ABB’s Data Analytics Application Helps Industry Tackle Emissions, Making the Shift Towards Predictive Maintenance

Oct. 13, 2021
  • ABB Ability™ Genix Datalyzer is a cloud-based data analytics solution for fleet-wide management and optimization of emissions monitoring equipment in highly regulated industries like cement, steel, chemicals and power generation 
  • The new solution pre-empts plant failure and helps achieve emissions compliance, improving plant uptime and process safety 
  • Out-of-the-box actionable insights combined with self-service analytics help close the skills gap

Increased governmental and societal focus on emissions mean that industry is under ever greater pressure to increase the agility and reliability of emissions monitoring in real-time. ABB’s Datalyzer is designed to help customers respond to this challenge. The comprehensive, cloud-based modular application provides real-time status across a fleet of analyzers and plants. In doing so, it lowers ownership cost and reduces capital expenditure. 

Datalyzer collects data from emissions monitoring analyzers which is then routed to an on-site Edge device (Micro PC). The Edge device sends the relevant information up to Datalyzer which sits in the Microsoft Azure cloud. The application analyzes the data received transforming it into a concrete information for decision-making.    

The end user receives the information from Datalyzer across three different dashboard views. The first shows the fleet view, the second the plant view and the third a more detailed analyzer view. This combination provides both an ‘at a glance’ vision of the overall emission monitoring equipment status alongside valuable detailed asset parameters. Heatmaps of the installed base, historical trends and systems diagnostics are amongst the key parameters provided.

Datalyzer also offers QAL-3 assessment* and reporting, as well as event-based notifications by e-mail. Live analyzer process data together with value added insights and reports are amongst the application’s key features. Historical trends are tracked for up to five years, uncovering recurring patterns in the equipment performance and providing the platform for predictive maintenance. Adherence to cyber security standards prevent unauthorized access while ensuring data integrity.

Continuous gas analyzers such as ABB’s ACF5000 and ACF-NT analyzers are compatible with Datalyzer with extensions planned to include Advanced Optima and Easy Line in the first quarter of 2022.

Datalyzer forms a part of the ABB Ability™ Genix Industrial Analytics and AI suite. The platform provides data analytics and industrial AI applications as the next generation operational intelligence and insight. 

ABB (ABBN: SIX Swiss Ex) is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. By connecting software to its electrification, robotics, automation and motion portfolio, ABB pushes the boundaries of technology to drive performance to new levels. With a history of excellence stretching back more than 130 years, ABB’s success is driven by about 105,000 talented employees in over 100 countries. www.abb.com

ABB’s Process Automation business is a leader in automation, electrification and digitalization for the process and hybrid industries. We serve our customers with a broad portfolio of products, systems, and end-to-end solutions, including our # 1 distributed control system, software, and lifecycle services, industry-specific products as well as measurement and analytics, marine and turbocharging offerings. As the global #2 in the market, we build on our deep domain expertise, diverse team, and global footprint, and are dedicated to helping our customers increase competitiveness, improve their return on investment and run safe, smart, and sustainable operations. go.abb/processautomation

* Industry quality check specifically designed for Continuous Emissions Monitoring. The definition of a QAL3, according to the BS EN 14181:2004, is “a procedure to maintain and demonstrate the required quality of the measurement results during the normal operation of an AMS, by checking that the zero and span characteristics are consistent with those determined during QAL1”.

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