AI-Powered Quality Control and Inspection Systems in Modern Manufacturing

Abstract

Quality control (QC) is critical in modern manufacturing to ensure product reliability, reduce defects, and enhance customer satisfaction. Traditional QC methods rely heavily on manual inspection, which is time-consuming, error-prone, and inconsistent. The integration of Artificial Intelligence (AI) with advanced sensing and imaging technologies has enabled automated quality control and inspection systems that operate in real time. This paper reviews AI-driven approaches for quality inspection, including computer vision, machine learning, deep learning, and robotics. It explores the architecture of AI-powered QC systems, data acquisition, defect detection algorithms, and practical applications in automotive, electronics, and food industries. Case studies demonstrate improvements in defect detection accuracy, throughput, and operational efficiency. Challenges such as data quality, integration with legacy systems, and algorithm interpretability are discussed. The study concludes that AI-powered QC systems are essential for Industry 4.0 manufacturing and smart factories.

Cite as:

Dr. Kondekal Manjunatha. (2025). AI-Powered Quality Control and Inspection Systems in Modern Manufacturing. Research and Reviews: Journal of Mechanics and Machines, 7(3), 18–23. 

https://doi.org/10.5281/zenodo.17839003