| Peer-Reviewed

Life Cycle Analysis of Computer Numerical Control (CNC) Machine Components

Received: 6 February 2021     Accepted: 24 February 2021     Published: 4 March 2021
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Abstract

The nucleus of this concept and system is directly focused on a 'computer numerical control' (CNC) turret lathe and milling machine tool systems. These concepts focus specifically to this category of engineered systems. Quality design review for quality service systems is a unique concept. Standard product service systems are qualitative and subjective in nature. A quantitative system identifies Key Predictive Attributes (KPA’s), which identifies a new concept application technique and applies quantitative methods to these attributes to develop a systemic process of analyzing and monitoring the system. This research is reviewing the specific projection of service outcomes for Machine tool CNC machining centers (Lathes and Milling Machines). The specific key predictive attributes are the elements being utilized in the newly created modular function in this research, to assess the potential impact of discrete elements of these attributes as it affects the occurrence of equipment down time for a system which will work to quantify the service quality of the maintenance process. This project is unique in that currently there is no system which utilizes methods or tools, that proactively gather, analyze, assess, and project outcomes of equipment “Down Time” of the Service Quality process. The innovative position of this analysis is one of actual variable tolerances, versus a more traditional nominal referenced variable reference. What makes this research unique additionally is the system is pre-service and not post service reporting of actual down time of the equipment. This research is much more than pro-forma estimate of service outcomes. Another unique aspect of this method is that it will establish tangible tolerances to assess the performance of the Design Review and Service Quality process and not just rely on subjective nominal values. Mathematical Upper Control Limits (UCL) and Lower Control Limits (LCL) will be programmatically developed based upon the system data. This system tool will develop programming algorithms which will propel this current process from a subjective qualitative process to become a robust quantitative projection tool. The novelty in this research is the development of a quality index through the creation of the new Moriarty/Ranky Transform approach.

Published in American Journal of Computer Science and Technology (Volume 4, Issue 1)
DOI 10.11648/j.ajcst.20210401.12
Page(s) 11-18
Creative Commons

This is an Open Access article, 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 or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

CNC, Quality Service, Maintenance, Life Cycle, Predictive Attributes

References
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Cite This Article
  • APA Style

    Moriarty Kevin. (2021). Life Cycle Analysis of Computer Numerical Control (CNC) Machine Components. American Journal of Computer Science and Technology, 4(1), 11-18. https://doi.org/10.11648/j.ajcst.20210401.12

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    ACS Style

    Moriarty Kevin. Life Cycle Analysis of Computer Numerical Control (CNC) Machine Components. Am. J. Comput. Sci. Technol. 2021, 4(1), 11-18. doi: 10.11648/j.ajcst.20210401.12

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    AMA Style

    Moriarty Kevin. Life Cycle Analysis of Computer Numerical Control (CNC) Machine Components. Am J Comput Sci Technol. 2021;4(1):11-18. doi: 10.11648/j.ajcst.20210401.12

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  • @article{10.11648/j.ajcst.20210401.12,
      author = {Moriarty Kevin},
      title = {Life Cycle Analysis of Computer Numerical Control (CNC) Machine Components},
      journal = {American Journal of Computer Science and Technology},
      volume = {4},
      number = {1},
      pages = {11-18},
      doi = {10.11648/j.ajcst.20210401.12},
      url = {https://doi.org/10.11648/j.ajcst.20210401.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20210401.12},
      abstract = {The nucleus of this concept and system is directly focused on a 'computer numerical control' (CNC) turret lathe and milling machine tool systems. These concepts focus specifically to this category of engineered systems. Quality design review for quality service systems is a unique concept. Standard product service systems are qualitative and subjective in nature. A quantitative system identifies Key Predictive Attributes (KPA’s), which identifies a new concept application technique and applies quantitative methods to these attributes to develop a systemic process of analyzing and monitoring the system. This research is reviewing the specific projection of service outcomes for Machine tool CNC machining centers (Lathes and Milling Machines). The specific key predictive attributes are the elements being utilized in the newly created modular function in this research, to assess the potential impact of discrete elements of these attributes as it affects the occurrence of equipment down time for a system which will work to quantify the service quality of the maintenance process. This project is unique in that currently there is no system which utilizes methods or tools, that proactively gather, analyze, assess, and project outcomes of equipment “Down Time” of the Service Quality process. The innovative position of this analysis is one of actual variable tolerances, versus a more traditional nominal referenced variable reference. What makes this research unique additionally is the system is pre-service and not post service reporting of actual down time of the equipment. This research is much more than pro-forma estimate of service outcomes. Another unique aspect of this method is that it will establish tangible tolerances to assess the performance of the Design Review and Service Quality process and not just rely on subjective nominal values. Mathematical Upper Control Limits (UCL) and Lower Control Limits (LCL) will be programmatically developed based upon the system data. This system tool will develop programming algorithms which will propel this current process from a subjective qualitative process to become a robust quantitative projection tool. The novelty in this research is the development of a quality index through the creation of the new Moriarty/Ranky Transform approach.},
     year = {2021}
    }
    

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Author Information
  • Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, the United Sates

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