Sri Lanka Garment Factory Deploys 3 REEMAN Fly Boat MAX AMRs With MES Integration

From MES Work Orders to Autonomous Garment Delivery: A Three-AMR Deployment in Sri Lanka

In industrial automation, a robot successfully completing a delivery route is only the beginning. The real engineering challenge is connecting that movement to production requirements and coordinating transportation tasks across an entire manufacturing facility.

That was the challenge addressed in a garment factory in Sri Lanka, where three REEMAN Dual Laser Fly Boat MAX Autonomous Mobile Robots (AMRs) were deployed to transport semi-finished garments between designated production locations.

Previously, workers moved loaded garment racks manually, sometimes covering 150 to 300 meters in one direction. The new system connects the factory's Manufacturing Execution System (MES) with REEMAN's multi-robot scheduling platform through an open API.

When production generates a material delivery requirement, the system arranges an AMR transportation task. The assigned robot travels to the pickup point, lifts a wheeled garment rack by 10 cm, and delivers it to the corresponding production workstation.

With three robots serving different task locations, the factory's estimated daily workload is approximately 200–250 point-to-point deliveries across the fleet.

This case examines the deployment from an engineering perspective: the original material handling problem, system architecture, robot execution process, fleet coordination, commissioning experience, and lessons for manufacturers considering MES-integrated AMR automation.

Project Background and Operating Conditions

The customer is a garment manufacturer in Sri Lanka. Its internal logistics activities include moving semi-finished garments between production-related locations using wheeled material racks.

Rather than following one identical route, the three robots serve different configured task points. Individual transportation distances vary according to the assigned pickup location and destination.

The daily trip count is a reported estimate across all three robots. The 50–100 kg figure represents the actual transported garment material, not the maximum rated payload of the robot.

The Original Problem Was Repeated Transportation, Not Just Load Weight

In garment manufacturing, internal material logistics is often less visible than the sewing and production equipment. Yet the movement of semi-finished garments is essential to keeping materials available at their next production location.

Before automation, workers at this factory handled those movements manually.

Even with wheeled racks, each delivery required someone to move the materials between locations. With one-way distances reaching 300 meters on some assignments, repeated rack transportation occupied a portion of the working day.

From an engineering perspective, the issue had three dimensions.

Transportation Frequency

The factory required repeated deliveries rather than occasional movement of a single rack. Automating frequent tasks offers an opportunity to reduce the time spent on routine internal transportation.

Different Production Destinations

The robots needed to serve multiple task points. This required a configurable transportation system rather than one permanently fixed material route.

Connection with Production Orders

Material delivery needed to correspond to production requirements. Simply providing a mobile robot was not enough; the factory also required a connection between the MES and the transportation system.

These conditions made the project a combination of mechanical material handling and software-level production integration.

Engineering Solution: Connecting MES with REEMAN Fleet Scheduling

The solution separates production management, transportation task management, and physical material movement into three connected functions.

The MES remains responsible for production work orders and material requirements. REEMAN's fleet scheduling platform handles transportation assignments. The Fly Boat MAX robots execute the pickup and delivery operations.

During system integration, the teams established the relationship between production workstations, pickup locations, delivery destinations, and associated work orders.

From Production Request to Completed Delivery

When the MES generates a material delivery requirement, the integration converts that requirement into a task containing the relevant pickup and destination information.

The scheduling platform arranges the robot assignment. Once a robot completes the physical delivery, the completion information is returned through the integration and associated with the corresponding production requirement.

In practical terms, the factory's production system determines what materials need to be delivered and where. The AMR system is responsible for carrying out the transportation.

This division of responsibility is important for manufacturers that want to introduce autonomous logistics while retaining their existing MES processes.

The Physical Workflow: Automatic Lifting of Wheeled Garment Racks

The factory uses wheeled racks to hold semi-finished garments. Rather than pushing these racks, the lifting-version Fly Boat MAX transports them from underneath.

The transport cycle begins when the assigned AMR travels to the designated pickup point.

At the pickup location, the robot positions itself beneath a compatible rack and activates its lifting mechanism. The rack is raised approximately 100 mm from its supported position.

The robot then carries the rack toward the assigned production workstation. At the destination, it lowers the rack and completes the transportation task.

The actual garment material loads in this application are approximately 50–100 kg. The Fly Boat MAX model has a rated payload capacity of up to 300 kg.

This application illustrates why the mechanical interface between the AMR and the load carrier is as important as the robot's navigation capability.

Why Three Robots Require Fleet-Level Coordination

A single AMR can perform point-to-point deliveries. When several robots operate within the same facility, however, the transportation system must manage tasks across different robots and locations.

At this Sri Lankan factory, the three Fly Boat MAX robots are connected to REEMAN's centralized scheduling platform.

Each robot serves different task locations, and the system coordinates transportation assignments received through the MES integration.

REEMAN's official deployment report also identifies route coordination and traffic management as elements of the multi-robot implementation.

What Makes Multi-Robot Scheduling Different from Independent AMR Operation?

With independent operation, each robot may be assigned tasks without a shared view of the broader transportation workload.

Centralized scheduling provides a common system for organizing task execution across multiple robots.

For this factory, that means delivery requirements originating from the MES can be managed within one robot fleet workflow rather than through three separate transportation systems.

Dual-Laser SLAM Navigation

The deployed Fly Boat MAX uses dual-laser SLAM navigation to support autonomous movement within the mapped factory environment.

Unlike guidance systems that rely on magnetic strips or QR-code markers installed along the transportation routes, laser SLAM uses environmental information for localization and navigation.

This reduces the need for fixed floor guidance infrastructure, although mapping, route configuration, obstacle detection and safety validation remain necessary during deployment.

The project is also notable because REEMAN identifies it in its official May 2026 report as the company's first successful overseas implementation of its multi-robot scheduling system.

Watch the Real Deployment: Three Fly Boat MAX AMRs in Sri Lanka

The actual factory footage provides a visual record of the robots' operation. It shows three robots departing from standby, one robot collecting and lifting a garment rack, two robots encountering each other, and robots moving between task points before returning to standby.

Watch the Sri Lanka Garment Factory AMR Case on YouTube

On-Site Video Timeline

The footage shows physical robot operation. MES task generation, software-level scheduling logic and completion feedback are described from the project's integration workflow; they cannot be fully verified from the short video alone.

Operating Results: What the Deployment Data Tells Us

Based on the project's reported operating information, the three Fly Boat MAX AMRs collectively handle an estimated 200–250 point-to-point material deliveries per day.

The robots serve different transportation locations, with one-way distances of approximately 150–300 meters. Actual garment material loads are generally 50–100 kg.

These figures demonstrate the scale of the transportation work assigned to the system, but they should be interpreted carefully.

Reduction in Manual Transportation

The AMRs automate transportation tasks that were previously performed by workers manually moving garment racks.

This reduces the need for repetitive rack pushing across the factory. However, the available project information does not establish an audited labor reduction percentage.

A More Structured Material Delivery Process

By associating transportation tasks with MES production requirements, the factory can organize material delivery as part of its production workflow instead of managing every movement as a separate manual activity.

Centralized Management of Multiple Robots

Three AMRs participate in a coordinated transportation operation, rather than functioning as independent devices.

Automatic Return to Charging

The Fly Boat MAX supports automatic return to its charging station according to the configured operating conditions.

In the recorded footage, the robots return to the standby area after their assignments. Returning to standby and returning for charging are different functions and should not be confused.

Commissioning the System: An Overseas Deployment Supported Remotely

The initial deployment took approximately one week.

According to REEMAN's official deployment report, much of the technical implementation was supported remotely, with REEMAN engineers working alongside the customer's team.

Remote technical assistance covered map construction, system configuration, robot calibration, scheduling optimization and operational guidance.

The MES integration required additional coordination around production workstations, material pickup points, delivery destinations, task triggering conditions and work-order relationships.

From an implementation perspective, these tasks explain why an AMR project cannot be evaluated only through the robot's payload or navigation specifications.

The complete system must be validated using the actual factory environment, material racks and production requests.

The approximately one-week deployment period is specific to this project and should not be treated as a universal installation time for other facilities.

Customer Feedback: Recognition Following a Successful Trial

After the implementation trial, a representative of the customer's project team sent REEMAN a written appreciation message.

The message recognized the engineering team's technical expertise, commitment, proactive support, coordination and prompt responses throughout the implementation process.

The customer specifically acknowledged the team's contribution to the successful execution of the trial.

The message also expressed an interest in continued support and further system optimization.

This feedback is valuable because it describes the customer's experience during the implementation, rather than making a general marketing claim about robot performance.

For international automation projects, remote engineering coordination and responsive support are important parts of commissioning and future optimization.

At the same time, successful trial completion should not be interpreted as proof that all subsequent optimization work has already been completed.

What Other Garment Manufacturers Can Learn from This Project

1. Start with the Material Flow, Not the Robot Specification

The first step is to understand which materials move between which locations, how often the movements occur, and what kind of racks or carriers are used.

In this factory, the transport requirement involved semi-finished garments, wheeled racks and multiple production task points.

2. Confirm Mechanical Compatibility Before Automating Pickup

Automatic rack lifting is practical only when the rack dimensions, clearance, support structure and total loaded weight are compatible with the robot.

3. Design the MES Interface Around Real Production Needs

The transportation task should contain the information required for execution, including the pickup location, delivery point and relevant production requirement.

Task triggering rules and completion reporting should be tested during commissioning.

4. Evaluate the Fleet as One System

With several AMRs, overall performance depends on task scheduling, route conditions, loading and unloading times, charging arrangements and actual transportation demand.

A three-robot deployment should therefore be assessed at fleet level, not by multiplying a single robot's theoretical performance.

5. Treat Commissioning and Optimization as Separate Stages

A successful initial trial confirms that the system can perform its intended workflow under the tested conditions.

Further optimization may still be needed as production demand, task distribution and operating requirements evolve.

Frequently Asked Questions

Q1. How are autonomous mobile robots used in this Sri Lankan garment factory?

A: Three REEMAN Fly Boat MAX AMRs move semi-finished garments between configured production locations by automatically lifting and transporting compatible wheeled material racks.

Q2. How does MES integration work with the REEMAN AMR scheduling system?

A: The MES sends material delivery requests through an open API. REEMAN's scheduling system arranges transportation execution, and task completion information is returned and associated with the relevant production requirement.

Q3. How many AMRs are deployed?

A: The factory uses three REEMAN Dual Laser Fly Boat MAX lifting AMRs operating under one centralized scheduling system.

Q4. How many deliveries does the AMR fleet complete daily?

A: The project's current operating estimate is approximately 200–250 point-to-point deliveries per day across the three robots combined.

Q5. What is the actual transportation distance?

A: Reported one-way route distances vary between approximately 150 and 300 meters, depending on the assigned pickup and delivery points.

Q6. Can Fly Boat MAX transport wheeled garment racks?

A: Yes, provided the rack design is compatible with the lifting mechanism. In this application, the robot enters beneath the rack, raises it by approximately 10 cm and transports it to the assigned location.

Q7. What is the payload capacity of Fly Boat MAX?

A: The model has a rated payload of up to 300 kg. The actual garment materials transported in this factory typically weigh approximately 50–100 kg. The rack's own weight must also be considered when checking total lifting load.

Q8. What navigation technology does the robot use?

A: The deployed Fly Boat MAX uses dual-laser SLAM navigation, which supports autonomous localization and movement without requiring magnetic strips or QR-code markers installed along factory routes.

Q9. How long did the overseas deployment take?

A: The initial deployment took approximately one week, with much of the technical implementation supported remotely by REEMAN engineers in cooperation with the customer's team.

Q10. What did the customer say after the AMR trial?

A: A customer project representative sent a written appreciation message recognizing REEMAN's technical expertise, responsive support and contribution to the successful trial, while expressing an interest in continued optimization.

Q11. Can the same MES-integrated AMR approach be used in other apparel factories?

A: It may be suitable where material movements are repeatable, the load carriers are compatible, and production requirements can be mapped to transportation tasks. Each factory requires site-specific evaluation of its layout, racks, safety conditions and system interfaces.

Conclusion: A Practical Example of Production-Connected AMR Logistics

The Sri Lankan garment factory deployment illustrates a key principle of industrial mobile robotics: successful automation depends on connecting physical transportation with the processes that create the transportation demand.

In this project, three REEMAN Fly Boat MAX AMRs lift and transport semi-finished garment racks along different routes, while a centralized scheduling system organizes tasks received from the factory's MES.

The three-robot fleet supports an estimated 200–250 daily deliveries across reported one-way distances of approximately 150–300 meters.

Equally important, the implementation demonstrates the role of remote engineering support and customer collaboration in overseas automation projects.

The customer's written appreciation following the successful trial reinforces the value of technical responsiveness, while the planned continued optimization reflects the ongoing nature of industrial system improvement.

For apparel manufacturers considering AMR deployment, the central question is not simply how many robots to purchase. It is how material requests, robot scheduling, rack handling and delivery confirmation can work together as one operational process.

REEMAN Official Deployment Report:

Sri Lanka Garment Factory Multi-Robot Scheduling Project

Factory Operation Video: https://youtu.be/y3C0jtkEIPg