Industrial AI Platform | STATANLY
STATANLY INDUSTRIAL AI

AI platform for industry: quality, safety, processes and equipment

We connect machine vision, industrial cameras, sensors, SCADA/MES/ERP and AI models into a single production control loop. From defect detection and object counting to industrial safety, failure prediction and deviation management.

24/7continuous control of lines, zones, equipment and events without manual rounds
0.1 mmdefect, geometry, size and deviation control directly on the production line
MES / SCADAevents delivered to MES, SCADA, ERP, PLC, BI and rejection systems
RULremaining useful life, anomaly and equipment failure-risk prediction
Edge / Cloudlocal, cloud or hybrid data-processing architecture
APIintegrations with lines, cameras, sensors and enterprise systems
KEY DIRECTIONS

One scheme for different production tasks

The platform brings together typical industrial AI scenarios: product quality, safety, traceability, process control and equipment health.

Quality control and defect inspection

Surface defects, shape, dimensions, color, geometry, packaging, assembly and standard compliance.

Production processes and OEE

Object counting, cycle time, downtime, line load, operation queues and process-parameter deviations.

Industrial safety

PPE, hazardous zones, fire, smoke, falls, outsiders, vehicle movement and procedure violations.

Marking and traceability

OCR, QR, Data Matrix, labels, serial numbers, batches, completeness and product-linked events.

Equipment and predictive analytics

Anomalies in vibration, temperature, current, acoustics, mean time to failure and remaining resource.

Data and integrations

Unified event center, API, BI reports, MES/ERP/SCADA, PLC commands and automatic line response.

APPLICATION INDUSTRIES

AI for different industrial sectors

Industrial sites differ by raw materials, lines, equipment and risks. We adapt cameras, models, events and integrations for mining, food production, machinery, chemicals, energy, light and processing industries.

AI for mining

Mining and extraction

Granulometry, fractions, foreign objects, belts, vehicles, safety.

AI for food production

Food industry

Counting, color, shape, packaging, marking, line hygiene, rejection.

AI for processing industry

Processing industry

Metal, glass, films, fabrics, paper, cardboard and composites.

AI for machine building

Mechanical engineering

Dimensions, assembly, welding, completeness, marking, part defects.

AI for agribusiness

Agro-industry

Sorting, classification, raw materials, fractions, contamination, process zones.

AI for chemical and energy industries

Chemicals, cement and energy

Process parameters, safety, equipment, sensors, anomalies and maintenance.

READY SCENARIOS

Machine-vision and industrial AI solutions

Scenarios can be launched step by step: one line or one area first, then scale to a workshop, plant and enterprise network.

Industrial safety with machine vision

Industrial safety

PPE, helmets, vests, hazardous zones, fire, smoke, falls, smoking, vehicles and abnormal events.

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Defect detection and inspection

Quality control and defect inspection

Surface defects, cracks, scratches, contamination, damage, deviations in shape and quality.

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Granulometry on conveyor

Granulometric analysis

Fractional composition, particle size, distribution, oversize, fines and raw-material quality dynamics.

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Conveyor process automation

Conveyor automation

A single section for conveyor tasks: counting, defects, granulometry and line events.

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Foreign body detection

Foreign inclusions

Foreign objects in bulk materials, food products, raw material, packages and process flow.

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Size and geometry control

Dimensions, geometry and sorting

Measuring length, width, thickness, shape, position, gaps, holes and tolerances of parts.

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Marking reading and control

Marking, OCR and Data Matrix

Checking labels, QR, barcodes, serial numbers, date, batch and marking readability.

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Assembly quality control

Assembly and completeness control

Component presence, operation order, assembly correctness, fasteners, welding, seams and kits.

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Color identification and classification

Color and product classification

Classifying objects by color, shape, type, grade, quality class and visual attributes.

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Conveyor belt defect control

Conveyor belt condition control

Tears, cuts, wear, joints, coating damage, defect dynamics and event coordinates.

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Object counting on conveyor

Object counting on conveyor

Counting products, packages, parts and mixed flows, presence checks and counters sent to accounting systems.

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Packaging defect control

Packaging defect control

Tightness, completeness, label shift, damage, contamination, deformation and packaging defects.

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Predictive analytics for equipment

Equipment failure prediction

Anomalies, vibration, temperature, current, acoustics, RUL, MTBF, early wear signs and planned maintenance.

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In-line quality control, defectoscopy and automated inspection
QUALITY CONTROL

In-line quality control, defectoscopy and automated inspection

The system detects surface defects, geometry, color, completeness and marking directly on the line. The operator receives an event, frame, coordinates, defect class and action: pass, reject, stop a section or send the event to MES/SCADA.

  • surface defects: cracks, chips, scratches, stains, contamination and coating issues
  • geometry and dimensions: shape, thickness, diameter, position, gaps and tolerances
  • marking control: OCR, QR, DataMatrix, barcode, batch, date and print quality
  • completeness and assembly: presence of parts, fasteners, correct location and operations
  • color identification, sorting, product classes and automatic rejection
  • unified quality log with frames, statistics, defect reasons and shift reports
INDUSTRIAL SAFETY

Safety of people, equipment and hazardous zones

Video analytics monitors PPE, hazardous zones, vehicle movement, falls, smoke, fire and regulatory violations. Critical events are sent to responsible staff immediately, while frames are stored as evidence.

  • hard hats, vests, gloves, glasses, masks and other PPE
  • people in hazardous zones, under suspended loads, near machinery or in restricted areas
  • forklifts and special equipment, intersections of people and vehicle routes
  • falls, loss of consciousness, long inactivity, fights and conflict events
  • early detection of smoke, open flame, sparks, spills and emergency situations
  • alerts to Telegram, email, BI, SCADA/MES and event logs for investigations
Safety of people, equipment and hazardous zones
FROM RAW MATERIAL TO SHIPMENT

Control can be placed at every stage of the production cycle

The logic is not tied to one industry. It is more important to understand where the risk appears: raw material, line, assembly, packaging, storage, shipment or equipment condition.

1

Incoming raw-material control

Fractions, contamination, foreign bodies, batch quality and compliance with incoming requirements.

2

Production line

Counting, sorting, presence control, defects, color, shape, cycle time and stops.

3

Assembly and processing

Completeness, operation order, geometry, welding, fasteners, marking and surface quality.

4

Packaging and marking

Packaging defects, tightness, labels, codes, date, series, traceability and rejection.

5

Warehouse and logistics

Pallets, storage zones, movement, vehicles, stock, shipment and warehouse safety.

6

Equipment and infrastructure

Temperature, vibration, current, pressure, acoustics, emergency modes and resource prediction.

Predictive analytics and equipment anomalies
NOT ONLY VIDEO ANALYTICS

Predictive analytics and equipment anomalies

In industry, AI works not only with images. Time-series data from sensors, PLC, SCADA and laboratory measurements can be added to predict risk before unplanned shutdown.

Failure prediction

Models learn the normal equipment profile and detect deviations before they become critical.

MTBF and RUL

Remaining life estimation for units, parts and lines based on operating mode and maintenance history.

Equipment anomalies

Vibration, temperature, current, sound, pressure, speed, flow and other signals are analyzed as one stream.

Planned maintenance

Alerts, repair priorities, deviation causes and links between events, process and product quality.

HOW IT WORKS

Industrial AI platform architecture

The system works as an overlay on existing infrastructure: cameras and sensors collect data, AI models detect events, and the result is sent to the operator, line or business systems.

1

Data

IP cameras, industrial cameras, line-scan cameras, sensors, PLC, SCADA, MES, ERP and lab data.

2

AI models

Detection, segmentation, OCR, classification, measurement, tracking, anomaly detection and forecasting models.

3

Events

Defect, scrap, violation, stop, overload, process deviation, failure risk or marking mismatch.

4

Response

Operator alert, event record, PLC command, rejection, line stop, MES task or maintenance ticket.

5

Analytics

BI reports, defect map, OEE, line ranking, loss causes, quality trends and predictive panel.

IMPLEMENTATION EFFECT

What the enterprise gets

The final effect depends on the line and scenario, but usually comes from lower scrap, reduced downtime and better production transparency.

-30%less manual inspection and repeated checks
-20%fewer unplanned stops and emergency shutdowns
+15-25%higher yield and more stable quality
24/7continuous control without operator fatigue
APIevents linked to MES, SCADA, ERP, PLC and BI
IMPLEMENTATION

Pilot without stopping production

We start with one clear control point: define defect criteria, collect data, tune the model, measure the effect and scale the solution.

Site survey

We study the line, defects, speed, lighting, camera positions and response requirements.

Data and labeling

We collect examples of normal and defective cases, build the dataset and define quality classes and rules.

Model and interface

We train AI models, configure analysis frequency, operator interface and event log.

Integration

We send events to MES, SCADA, ERP, PLC, rejection systems, BI, Telegram or corporate systems.

Pilot and scale-up

We test accuracy, false positives and economic effect, then connect new lines or workshops.

INTEGRATIONS AND EQUIPMENT

We connect to what the plant already has

The system can work with existing cameras and systems; for complex tasks, industrial optics, lighting, line-scan cameras, edge servers and sensors can be selected.

Cameras and optics

IP, RTSP, ONVIF, industrial cameras, line-scan cameras, global shutter, lighting and protective housings.

Automation and line

PLC, SCADA, sensors, rejection units, stop signals, actuators and process events.

MES / ERP / 1C

Batches, shifts, orders, production jobs, quality logs, claims and traceability.

BI and reports

Dashboards for quality, OEE, productivity, losses, defects, equipment and shifts.

Equipment sensors

Vibration, temperature, current, pressure, acoustics, flow, speed, load and unit telemetry.

Data security

On-prem, Edge, closed loop, access roles, logging and hybrid architecture.

We will build an industrial AI loop for your line

Describe the area, defect, line speed and required system response. We will propose camera layout, models, integrations and a pilot with measurable effect.