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IJAT Vol.13 No.6 pp. 825-833
doi: 10.20965/ijat.2019.p0825
(2019)

Paper:

Automated Process Planning System for End Milling Operation Constrained by Geometric Dimensioning and Tolerancing (GD&T)

Isamu Nishida, Shogo Adachi, and Keiichi Shirase

Kobe University
1-1 Rokko-dai, Nada-ku, Kobe, Hyogo 657-8501, Japan

Corresponding author

Received:
June 28, 2019
Accepted:
September 16, 2019
Published:
November 5, 2019
Keywords:
geometric dimensioning and tolerancing (GD&T), geometric tolerance, automation, process planning, NC program
Abstract

To realize autonomous machining, it is necessary to focus on machining tools and also on the automation of process planning in the preparation stage. This study proposes a process planning system that automatically defines the machining region and determines the machining sequence. Although previous studies have explored computer-aided process planning, only a few have considered geometric tolerances. Geometric tolerances are indicated on product drawings to eliminate their ambiguity and manage machining quality. Geometric dimensioning and tolerancing (GD&T) is a geometric tolerance standard applied to a three-dimensional computer-aided design (3D CAD) model and are expected to be used for the digitization of manufacturing. Therefore, this study developed an automated process planning system by using GD&T as a sequencing constraint. In the proposed system, the machining sequence is automatically determined by the geometrical constraints, which indicate whether the tool can approach, and GD&T, which indicates the geometric tolerance and datum in a 3D CAD model. A case study validated the proposed method of automated process planning constrained by GD&T. The result shows that the proposed system can automatically determine the machining sequence according to the geometric tolerance in a 3D CAD model.

Cite this article as:
I. Nishida, S. Adachi, and K. Shirase, “Automated Process Planning System for End Milling Operation Constrained by Geometric Dimensioning and Tolerancing (GD&T),” Int. J. Automation Technol., Vol.13 No.6, pp. 825-833, 2019.
Data files:
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