Manufacturing industries often use contact and noncontact drilling tools to drill holes. The aerospace and automobile industries, in particular, require millions of holes for riveting and bolt joining. However, the precision of the machine device/tool and working conditions, such as vibration, can lead to off-center drilling. This results in tedious and time-consuming efforts to measure the location of each hole. To address this issue, this paper proposes a technique for identifying defective parts based on hole location using machine vision. The study includes a perfect model and test models with 90 datasets, created using CATIA V5 software. The test models intentionally vary the spacing distance of the center of the hole in three directions: horizontal, vertical, and diagonal directions. The perfect model has holes with an 83 mm spacing distance between them, while the test models range from 80 mm to 83 mm in 0.1 mm increments along the three directions. The mean difference between the perfect model and test models was studied, and the results show that deviations in hole spacing distance from 80.1 to 83 mm are easily detectable using edge detection methods.