Leveraging Defect Trend Analysis for Sustainable Printed Circuit Board and Assembly (PCBA) Quality Assurance: A Low-Cost Portable Smart Inspection Solution for Small-Scale Electronics Manufacturers
Meynard H. Samson | Francis Balahadia
Discipline: electrical and electronic engineering
Abstract:
This research addresses the challenges in quality
assurance (QA) for low-volume Printed Circuit
Board and Assembly (PCBA) production, where
manual inspection often leads to inconsistencies,
limited traceability, and delays. Analyzing defect
trends from 2019 to 2024 across six suppliers,
the study identified common issues such as
missing components, misalignment, and solder
defects. This defect analysis introduces the
concept of developing a low-cost, portable, AIdriven PCBA QA inspection system that would
utilize a high-resolution microscope, Pythonbased computer vision, and object detection tools
like YOLO to provide an affordable, scalable, and
customizable solution ideal for small-scale
manufacturers, SMEs, and research
environments. This conceptual system is
intended to enhance inspection efficiency,
accuracy, and traceability while promoting
sustainable engineering practices. Future
research would focus on developing and
implementing this system, including AI-based
defect classification and conducting pilot studies
to validate its performance in real-world settings.
This system has significant implications for SMEs
in electronics manufacturing, providing an
accessible, cost-effective solution to improve
product quality and support the digital
transformation of manufacturing operations.
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ISSN 3082-3684 (Online)
ISSN 3082-3676 (Print)