Machine signals and operator inputs provide essential context, but they don't always capture the full picture. Some inefficiencies remain invisible: unrecorded micro-stops, unreported manual interventions, or process deviations that go unnoticed.
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OEE from 20% to 62% in three months
What you get
Fabrico's Computer Vision module bridges this gap by adding a visual layer of intelligence. Cameras integrated with AI models continuously observe production activity, identifying events that machines or humans may miss.
Some stations give no machine signal at all, such as manual assembly or packing. There, AI cameras recognize and count output, so these stations get counts and OEE too.
Which option fits each machine, a PLC connection, an IoT device or a camera, is agreed with the Fabrico team before installation. One plant can mix all three.
Output and cycles. The camera counts parts and detects cycles where there is no machine signal.
Stops and micro-stops. Cameras detect when a line stands still, including a line that is switched on but not producing and short stops that nobody writes down.
Speed. By analyzing cycle patterns visually, cameras check whether production runs at the correct speed.
The moment of the stop. Footage is synchronized with machine and timeline data, so you can zoom in on the exact moment a line stopped and review the cause.
Cameras positioned above production lines continuously capture and synchronize footage with machine and timeline data. When an abnormal event occurs, users can immediately zoom in on the exact moment to review and validate the cause.
Trained AI models assist by suggesting likely stoppage reasons based on learned behavior patterns, transforming raw footage into actionable process insight.
Fabrico installs one or more industrial-grade cameras per production line, configured to cover key process areas. Using historical inputs from machines and operators, the system's machine-learning model learns to recognize recurring stoppage causes such as no material, jam, or broken part.
After the learning phase, the model classifies future events and fills data gaps, giving you a downtime record that gets more complete as the model learns.
By integrating visual evidence with OEE analytics, Fabrico helps manufacturers see downtime and process loss by cause. This gives Kaizen and other continuous improvement work the data an RCA needs: the video of a stop next to its machine data and the cause the operator tagged.
The result is an objective, data-driven foundation for continuous improvement.
See it on your own lines in a live demo.
Or start with a pilot, in four moves
A pilot site is operational in days, with minimal disruption to your teams.
Fits the systems, sites and standards you already have
Designed for manufacturing groups: integrated with your IT and OT, secure by design and simple enough for every shift.
Connects to ERP systems such as SAP and Oracle for full asset lifecycle management, and to the OT layer through PLCs, sensors and cameras.
ISO-certified company and solution, with role-based access control on every asset and financial record.
Standardize across plants, compare sites and meet group-level requirements from one central platform.
Being part of an international group, the requirements that come from group level to our production are already available in Fabrico, way ahead. With Fabrico, all our needs are covered and even exceeded.
Valentin Alexandrov · Transformation Manager, SchaefflerThe questions every plant asks first
Yes. Older machines get an IoT device with external sensors, and manual stations can use cameras that count output.
A pilot line is live in days. Training is live and on site, and support responds in under 2 hours.
Fabrico is a light MES: machine data collection, production monitoring, OEE and downtime analytics, and integration with SAP and other ERP systems. Job dispatching, BOMs, routings and genealogy stay in your ERP.
Certified to ISO/IEC 27001, ISO 9001 and ISO/IEC 20000-1, with EU hosting on AWS and role-based access.
No. A camera can measure stations that have no PLC or sensor, such as hand assembly or packing, by counting the output it sees.
Those counts feed the same OEE figures as the machines connected through a PLC.
A line can be switched on and still produce nothing, and a running signal will not show that as a stop. The camera sees it, even when nobody reports it.
Cycle patterns on the video also show whether the line runs at the correct speed.
The machine-learning model learns from historical inputs from machines and operators. It learns to recognize recurring causes such as no material, a jam or a broken part.
After the learning phase it classifies new events and fills data gaps, so the downtime record gets more complete over time.
Fabrico installs one or more industrial-grade cameras per production line, configured to cover the key process areas.
The number for each line is agreed with the Fabrico team after a review of your process and machines.
Plan on about one month to install the devices and connect the machines.
The full rollout, including data import, setup and on-site training, is complete in 3 to 4 months.
Fabrico holds ISO/IEC 27001 and hosts data on AWS in the EU, encrypted in transit and at rest and backed up daily.
A data processing agreement sets out how your data is handled under GDPR.
Find out what your losses cost. Recover the output you already own.
Most customers reach ROI in 3 months. See your own losses with a price tag in a live demo, or start with a focused pilot on one representative line.
More detail
Camera counts land on the same timeline as PLC and sensor data. Every source feeds the same OEE calculation, so lines connected in different ways can be compared side by side.
Fabrico connects vision data with operator activity, work orders and machine states. When a line stops, the footage, the machine record and the operator's reason sit in one place.
See how OEE software builds availability, performance and quality from this data, and how downtime tracking records every stop with its cause.
Each project starts with a review of your process and your machines. It shows which machines can be read through their PLC, which need an IoT device and which manual stations suit a camera.
Installing the devices and connecting the machines takes about one month. Full rollout across the lines you choose, with data import, setup and training, takes 3 to 4 months.
Training is given live and on site, and support responds by email or phone callback in under 2 hours. The machine monitoring page covers each connection option in detail.
Fabrico is certified to ISO/IEC 27001 and runs in the AWS EU region. Data is encrypted at rest and in transit, and backups run daily.
Data is processed under GDPR with a data processing agreement, and Cloudflare protects the service against DDoS attacks.
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