Study of lighting solutions in machine vision applications for automated assembly operations

Zorcolo, Alberto and Escobar-Palafox, Gustavo and Gault, Rosemary and Scott, Robin and Ridgway, Keith (2011) Study of lighting solutions in machine vision applications for automated assembly operations. IOP Conference Series: Materials Science and Engineering, 26 (1). ISSN 1757-899X (https://doi.org/10.1088/1757-899X/26/1/012019)

[thumbnail of Zorcolo-etal-MSE2011-Study-lighting-solutions-machine-vision-applications-automated-assembly-operations]
Preview
 Text. Filename: Zorcolo_etal_MSE2011_Study_lighting_solutions_machine_vision_applications_automated_assembly_operations.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (2MB)| Preview

Abstract

The application of machine vision techniques represents an invaluable aid in many fields of manufacturing, from part inspection to metrology, robot guidance and assembly operations in general. An effective illumination of the working area constitutes a crucial aspect for optimising the performance of such techniques but unfortunately ideal light conditions are rarely available, especially if the vision system has to work within small areas, possibly close to metallic surfaces with high reflectivity. This work aims to investigate which factors mostly affect the accuracy in a typical feature recognition and measurement application. A first screening of a set of six factors was carried out by testing three different light sources, according to a two-level fractional factorial design of experiments (DOE), a Pareto analysis was performed in order to establish which parameters were the most significant. Once the key factors were identified, a second series of the experiments were carried out on a single light source, in order to optimise the key parameters and to provide useful guidelines on how to minimise measurement errors in different scenarios.

CORE (COnnecting REpositories)