MEMS 411: Automatic Ball Bearing Sorter

The objective of this project was to design and build an automatic ball bearing sorter to sort bearings by both material (steel, brass, plastic) and size (½ inch and ¼ inch) into separate packaging stations. The system was designed to process up to 80 balls poured simultaneously into a hopper and accurately sort them in under one minute, with a target accuracy of 90% or greater. The customer, Dr. Potter, provided specifications and requirements for the device, including a compact size (≤ 20x20x20 inches) and weight (≤ 15 lbs). Additional customer needs included performance reliability, manufacturability, safety, speed, and ease of assembly. The sorter was built on an aluminum rail base frame, starting with a hopper that uses a slanted ramp with guiding rails to prevent jamming. After the bearings are sorted by size through the diverging rails, they are directed into two separate tracks—one for ½-inch bearings and one for ¼-inch bearings. Each track features a catcher area to catch the bearings as they depart the diverging rails, followed by a downward sloped tube where the bearings roll until they hit a vertical wall. A light sensor analyzes the material of each bearing and sends a signal to a solenoid, which launches the bearing over the wall and into one of three possible paths. The paths are managed by a servo motor that directs the moving tube piece, guiding the bearing to the appropriate packaging station according to its type of material. The device’s electrical components are controlled by an Arduino system, with all parts connected through a custom circuit and code to ensure proper signaling. Most mechanical components—aside from the frame and electrical parts—were CADdesigned and 3D printed. The device meets key performance goals, consistently adhering to size and processing time requirements, with an average cycle time of 40 seconds. Although the target precision was 90%, the current model achieves 85%, which falls short of the target, but still shows strong and impressive results, with room for fine-tuning and improvement.

Publication Details

Journal
Open Scholarship Institutional Repository (Washington University in St. Louis)
Published
2024-12-06
Primary Topic
Arduino and IoT Applications
Type
article
Field-Weighted Citation Impact
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article

MEMS 411: Automatic Ball Bearing Sorter

Open Scholarship Institutional Repository (Washington University in St. Louis)
Arduino and IoT Applications
article

MEMS 411: Automatic Ball Bearing Sorter

article en

Abstract

The objective of this project was to design and build an automatic ball bearing sorter to sort bearings by both material (steel, brass, plastic) and size (½ inch and ¼ inch) into separate packaging stations. The system was designed to process up to 80 balls poured simultaneously into a hopper and accurately sort them in under one minute, with a target accuracy of 90% or greater. The customer, Dr. Potter, provided specifications and requirements for the device, including a compact size (≤ 20x20x20 inches) and weight (≤ 15 lbs). Additional customer needs included performance reliability, manufacturability, safety, speed, and ease of assembly. The sorter was built on an aluminum rail base frame, starting with a hopper that uses a slanted ramp with guiding rails to prevent jamming. After the bearings are sorted by size through the diverging rails, they are directed into two separate tracks—one for ½-inch bearings and one for ¼-inch bearings. Each track features a catcher area to catch the bearings as they depart the diverging rails, followed by a downward sloped tube where the bearings roll until they hit a vertical wall. A light sensor analyzes the material of each bearing and sends a signal to a solenoid, which launches the bearing over the wall and into one of three possible paths. The paths are managed by a servo motor that directs the moving tube piece, guiding the bearing to the appropriate packaging station according to its type of material. The device’s electrical components are controlled by an Arduino system, with all parts connected through a custom circuit and code to ensure proper signaling. Most mechanical components—aside from the frame and electrical parts—were CADdesigned and 3D printed. The device meets key performance goals, consistently adhering to size and processing time requirements, with an average cycle time of 40 seconds. Although the target precision was 90%, the current model achieves 85%, which falls short of the target, but still shows strong and impressive results, with room for fine-tuning and improvement.

Open Scholarship Institutional Repository (Washington University in St. Louis)
Openalex Percentile: Top 64%
Arduino and IoT Applications
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