Case Study

How FlexPorter AMR Enabled Guardian to Ship Faster and Safer

Units of AMR

k

Pieces / Day

PPH / Person

+ %

Per-person Efficiency Improved

Project Overview

This is the second project where Syrius Technology collaborates with Guardian Malaysia on AMR solutions. The goal is to enhance the automation of outbound logistics at a busy distribution center. We aim to deploy 35 AMRs to help pick and handle 315,000 items daily, achieving an average of 327 pieces per person per hour with no more than 45.5 human pickers per shift. It's crucial that AMRs and forklifts work safely together in the same space.

The project included two implementation strategies:

  1. Tote-based AMR pick-assist solution using rack-mounted PDAs and smart carts.
  2. Pallet BAY solution where AMRs directly lift and move pallets measuring 1.2m x 1m with attached tote boxes.

The Problem

The warehouse encountered a significant challenge in scaling its operations to accommodate the surging demand. This needed to be achieved while simultaneously reducing labor costs and minimizing safety risks associated with human-forklift interactions in the narrow aisles. The primary issues included:

  • Low picking efficiency due to a fully manual process, which hindered productivity and slowed down operations.
  • Congested aisles that were shared by both pickers and forklifts, creating potential hazards and bottlenecks.
  • Rising labor costs coupled with difficulties in hiring skilled workers, which strained the budget and resources.
  • An urgent need for high throughput and rapid order fulfillment to meet customer expectations and maintain competitive advantage.

A critical business constraint was the necessity to keep labor usage under 45.5 workers per shift. This had to be balanced with the efficient and safe management of over 315,000 daily SKUs, ensuring that operations remained smooth and effective.

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Frankie Franks
CEO of Company

Before introducing FlexPorter DO AMRs in the Guardian project, the warehouse struggled with several operational challenges that limited its growth. A major issue was the lack of available workers, especially for demanding tasks like picking and handling. Rising labor costs and a lack of interest from younger workers made it hard to hire and keep enough staff to meet daily needs. The work was split into two shifts, which complicated management and led to delays and miscommunication during shift changes, affecting overall efficiency and accountability.

Another big challenge was the mismatch between rising revenue and the rapidly increasing workload. As customer demand and orders grew, the workload increased even more, leading to higher costs in labor, management, and space. This made it clear that relying solely on manual labor was not sustainable or profitable. Without smart automation, the warehouse risked facing reduced returns, more human errors, and eventually hitting a growth limit.

The Solution

To overcome the operational bottlenecks and labor constraints, the project adopted a Human-Machine Collaboration solution, which proved to be a far more optimal and pragmatic approach compared to fully automated systems like AS/RS. Instead of overhauling the warehouse infrastructure or pausing operations for large-scale reconstruction, AMRs were introduced in a way that seamlessly integrated into the existing workflow. There was no need to suspend operations during deployment—AMRs began working alongside human staff immediately, enhancing productivity without disruption. This flexible setup allows for continuous adjustments and redeployments based on real-time business needs, offering a level of agility and ease-of-use that fixed automation simply cannot match.

Beyond flexibility, the solution is future-proof, designed to scale and evolve alongside the warehouse itself. The AMRs can be easily upgraded with new top modules such as lift mechanisms or fork attachments, enabling them to handle a wider range of tasks as operational complexity grows. This adaptability ensures long-term value and protects the initial investment. Moreover, before any real-world implementation, simulation models were used to validate ROI and guide optimal deployment strategies. This meant that clients could preview performance outcomes and make informed decisions before committing to scale. The immediate result was a dramatic increase in efficiency and a balanced workload between humans and robots—achieving a smarter, safer, and more resilient warehouse operation from day one.


🔧 Configuration Overview

  • Software:
    • HandyPage Applet – Manages robot-task handoffs and interactive warehouse workflows.
    • SpeedPicker Applet – Enables rapid task execution and real-time picker-AMR coordination.
    • megacosmOS GoGoReady – Establishes initial communication between Android devices and robots, enabling configuration and system readiness from first contact.
  • System Integration:
    • FlexGalaxy.AI – Unified orchestration platform for managing AMRs, devices, users, and task logic.
    • Infor WMS – Existing Warehouse Management System integrated for real-time inventory and order processing.
  • Hardware:
    • FlexPorter DO AMRs – Autonomous Mobile Robots equipped with modular lift systems.
    • Table Trolleys – Mobile, ergonomically designed carts that assist in high-throughput tote handling.

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The Results

The Human-Machine Collaboration solution transformed our warehouse operations, boosting efficiency, labor use, and overall resilience. Before, we depended solely on human pickers to handle over 300,000 items daily, which required a large, hard-to-manage workforce across two shifts. This led to unsustainable efficiency levels during peak times, with workers often overwhelmed, especially in crowded aisles with forklifts, and productivity gaps during shift changes.

Now, with AMRs, we achieve stable and efficient operations. We process 315,000 items daily with just 45.5 pickers per shift, meeting strict labor efficiency targets. Picking efficiency rose to 327 items per person per hour, a significant improvement. AMRs take on repetitive and physically demanding tasks, allowing our staff to focus on decision-making and handling exceptions.

The robot-assisted system also brought predictability and consistency to previously fragmented workflows. AMRs were deployed flexibly without downtime or infrastructure changes, and results were immediate. Simulation tools confirmed performance beforehand, ensuring a smooth transition and clear return on investment from the start.

  • 👥 ↓ to 45.5 pickers per shift, compared to a larger headcount in manual-only setup

  • 🔁 46 picking trips/hour per robot, maximizing asset usage

  • 🧱 0 infrastructure reconstruction required — 100% plug-and-play

Where are we now

The system now runs smoothly across 7 aisles with 35 AMRs, fully integrated with WMS and real-time task tracking—cutting labor strain and keeping peak-hour order flow steady and reliable.

Looking ahead, the project is set to evolve with smarter inbound and storage automation. First, electric jack trucks will be introduced to offload pallets from box trucks and pass them directly to AMRs. The AMRs will then autonomously transport and arrange these pallets in the receiving area, enabling operators to easily complete receiving tasks using PDAs.

Next, the project will incorporate automated forklifts to handle pallet storage. After receiving, AMRs will deliver pallets to designated aisles where the auto-forklifts operate. By keeping automated forklifts stationed within their assigned aisles—rather than having them travel long distances—the system will improve both efficiency and safety, reducing the risk of collisions with human workers while streamlining high-density storage operations.

These enhancements represent the next step in building a fully coordinated, human-machine warehouse ecosystem.

DFI | Guardian Fulfillment Center

Services we provided:

  • AMR Deployment and Configuration
  • Custom Equipment and Accessories
  • Warehouse Layout and Process Reengineering
  • System Integration
  • Human-Machine Collaboration Planning
  • Safety and Risk Mitigation
  • Infrastructure Planning
  • Exception Handling and Operations Support
  • Ongoing Optimization and Future Readiness

 

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