A Machine Vision Based Automated Quality Control System for Product Dimensional Analysis

Quality control (QC) in manufacturing processes is critical to ensuring consumers receive products with proper functionality and reliability. Faulty can lead additional costs for the manufacturer damage trust a brand. A growing trend QC use of machine vision (MV) systems because their noncontact inspection, high repeatability, relatively low cost. This paper presents robust MV system developed perform comparative dimensional inspection on diversely shaped samples, including additive products. The algorithm used performs base product considered have acceptable dimensions. perimeter, area, rectangularity, circularity are determined using blob analysis calibrated camera. These parameters then as standard which judge Each following similarly inspected compared parameters. likeness score calculated each product, provides single value tracking all parameter differences. Finally, whether it within threshold, be or defective. proposed has achieved satisfactory results, discussed results section, that would allow serve dependable accurate industrial settings.