FEATURE Sensors & Industry 4.0
BRIDGING THE DATA/REALITY GAP BRIDGING THE GAP
continuously for years or decades. Cameras deployed in these settings must withstand temperature extremes, dust, vibration and electrical noise. Secure device communications and controlled access should be standard. Update procedures must align with maintenance windows and OT policies. Integration architecture also matters.
A
s operations generate greater volumes of sensor data, putting data into context becomes critical. While PLCs track timing and
sensors measure parameters, the reality of remains unseen. Network video bridges digital record keeping and production reality. Beyond surveillance, cameras provide a structured data layer within industrial architectures – an observational source that supports safety, diagnostics and operational
parameter drift at one stage of production may not show up as a problem until several operations downstream. Control data cannot explain whether material presentation caused a misalignment, whether debris obstructed a sensor, or whether an operator action initiated the sequence.
When video is time-synchronised with PLC timestamps, investigations accelerate. If defects appear, tracing handling conditions backward is faster when visual evidence is tied to operational logs. Near-misses that triggered no formal alert can be reviewed and understood, informing preventive adjustments before they become incidents. The European Machinery Regulation (EU) 2023/1230, which applies from 20 January 2027, explicitly addresses risks introduced by software, connectivity and AI-enabled functionality in machinery. Manufacturers must assess digital components across the entire machinery lifecycle, including
automationmagazine.co.uk
foreseeable misuse and security threats. Meeting these requirements demands traceability and the ability to show that machines operate predictably and safely under real-world conditions. Video provides evidence that control data alone cannot. When an emergency stop activates or a safety interlock trips, synchronised footage shows what physically preceded the event. If a collaborative robot slows due to proximity detection, this can be assessed visually. Organisations working through regulatory demonstration of due diligence, but it does not validation. Video supplements those foundations cannot.
As manufacturers face skills shortages, applying engineering expertise remotely without compromising diagnostic quality becomes valuable. A remote team reviewing visual and process data can assess misalignment, leaks and visits. Video helps expertise scale across plants and regions in ways that were previously impractical. Equipment manufacturers are embedding cameras within machinery, enabling visual diagnostics alongside metrics to support condition- based maintenance and improve transparency. This keeps OEMs engaged with asset performance across the machine lifecycle. of industrial networks. These environments are safety-critical, subject to formalised change management and expected to operate
Video data must interface cleanly with industrial protocols, analytics platforms and management systems, minimising the need for bespoke integration. Open standards support interoperability, enabling video to function as another node on the network. Integrating video is a process, not an event. It can be built into new installations – BMW’s iFACTORY initiative integrates quality assurance cameras into production processes and manages them through a dedicated platform, providing operational data that informs quality management and continuous improvement.
In most facilities, change occurs through
targeted upgrades that deliver measurable synchronising cameras with alarm systems to improve incident review. From there, visual data integrates into root-cause analysis analytics. Each step builds on what is in place. In high-throughput environments
where downtime has direct commercial consequences, even small improvements in diagnostic speed and accuracy are measurable. Integration must be staged carefully during planned downtime.
Network video is now an established industrial data source. Managed with the same discipline as any other control technology component, it becomes part of the permanent operational record. Visual data provides the context that supports the shift from reactive troubleshooting to predictive operations, where understanding the full sequence of events leads to better decisions before problems occur.
Axis Communications
www.axis.com/en-gb/solutions/industrial
Automation | April 2026 27
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40
