ADVERTISEMENT FEATURE Smart manufacturing
For manufacturers, the value of video analytics is clearest in three areas when context changes outcomes: quality, flow and safety
across its French production sites, monitoring automated and robotic processes for both defects and optimisation opportunities. Compact cameras monitor coffee jar filling stations, for example, allowing operators to remotely supervise the robots on the line and providing evidential footage for later analysis. For operations leaders, video is a
root-cause tool. When linked with production events, it allows teams to compare and understand the reasons for throughput changes, to see what has worked and what has not, and to make fair assessments about overall equipment effectiveness (OEE). Stoppages and repeated interventions get that all-important ‘why’. And for those pushing forward the digital transformation agenda, the extra value of linked, explained events may be all the argument that is required for video to be brought into the manufacturing technology stack.
Supporting PPE, near-miss and HSE reporting with AI-powered video monitoring Video’s place in safety is often underappreciated, but as manufacturers invest further in HSE systems, training and reporting, it is risky to leave safety visibility entirely to human operators. Even experienced operators cannot see every risk, every time. Near misses, PPE non-compliance, and ergonomic or zoning risks are easily missed by tired eyes, but video analytics both help bring these events to operators’ attention and aid in post-incident investigation. Steel manufacturer ArcelorMittal Belgium employs over 2,700 Axis network cameras across its seven high- risk production departments, allowing edge-based analytics to aid in production line monitoring and restricted area safety. These cameras, attached to machines and monitoring restricted zones, are not bespoke designs. The company’s AI functions can run on compatible Axis cameras and, in case of a malfunction or damage, engineers can replace a camera within an hour from on-site stock. By simply utilising video in the right way, HSE leaders get answers to their questions, and stronger evidence for intervention.
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Using existing camera infrastructure for video analytics
This does raise a practical question: can manufacturers use the cameras they already have? Sometimes they can. Sometimes they need to upgrade, reposition or supplement them. Analytics performance depends on whether the image is good enough for the job. Lighting, angle, resolution, frame rate and field of view all affect the result. Determining what works begins with an audit to determine what can already be seen, if the image quality is adequate, and which views support measurable operational problems.
The answers to those questions help shape the architecture. Edge analytics – that is, analytics that run directly on camera hardware – are useful where speed and resilience matter; cloud analytics can support broader analysis and comparison across sites. Many manufacturers will need a mix of both, with local detection at the line and central reporting for the business.
Connecting edge AI, cloud analytics and OT cybersecurity Integration is just as important. Video intelligence should not become just another isolated dashboard. To support smart manufacturing, analytics outputs need to feed the systems manufacturers already use, from MES and SCADA to ERP, historians, maintenance platforms and BI tools. Standard protocols such as Modbus and OPC UA can help bring camera-generated events into industrial automation and control environments. Cybersecurity and governance also need to be designed in from the start. Cameras
are connected devices, and they often sit close to sensitive operational systems. They must be managed with strict access control, lifecycle management, network segmentation and disciplined firmware updates, around rules concerning video retention and worker privacy.
Building the business case for smarter factory vision
The business case should begin with one operational problem. That might be defect escape cost, downtime per hour, time spent reviewing incidents, manual inspection effort, safety reporting workload or lost output from recurring stoppages. Once the baseline is clear, video intelligence can be judged against measurable improvement in quality, downtime and safety. Start with a problem that the ops team
already cares about. Prove the value in one line, process or site, then build an architecture that can extend across quality, throughput and safety without creating a disconnected technology estate. Factories already have eyes on their most important processes. The task now is to turn that view into usable operational intelligence that delivers clear ROI.
In focus: a spotlight on manufacturing
by Axis explores how video data can help manufacturers add context to operations, close the visibility gap, and support smarter, safer and more efficient manufacturing.
https://www.axis.com/ en-gb/explore/in-focus-manufacturing
Axis Communications
www.axis.com/en-gb/
Automation | July/August 2026 11
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