An Optical Area-Scattering Based Approach for the Measurement of Surface Roughness Formed During Machining
DeVoe, Don L.
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The measurement of surface roughness during a machining process is critical for the automatic control of surface quality in a computer-integrated manufacturing (CIM) system. In this work, a method of surface roughness assessment is investigated which is particularly applicable for in-process roughness measurement. The measurement system employs a novel application of light- scattering theory, which has been used in a number of commercially available optical surface roughness measurement techniques.<P>The need for such a measurement system is discussed, and a review of several systems currently available for this purpose is provided. The theory upon which many of these optical system is based is introduced, and the theory is extended for application to the measurement system introduced in this work. The differences and advantages of the developed vision system, compared to other optical systems, are investigated. Particular attention is paid to the area-based nature of the new technique. The performance of a prototype vision system is considered, and the results of a factorial design are interpreted to determine the sensitivity of the system to six environmental and system configuration factors. A calibration curve, which relates the surface roughness of fifty aluminum workpieces to an optical roughness parameter, is developed to provide a method of determining surface roughness directly from optical measurements. A prototype of a second optical system is constructed to attach directly to a CNC milling machine, and the suitability of this system for use in a machining environment is investigated.<P>There are three stages of this work. In the first stage, a preliminary experimental study is performed to investigate some of the basic attributes of the vision system. While this study is fairly simple, it demonstrates the potential usefulness of the proposed system. In the second stage, a prototype vision system is designed and constructed, and a detailed factorial design is undertaken to develop an empirical model of the system output as a function of six factors related to the system configuration and environmental conditions. Several calibration curves are produced for relating the system output to a range of known surface roughnesses. In the third stage, a prototype system is integrated with a Computer Numerically Controlled (CNC) milling machine to investigate the feasibility of using the system in a true machining environment. The results indicate some of the advantages and limitations of the proposed system.