An Optical Area-Scattering Based Approach for the Measurement of Surface Roughness Formed During Machining

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.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.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

Optical Area-Based Surface Quality Assessment for In-Process Measurement

The measurement of surface finish has been recognized as an important element of Computer Integrated Manufacturing (CIM) systems which perform on-line machining systems control. Optical methods for the in-process measurement of surface roughness have been developed for this purpose, but these systems have in many cases introduced excessive complexity in the CIM system. This work presents an area-based surface characterization technique which applies the basic light scattering principles used in other optical measurement systems. These principles are applied in a novel fashion which is especially suitable for in-process measurement and control. A prototype of the optical system to implement these principles is developed in this work. The experimental results are presented to demonstrate the capabilities and future potential for integrating the measurement system into a machining process to achieve significant improvement of quality and productivity

An Experimental Study of Surface Roughness Assessment Using Image Processing

A surface roughness measurement technique, based on an area measurement method using a computer vision system, was investigated for applicability to in-process inspection of surface quality during a machining process. The vision system uses a monochrome CCD camera to provide a gray-scale image based on the pattern of light scattered from an area of the machined piece. This gray-scale image is sent to image manipulation software for analysis. For this investigation, an optical camera was used to photograph four aluminum samples with different roughnesses, and the resulting photographs were scanned into a computer using an 8-bit flat-bed scanner to produce the digital image used by the image manipulation software. Three parameters were derived from the images based on their gray-scale histograms, and these parameters were plotted against the corresponding average roughness (Ra) values determined using a stylus instrument. The resulting correlation curves were inspected to determine which optical parameter was most suitable for use in the system, based on relative accuracy and sensitivity of the parameters to changes in Ra

Microscale Patterning of Thermoplastic Polymer Surfaces by Selective Solvent Swelling

A new method for the fabrication of microscale features in thermoplastic substrates is presented. Unlike traditional thermoplastic microfabrication techniques, in which bulk polymer is displaced from the substrate by machining or embossing, a unique process termed orogenic microfabrication has been developed in which selected regions of a thermoplastic surface are raised from the substrate by an irreversible solvent swelling mechanism. The orogenic technique allows thermoplastic surfaces to be patterned using a variety of masking methods, resulting in three-dimensional features that would be difficult to achieve through traditional microfabrication methods. Using cyclic olefin copolymer as a model thermoplastic material, several variations of this process are described to realize growth heights ranging from several nanometers to tens of micrometers, with patterning techniques include direct photoresist masking, patterned UV/ozone surface passivation, elastomeric stamping, and noncontact spotting. Orogenic microfabrication is also demonstrated by direct inkjet printing as a facile photolithography-free masking method for rapid desktop thermoplastic microfabrication