Determination of manufacturability and machining parameters based on a new classification of machinability
Abstract
This research discusses a new representation method to represent the machinability of materials. A classification approach is suggested that classifies materials into groups according to their similarities in mechanical properties, metallurgical structure, and chemical compositions. Classified information is then represented by using numerical codes. Materials having the same code means they may have similar microstructure, chemical composition, and property. Also classified are tool wear rates and machining parameters (speed, feed, and depth of cut). The relationships among tool wear rates, machining data, and materials can be illustrated by codes, which are converted by discrete quantitative information. This method incorporates both qualitative and quantitative information in metal cutting operations. With such a method, the data from metal cutting operations can be simplified and organized. Also revealed from the result is the inadequacy of the current material classification standard in representing the machinability of materials. With the newly proposed classification method, meaningful analysis can possibly be derived that can hardly be achieved with the original classifications standards. In this research, a set of tool wear rate data is used as an example to build a machinability database. A simplified cutting economic problem is used as a demonstration to show the use of the database and the procedure to find the optimal cutting parameters. Finally, current problems of the proposed method are discussed together with its future extensions.
Degree
Ph.D.
Advisors
Liu, Purdue University.
Subject Area
Industrial engineering
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