message from an operator that “something’s wrong” is not a good start to the day. Early warning signs are there to be found. However, maintenance engineers can’t be everywhere at once. Time between data rounds is when something can go wrong, and some equipment isn’t even on a data collection route.
Many experienced maintenance professionals are at or near retirement age. With fewer replacements on the horizon, manufacturers are increasingly looking to industrial technology to maximize worker productivity to unlock capacity and improve overall equipment effectiveness (OEE). Better uptime starts with better data. These four technologies help provide better data quality and access to the teams that keep plants up and running.
To reduce unplanned downtime for a leading Fortune 500 pharmaceutical client, Cushman & Wakefield (C&W) Services moved from a traditional route based condition monitoring program to a wireless and artificial intelligence (AI) based predictive maintenance (PdM) program. The shift in technology not only led to reduced unplanned downtime, but also a better utilization of resources and a deeper understanding of asset condition. Here’s how C&W Services approached the challenges and arrived at solutions.