Date of Award

Fall 1991

Document Type

Thesis - Restricted

Degree Name

Master of Science (MS)

Department

Mechanical Engineering

First Advisor

Cariapa, Vikram

Second Advisor

Akbay, Kunter S.

Third Advisor

Radharamanan, R.

Abstract

In the present global market there is a need for products with fine surface finishes. A polishing process using compliant tools is one means of improving surface finish of a product. In this research, a two phase approach is adapted to investigate the polishing characteristics of one type of compliant tool, namely circular filamentary brushes. The first phase of the research involves identification of important process parameters and corresponding performance measures of circular filamentary brushes during a polishing operation. Taguchi design of experiments strategy is used to investigate the polishing of brass workparts, using a nylon filamentary brush and an abrasive impregnated nylon filamentary brush. The main and interaction effects of process parameters on various performance measures is discussed. It is observed that an abrasive impregnated filamentary brush improves the surface finish more substantially than a plain nylon brush. The second phase of the research investigates the feasibility of utilizing neural networks as potential tools in an automated polishing scenario. This phase includes the design and testing of two types of neural networks, i.e., a prediction network and a control network. A prediction neural network is designed to predict the performance measures of the polishing process using process parameters of the polishing operation as inputs. A control neural network is designed to predict the process parameters of the polishing operation, given the performance measures of the polishing process as inputs. The performance of prediction neural network is within acceptable limits except for few exceptions. Control neural network designed in this research did not perform within acceptable limits.

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