A large, complex stack of black steel pipes and metal tubing in a manufacturing warehouse, representing the inventory management challenge solved by AR + AI.

Metal Parts Inventory Management Using AR + AI

Case Overview

Logo for Shuz Tung Machinery, a leading manufacturer of high-precision OEM metal parts and automation equipment.

Customer: Shuz Tung Machinery

Location: Taiwan

Industry: Manufacturing / Metal Processing

Solution: META-aivi

Objectives:

  • Reduce human error during inventory counting
  • Increase speed and accuracy of stocktaking
  • Streamline inventory data management through MES integration

Results:

  • 100% counting accuracy, eliminating human error
  • Stocktaking reduced from minutes to seconds per batch, increasing efficiency
  • Digital traceability via MES integration, enhancing auditability

Testimonial:

“After using Solomon’s wearable AI, META-aivi, the speed and accuracy when counting metal pipes has greatly improved, saving us time, costs, and enhancing operational efficiency.”

— Director, Mechanical & Electronics Department, Shuz Tung Machinery

The Customer

Shuz Tung Machinery is a leading manufacturer of automation equipment and high-precision OEM components, specializing in metal fabrication.

The Challenge

Manual Counting Limitations in High-Volume Stocktaking

Shuz Tung manages a large inventory of industrial components, including steel pipes and machinery parts with complex geometries—varying shapes, wall thicknesses, and tolerances. Manual counting was slow, labor-intensive, and prone to error, particularly when distinguishing closely sized components. Traditional counting methods could not handle these material complexities, leading to inventory inaccuracies and reduced operational efficiency.

The Solution

AR + AI Automated Counting

Shuz Tung deployed META-aivi, Solomon’s unique AR + AI vision system, to automate counting and classification of metal pipes. Using deep learning and machine vision, META-aivi detects subtle dimensional differences—such as closely sized pipe diameters or varying wall thicknesses—that manual inspection cannot. Operators using AR glasses or tablets see real-time results overlaid on the physical inventory, enabling instant verification and quality control. All inspection data is uploaded to the MES (manufacturing execution system), creating a digital traceability chain that links inventory counts directly to production and logistics workflows, improving efficiency and reducing stocktaking errors.

A wire mesh container filled with uncounted black metal pipes, representing the high-volume inventory management and stocktaking challenge.
Manual counting of densely stacked metal pipes is inefficient and error-prone, often leading to inaccurate stocktaking
Screen capture showing the META-aivi AR and AI vision system overlaying green and purple segmentation on metal pipes, displaying a precise automated counting result of 'Total: 328'.
META-aivi uses AR + AI vision to instantly count each pipe, displaying accurate results directly on the physical batch for real-time verification

The Results

100% counting accuracy, eliminating human error
Stocktaking reduced from minutes to seconds per batch, increasing efficiency
Digital traceability via MES integration, enhancing auditability