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Forging a path towards predictive asset performance management

Home Engineering Automation & Control Forging a path towards predictive asset performance management

IN today’s industrial processes, assets are fundamental to keeping the production cycle going, avoiding unplanned shutdowns, and ensuring strategic business outcomes. Managing and maintaining these assets dictates the efficiency of industrial operations and meeting customer needs. With digitalisation, asset performance management (APM) is moving away from traditional time-based maintenance approaches, which can lead to high costs, low output, unplanned work, safety risks, environmental damage, regulatory issues and energy inefficiencies, says Charles Blackbeard, business development manager, ABB Ability Digital Solutions.

The ABB Ability Genix APM suite is a comprehensive asset management platform powered by artificial intelligence (AI), the industrial internet of things (IIoT), and model-based predictive data analytics. This enables a paradigm shift towards a more proactive and predictive asset management approach.

Maximising performance, minimising failures

Data is at the heart of APM. Access to data on operational systems (OT), information technology (IT), and engineering technology (ET) is helping industries such as oil and gas, refining, and power generation to monitor their critical assets proactively.

By applying this data-driven approach, the Genix APM suite leverages advanced analytics and predictive algorithms and provides insights into asset health, identifies potential issues or failures, and recommends proactive measures to avert unplanned downtime – thereby establishing a reliability culture.

Furthermore, it reduces maintenance costs and wastage, optimises energy usage, and helps enterprises meet their business and sustainability targets. Moreover, it engenders greater confidence among plant operators to act proactively based on actionable insights to avoid production incidents.

Lack of visibility across assets can give rise to risk exposure and potential costs. The Genix APM suite begins with an initial event – such as a process upset or asset degradation – which triggers the implementation of protective measures to prevent further failures. These measures start with rules-based monitoring, ranging from simple sensor alerts to more complex conditional statements based on multiple sensors.

Genix APM also includes various risk and predictive analysis models. These include predictive systems and analytics, which integrates technologies into a unified APM solution for the process automation industry while facilitating predictive maintenance by contextualising OT, ET, and IT data.

Furthermore, Genix APM goes beyond routine-based predicted maintenance schedules and equipment condition monitoring while giving role-specific actionable insights, thereby helping tactical decision making. Efficient asset maintenance based on real-time data reduces maintenance costs by more than 15 percent and downtime in industrial contexts by more than five percent.

Genix APM plays a key role in ensuring safety and helping reduce energy usage by providing data on asset utilisation and enabling plant operators to prioritise and optimise productivity. It has been implemented across various industries worldwide.

Norwegian oil and gas producer OKEA has a Memorandum of Understanding (MoU) with ABB to deploy digital solutions that help drive smarter, safer and sustainable operations. As part of the MoU, signed in 2019, OKEA has been leveraging ABB’s digital offerings, including APM.

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