Machine vision in the tire industry

Abstract

The author examines the use of machine vision as an intelligent sensor for the acquisition of process data and the ways in which the data can be assimilated into closed-loop control of the tire manufacturing process. He first describes how process data can be collected with vision sensors. Specific application examples are given. The various methods by which this process data can be integrated into an automatic control system for closed-loop feedback are discussed. Some of the application issues involved when vision sensor technology is used in the tire manufacturing environment are examined. Applications of machine vision in the tire industry can be classified as noncontact measurement, assembly verification, and product identification. Depending on the degree of process automation, the vision system can supply a simple accept/reject signal, actual results data, or an identification code. It is noted that the implementation of vision sensors has been somewhat hindered because of the harsh environment present in the tire manufacturing process. Techniques are available for dealing with these environmental concerns and must be incorporated into the system design from the beginning. It is concluded that the real benefit of machine vision is realized when the inspection data can be tied back into the machine control architecture for true automatic closed-loop process modification. >