The Vision AI Center of Excellence Blueprint
A playbook for turning vision AI into an owned, scalable capability.
Add a continuous measurement layer to every belt with vision AI for aggregate size and gradation analysis. Built for the operations where the sieve test that certifies a product runs hours after the crusher started drifting, a worn screen panel lets oversize into a finished pile all afternoon, or the gradation that left the plant isn't the gradation that arrived at the job. Whether you're running a quarry and crushing plant, a sand and gravel operation, a ready-mix or asphalt plant, or the mining operation upstream, Roboflow measures the material actually moving through your plant, continuously, with records tied to product, belt, and time.
Belt-Level Size and Gradation Monitoring:
Crushers, Screens, and Process Drift:
Stockpiles, Load-Out, and Systems Integration:
Bring intelligence to every belt today. Stop gradation problems from becoming requalified stockpiles, reblended product, or rejected loads.
What is aggregate size and gradation analysis with Vision AI?
Aggregate size and gradation analysis with vision AI uses computer vision models to measure particle size distribution from imagery of material on belts, in stockpiles, and at load-out. Models trained on your actual products measure size continuously as material moves through the plant, track the gradation curve against spec envelopes, and alert on oversize, excess fines, and drift, with records tied to product, belt, and time that correlate against your ASTM C136 sieve program.
Can Vision AI measure gradation when rock overlaps and the belt is dusty or wet?
A loaded belt is the hard case: particles overlapping and burying each other, dust coating everything, wet fines clumping, and the camera seeing only the surface of the material bed. Deep-learning models trained on your actual belts and products learn to measure through overlap and surface conditions, and the system is calibrated against your sieve results so its continuous readings track the numbers your lab produces. When conditions degrade past reliable measurement, the system flags the interval for review instead of guessing, so a dusty hour becomes a gap you know about rather than a number you can't trust.
Does it replace sieve testing for ASTM and DOT certification?
Sieve analysis under ASTM C136 remains how products are certified, and your lab program stays the system of record for spec compliance. Vision AI adds what sieves can't: continuous measurement of every belt between tests, so drift shows up in minutes instead of at the next sample, and the material a sieve test certifies matches the material that actually ran all shift. Correlation records between the vision measurements and your sieve results document how the two track together.
Can it integrate with our plant PLCs, SCADA, and load-out systems?
Yes. Roboflow Inference exposes a standard API and supports common industrial protocols, so size data and alerts flow into your existing systems: plant PLCs from Allen-Bradley and Siemens, SCADA and HMI platforms like Ignition and AVEVA, and load-out and ticketing systems, through REST, MQTT, OPC UA, and direct database writes. PLC-level integration can alert operators or adjust downstream handling the moment a product trends off spec, and every measurement carries product, belt, timestamp, and imagery, with a full record behind every shift.
