Intelligent vision system to control flexible assembly cell feeding processes

Abstract

A vision system which is installed at an assembly cell to detect its feeding system must analyze objects for inspection and assembly operations. This means that a description of the objects must be generated. A particular analytic technique may be characterized by the nature of the formal description generated, by the computation techniques employed and by the degree to which the formal description accurately reflects pertinent information about the object. To execute assembly tasks, the part identification, orientation, spatial position and geometric features were calculated. For inspection tasks, a list of deviations between the observed object and a reference object was generated to determine whether a part could proceed into the assembly cell. Since the vision system is associated with real-time assembly cell operations, its vision data processing time must be minimized. Therefore, intelligent processing techniques must be developed. Such techniques are provided by the developed knowledge-base and inference engine. The described vision system which is incorporated with the knowledge base and the inference engine is referred to as an “intelligent vision system”. The developed intelligent vision system was implemented in a simulation program to inspect the feeding systems of pneumatic motor assembly cells. The results support known interrelationships between parameters associated with detected assembly processes, and verify the reliability of the developed inference engine reasoning algorithms. Since the simulation was programmed in generic terms, it is not limited to a specific product but can be applied to a large variety of products.