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IJAT Vol.5 No.4 pp. 575-586
doi: 10.20965/ijat.2011.p0575
(2011)

Paper:

A Knowledge-Based Model for Capturing and Managing the Knowledge of CNC Operators for Integrating CAM-CNC Operation

Wikan Sakarinto*, Hiroshi Narazaki**, and Keiichi Shirase*

*Department of Mechanical Engineering, Graduate School of Engineering, Kobe University, 1-1 Rokko-dai, Nada, Kobe, Hyogo 657-8501, Japan

**Production Systems Laboratory, Kobe Steel, Ltd., 5-5 Takatsukadai 1-chome, Nishi-ku, Kobe, Hyogo 651-2271, Japan

Received:
October 21, 2010
Accepted:
March 7, 2011
Published:
July 5, 2011
Keywords:
knowledge-based system, knowledge capturing, knowledge representation, CAM & CNC system
Abstract

This study is aimed at filling the gap between CAM and CNC operations. The problem is important in practice but has been rarely addressed in the resarch community. In practice, the machining parameters designed by a CAM operator are not always applicable to the machining process by a CNC operator due to several reasons such as tool wear, in-availability, inefficiency, etc. This is mainly due to the discrepancy of knowledge between CAM and CNC operators. To deal with this situation, this study proposes a knowledgebased model for capturing the know-how of CNC operators in the assessment of the product data (CAM files) produced by CAM operators. The assessment determines whether the designed machining parameters are appropriate or not before proceeding further to the machining process. This assessment is the main process where the know-how of a CNC operator is actualized. Based on the data extracted from CAM files, this study discusses a method that captures the knowledge of CNC operators in the process of an assessment. In this work, the discussion is focused on common CNC milling operations.

Cite this article as:
W. Sakarinto, H. Narazaki, and K. Shirase, “A Knowledge-Based Model for Capturing and Managing the Knowledge of CNC Operators for Integrating CAM-CNC Operation,” Int. J. Automation Technol., Vol.5, No.4, pp. 575-586, 2011.
Data files:
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Last updated on Nov. 08, 2019