Inspection professionals can quickly detect faults and issues to prevent downtime and extend equipment life. (Image source: Flir)

Flir, a Teledyne Technologies company, has launched the C8 latest-generation thermal imaging camera, providing enhanced image quality, higher accuracy, improved sensitivity, andf advanced reporting templates within Flir Ignite Pro

Traditional thermal inspections can be slow, unclear, and hard to document, relying on manual processes that risk overlooking critical issues, leading to higher maintenance costs, delayed repairs, and reduced productivity. The rugged, easy to use Flir C8 addresses these challenges with powerful, high-resolution thermography, ensuring accurate, efficient, standardised inspections. In addition, technicians can integrate FLIR Ignite Pro cloud connectivity and new advanced reporting templates that streamline workflows and save time as well as supporting easy collaboration.

New capabilities for the Flir C8 include 320 x 240 thermal resolution and 35° horizontal field of view to increase the number of pixels. Used in combination with Flir’s patented MSX® detail enhancement technology, it provides clear and accurate imaging, supporting faster fault and anomaly detection for more accurate diagnostics. For example, in electrical and mechanical maintenance activities Inspection professionals can quickly detect faults and issues in factories, process plants, commercial facilities, and utilities to prevent downtime and extend equipment life.

“Users of our C8 can enjoy up to 40-50% quicker inspections, helping to cut labour and downtime costs,” revealed John Gould, Director – Global Business Development – Condition Monitoring. “Identifying faults faster and acting sooner reduces expensive outages and unplanned repairs, while confidence in consistent, reliable results is assured thanks to high resolution and high thermal sensitivity. Furthermore, isotherm alarms instantly highlight when temperatures cross set limits, helping users quickly identify potential issues”.

The camera also provides increased accuracy of ±2°C @ 0°C to a newly elevated 450°C maximum object temperature, higher sensitivity (NETD <50 mk) and streaming over USB.

DUG Elastic MP-FWI Imaging produces superior results compared with conventional processing workflows. (Image source: DUG)

When it comes to processing and imaging land seismic data, DUG Elastic MP-FWI Imaging produces far superior results!

Land seismic data, such as the example above, can often exhibit strong elastic effects that violate the assumptions of acoustic imaging. This desert setting has geological complexity both in the near-surface and at the target depth, including high-impedance carbonates. Conventional pre-processing workflows are non-trivial, especially on land data, where stages such as demultiple often require complex modelling and adaptive subtraction workflows.

The traditional processing workflow involves the testing and application of dozens of steps such as deghosting, designature, demultiple and regularisation, which are all designed to overcome the limitations of conventional imaging. These workflows are complex, subjective, and very time-consuming due to their serial nature and they rely on many assumptions and simplifications. All of these issues impact the output data quality. The resulting, primary-only data then undergoes a similarly complex model-building workflow to derive an estimate of the subsurface velocity, which is used for depth imaging. Post-migration processing is performed before the pre-stack reflectivity undergoes another workflow to derive rock properties that feed into quantitative interpretation, also relying on simplifications of the actual physics. As a result of these workflows, projects can take many months to years to complete.

Significantly better illumination and event continuity is obvious when comparing the sections in the figure, thanks to DUG Elastic MP-FWI Imaging of the full wavefield — that includes interbed multiples. Incredible near-surface detail has been resolved, as can be seen on the shallow depth-slices to the right. Subtle structural and stratigraphic features that were simply not imaged with a conventional processing and imaging workflow have now been resolved.

A complete replacement for traditional processing and imaging workflows is no longer a stretch of the imagination. Visit dug.com to see more outstanding DUG Elastic MP-FWI Imaging results.

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DUG Elastic MP-FWI Imaging leaps entire workflows in a single bound, delivering unsurpassed imaging and high-resolution rock properties from field-data input. Superior outputs, in a flash!

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Borouge has set a target of generating US$575mn in value by 2025. (Image source: Borogue)

Borouge is working with Yokogawa UAE Industry to test AI-powered autonomous control room operations at its Ruwais facility in Abu Dhabi

The proof-of-concept will use advanced AI tools to analyse plant data, detect patterns, and predict anomalies, allowing faster corrective actions and reducing the risk of unplanned shutdowns. It will also assess how autonomous control could improve efficiency and optimise overall performance.

Borouge has set a target of generating US$575mn in value by 2025 through technology and AI-driven initiatives. By the end of Q2, the company had already achieved US$307mn.

At Ruwais, Yokogawa is trialling AI operations at the Borouge 3 Cracker, while Honeywell is running a parallel project at the Borouge 2 Cracker. Together, the initiatives aim to deliver the petrochemical industry’s first fully autonomous AI-driven control room.

Hazeem Sultan Al Suwaidi, chief executive officer of Borouge, said, "As we progress our AI, Digitalisation and Technology (AIDT) transformation programme, our goal is to deliver an AI-powered autonomous control room at what will be the single largest petrochemical site in the world, enabling Borouge to accelerate growth and create lasting value for shareholders.”

Norinao Sato, president and CEO of Yokogawa Middle East & Africa, commented, “An AI-powered control room is a next generation operational hub that leverages artificial intelligence, machine learning and automation to optimise decision-making, automate processes, enhance safety and boost efficiency sustainably, transforming the control room from a reactive monitoring station to a proactive, intelligent command centre.”

Kriti Sharma, CEO IFS Nexus Black. (Image source: IFS)

The global adoption of Industrial AI is accelerating rapidly, and is set to double from 32% to 59% within 12 months, according to a recent study from IFS, a leading provider of Industrial AI Sofware

However, according to The IFS Invisible Revolution Study 2025*, which surveyed over 1,700 senior decision makers at industrial enterprises globally, organisations are not fully prepared for its full implementation, creating what IFS calls the ‘AI Execution Gap,’ with 52% of senior leaders saying their management teams don’t fully understand AI, and 99% of global workforces requiring major reskilling to scale AI impact.

“AI is a core driver of business performance, it’s time to plug the AI Execution Gap – bring people, process and product together to deliver tangible outcomes,” said Kriti Sharma, CEO, IFS Nexus Black. “The pace of adoption is inspiring, but the next big unlock will come from scaling trust, strategy, and talent. Industrial AI is a powerful force for good, and we’re in a moment of opportunity: those who move fast will lead the next decade of industry.”

More than half of business leaders (53%) admit their organisation still lacks a clear AI strategy, yet the study clearly highlights the benefits available to companies that embrace AI. 70% of businesses report better-than-expected ROI from their AI investments, and on average 88% say AI has already improved profitability. Training and upskilling will be key to ensuring that industrial companies remain relevant.

Despite growing confidence in AI’s potential, there are still issues with trust. Only 29% of global leaders are comfortable allowing AI to make strategic decisions autonomously, while 68% say a human must still confirm or approve AI-generated outputs. Concerns about bias also persist. 65% of global leaders support the creation of an independent, international AI regulatory body to help close the trust gap.

Business model shift

The report highlights how Industrial AI is changing how businesses are run, automating maintenance, predicting disruptions, optimising supply chains, and facilitating intelligent decision-making across field service, asset management, and manufacturing. 54% of global organisations are using automation AI, while 45% are deploying predictive AI. Already, 35% are experimenting with Agentic AI, capable of autonomously executing decisions across workflows. Traditional business models are being influenced by AI with 77% of global leaders saying it is accelerating servitisation, the evolution from product sales to outcome-based services, where businesses deliver uptime, performance, and continuous value instead of just physical goods.

Sharma continued, “Industrial AI is moving into real-time, decision-grade intelligence embedded across the enterprise. It’s already securely automating the complex, predicting the unexpected, and powering new service-led business models. This is about shifting from tasks to transformation, and the organisations who embrace that shift will lead the next industrial chapter.”