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Industrial & Courier  ·  Conveyor Picking
AI-powered robotic
picking for conveyor belts.

Automate repetitive picking, sorting, and handling on moving lines. Makeen deploys vision-guided robots — powered by Sirona — that identify, pick, and place objects for manufacturing quality inspection and courier sortation across the UAE.

Potential labour savings
AED 60–100K
Per cell / year · illustrative UAE
Hours automated
6–8K
Repetitive picking hours / year
Indicative payback
2–4 yr
Labour savings alone
The Problem

Conveyor picking is still highly manual.

Manufacturing plants with quality inspection, warehouses, and courier hubs still rely on operators to identify, pick, sort, and place products from moving belts — shift after shift.

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Variable parts — different sizes, shapes, orientations, and SKUs arriving in unpredictable positions.
Moving targets — variable conveyor speeds make timing the pick the hard problem.
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Labour dependence — throughput drops when operators are unavailable, fatigued, or rotating across shifts.
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Rising cost — consistent quality inspection and sortation is expensive to scale with headcount alone.
The Challenge

How do you make a robot reliably pick the right object, at the right time, from a moving conveyor?

That is the brief for every quality line and courier sort belt we walk. Defective parts must be selected, sorted, and binned without stopping the line. Good parts — and the right parcels — must keep moving.

Our Solution

Intelligent robotic picking.

Makeen implements customized vision-guided robotic cells that understand the production environment and dynamically execute picking operations. Computer vision, AI, robotics, and motion planning work as one system.

01
See
02
Understand
03
Plan
04
Pick
05
Place
Detect objects on the conveyor and identify the target — including defective parts by visual characteristics.
Estimate position and orientation, then track or predict movement as the belt runs.
Generate an optimized trajectory, synchronize with the conveyor, and place the object in the required bin, lane, or destination.
How It Works

From conveyor to pick — in real time.

01
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Perception

Cameras continuously observe the belt and detect objects entering the robot’s workspace.

02
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Understanding

AI perception decides which objects to pick and estimates position, orientation, and quality traits.

03
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Motion Plan

The system calculates a safe trajectory from object location, belt speed, robot config, and surroundings.

04
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Dynamic Pick

The robot synchronizes with the moving conveyor and executes the pick at the right moment.

05
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Place & Repeat

The object is binned or transferred. The cell immediately prepares for the next pick.

Built for Real Lines

Not every pick looks the same.

Traditional automation struggles when position, orientation, or appearance changes. These cells are designed for real-world variability on factory floors and courier hubs — not a single SKU in a fixture.

Multiple object types Variable orientation Moving objects Variable belt speeds Cluttered scenes Multiple destinations Multiple SKUs Changing lighting
Use Cases

One platform. Multiple picking jobs.

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Quality-based picking

Identify products by visual characteristics and separate accepted vs. rejected parts on the inspection line.

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Defective binning

Select defective parts from a moving conveyor and place them into reject bins without stopping throughput.

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Courier sortation

Identify parcels and route each item to the correct lane, cage, or outbound conveyor in delivery hubs.

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Packaging

Pick products from a conveyor and place them into packaging, cartons, or containers.

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Assembly feeding

Identify components and feed them into downstream assembly processes at line rate.

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Bin / conveyor transfer

Transfer objects between conveyors, bins, pallets, or workstations across the cell.

Business Impact

Automate thousands of hours of repetitive work.

For a typical Dubai / UAE operation running two shifts, the economics become material once the cell is on the line. Illustrative example: a conveyor picking job that needs ~2 operators per shift across 2 shifts per day.

MetricManual operationRobotic operation
Operators / shift~2~0.5–1*
Shifts / day22
Labour requirement~4 operator-shifts/day~1–2 operator-shifts/day
Picker salary benchmark~AED 2,300–2,500 / month
Annual labour cost~AED 125K–132K~AED 31K–66K
Potential annual labour savings~AED 60K–100K
Manual hours automated~6,000–8,000 hrs/year

*Depends on supervision needs and whether the cell can run unattended. UAE picker salary benchmarks ~AED 2,300/month; loaded cost includes visa, insurance, and end-of-service.

AED 200–250K
Illustrative cell investment
~3.3–4.2 yr
Conservative payback · AED 60K/yr
~2.5–3.1 yr
Typical payback · AED 80K/yr
~2.0–2.5 yr
High utilization · AED 100K/yr
Your Line

Your process. Your robot. Your solution.

Every factory has different objects, conveyor layouts, cycle times, lighting, and downstream processes. Makeen — with Sirona’s robotics platform — designs the cell around your actual line, not a catalogue SKU.

01
Understand Map the existing workflow, objects, cycle time, constraints, and success criteria.
02
Simulate Build and test the robotic workflow in simulation before hardware hits the floor.
03
Pilot Validate perception, picking accuracy, throughput, and reliability on the real system.
04
Deploy Integrate with the conveyor, PLC, sensors, and factory or hub infrastructure.
05
Scale Expand across additional SKUs, production lines, sort zones, or facilities.
Why Makeen

Robotics built around your use case.

Hardware agnostic

We select the right robot, camera, and end-effector for the application — not the other way around.

AI-first perception

Modern vision and learning-based models for mixed SKUs, orientation changes, and messy belts.

Simulation before deploy

Validate workflows before committing to physical installation on a live production line.

UAE implementation

Local install, integration, training, and SLA-backed service. Sirona supplies the platform layer; Makeen runs the deployment.

⚠ NOTE
All figures and ROI projections on this page are representative estimates based on published UAE labour benchmarks and illustrative cell configurations. They are not guarantees of performance. Actual results depend on labour cost, shifts, production volume, system configuration, and the degree of automation. Contact us for a line-specific business case.
Have a conveyor picking challenge?
Tell us about your line.
Objects, belt speed, quality criteria, and sort destinations — we’ll assess what can be automated and what the ROI could look like.
Contact

Let’s talk your belt.

Manufacturing quality inspection or courier sortation — same core capability: see, decide, pick, bin.

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Email
info@makeenrobotics.com
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WhatsApp
+971 50 678 1841
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Location
Dubai, United Arab Emirates