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     Research Journal of Applied Sciences, Engineering and Technology


The Methodologies of Automatically Analyzing the Similarity of Processes Based on Features Abstracted From NC Codes

Yabo Luo, Ya Mao, He Ling and Lei Chen
School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, 430070 China
Research Journal of Applied Sciences, Engineering and Technology  2013  10:2923-2928
http://dx.doi.org/10.19026/rjaset.5.4600  |  © The Author(s) 2013
Received: September 07, 2012  |  Accepted: October 05, 2012  |  Published: March 25, 2013

Abstract

It is difficult to draw the similarity correlation degree of the process features from NC codes since the NC codes do not represent the process features directly. This research works at the methodologies of automatically analyzing the similarity of process based on features abstracted from NC codes to improve the group efficiency. Employing the NC codes’ advantages of the clear and stable structure, good readability, taking the similarity principles as the theoretical foundation, this research regards the NC codes as similar systems to study on the problem of automation for similarity correlation comparison of process features. A detailed and concrete case study demonstrates the specific steps of the process features modeling and similarity comparison of the NC codes. The calculation and comparison shows the effectiveness of the method, which provides the foundation for group automation.

Keywords:

Correlation relationship, group technology, NC codes, similarity theory,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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