Semiautomatic dimensional screening of plastic scintillator cubes using image analysis and robotics

TL;DR

This paper presents a semiautomatic, image analysis and robotics-based system for precise quality control of plastic scintillator cubes, crucial for large-scale particle physics detectors.

Contribution

The authors developed and validated a prototype system combining imaging, robotics, and software for efficient, scalable screening of detector components with high precision.

Findings

Achieved 10 μm measurement precision.

Over 80% consistency with manual screening.

Rejection rate of 3.1% for defective cubes.

Abstract

Large-scale particle physics detectors often contain millions of repeated components, making precise and efficient quality control essential. We have developed a semiautomatic system for dimensional screening of 1 cm$^3$ plastic scintillator cubes for their potential use in future neutrino detectors. The system employs a motorized rotating stage, six high-resolution cameras, and image analysis software to measure cube size, surface protrusions, and the positions of holes for wavelength-shifting fibers used in optical readout. Based on these measurements, each cube is automatically classified as either acceptable or defective. We constructed and validated a prototype system, achieving a measurement precision of 10 $\mu$m and over 80% consistency with manual screening. To enable classification of cubes into 48 groups based on hole positions while preserving their orientation, we introduced a 6-axis robotic arm. The completed system achieved a rejection rate of 3.1%. Our approach contributes to scalable, precise, and efficient quality control for future large-scale particle physics detectors.