Establishment of process capability of machine centre driling using multiple regression analysis

A Rahman, Muhamad Arfauz and Imam Fauzi, Elfi Rahayu and Abu Bakar, Baharudin and Ali Mokhtar, Mohd Najib and Saptari, Adi and Hussein, Nur Izan Syahriah and Halim, Isa (2014) Establishment of process capability of machine centre driling using multiple regression analysis. Applied Mechanics and Materials, 465 (-). pp. 740-745. ISSN 1660-9336

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Abstract

Assessment of process capability enables manufacturers to determine if a process produces products that meet customers’ expectation. Process capability can be beneficial in the long run in producing quality parts with minimum reject and optimum manufacturing cost. This paper proposes a procedure to assess process capability of a machining centers in drilling process using statistical analysis of machining parameters and machine rigidity. Experimental method used mild steel plate as work piece and carbide indexable cutting insert on drill of diameter 20mm. Cutting parameters such as cutting speed and feed rate were varied according to different cutting parameter level while wear in peripheral insert was inspected before and after each test run start. Machine rigidity in terms of vibration acceleration amplitude in x-, y-, and z-axis were measured and analyzed. Process capability index, Cpk of drilled hole accuracy was calculated. A regression model based on this experiment was established for predicting the process capability of machine tool in drilling operation. The established regression model is proven to have high accuracy, which is more than 80%. The validation test was carried out on a different machine tool with the same cutting conditions to check if different machine was adaptable to the regression model. This finding provides useful guidelines for machining operator to predict the process capability of the machine tool in the drilling process.

Item Type:	Article
Uncontrolled Keywords:	Drilling, Machining parameters, Multiple regressions, Rigidity, Vibrations
Divisions:	Faculty of Manufacturing Engineering > Department of Manufacturing Management
Depositing User:	Dr. Isa Halim
Date Deposited:	01 Apr 2014 02:14
Last Modified:	04 Jul 2023 12:14
URI:	http://eprints.utem.edu.my/id/eprint/12032
Statistic Details:	View Download Statistic

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