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Notice of Violation of IEEE Publication Principles
"Process Control Technology Application in the Manufacture of Discrete Component NC"
by Hou Ming
in the Proceedings of 2009 World Congress on Computer Science and Information Engineering
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"Process Control in CNC Manufacturing for Discrete Components: A STEP-NC Compliant Framework"
by Sanjeev Kumar, Aydin Nassehi, Stephen T. Newman, Richard D. Allen, Manoj K. Tiwari,
in Robotics and Computer-Integrated Manufacturing, Vol 23, No 6, December 2007, Elsevier, pp. 667-676
With todaypsilas highly competitive global manufacturing marketplace, the pressure for right-first-time manufacture has never been so high. New emerging data standards combined with machine data collection methods, such as in-process verification lead the way to a complete paradigm shift from the traditional manufacturing and inspection to intelligent networked process control. Low-level G and M codes offer very limited information on machine capabilities or work piece characteristics which consequently, results in no information being available on manufacturing processes,inspection plans and work piece attributes in terms of tolerances, etc. and design features to computer numerically controlled(CNC)machines. One solution to the aforementioned problems is using STEP-NC (ISO 14649) suite of stan- dards, which aim to provide higher-level information for process control. In this paper,the authors provide a definition for process control in CNC manufacturing and identify the challenges in achieving process control incurrent CNC manufacturing scenario. The paper then introduces a STEP-compliant framework that makes use of self-learning algorithms that enable the manufacturing system to learn from previous data and results in eliminating the errors and consistently producing quality products. The framework relies on knowledge discovery methods such as data mining encapsulated in a process analyser to derive rules for corrective measures to control the manufacturing process. The design for the knowledge-based process analyser and the various process control mechanisms conclude the paper.