Impact of Adequate Knowledge Model on Bottom-Line
Keywords:
knowledge modeling, ontology, process modeling, CAD/CAM, CIMAbstract
As the competition is getting fiercer, smarter knowledge representation is needed to keep our bottom line un-compromised. With the so much outsourcing of jobs, more of our youth are going away from studying and/or training in manufacturing. Unless more is done immediately, this will hit the whole manufacturing community with lack of expertise and less people with the "know how" skills to keep our manufacturing prospering. In this paper advantages of an adequate knowledge modeling are highlighted. Ontology will be used as a platform for modeling the accumulated knowledge in manufacturing. A meta model will be built to capture the manufacturing knowledge in an easy to use and maintain model. A turning process is selected to model the knowledge needed for it in an ontology model.
References
EU commission enterprise and industry, Impact of the economic crisis on key sectors of the EU – the case of the manufacturing and construction industries. February 2010
Flexing Its Muscle: Why Manufacturing Is Bouncing Back, Knowledge at Wharton. By John Ryding.
William Inmon, Inmon Data Systems, Castle Rock, CO, USA
Bonnie O'Neil, Project Performance Corporation, Denver, CO, USA
Lowell Fryman, VIP LLC, Denver, CO, USA. Business Meta Data: Capturing Enterprise Knowledge. Morgan Kaufmann.
Ian Cameron,John Perkins, Katalin Hangos and George Stephanopoloulos, Process Modeling and model analysis. May 2001, Academic Press
Eric H. K. Fung, S. M. Cheung and T. P. Leung. The implementation of an error forecasting and compensation system for roundness improvement in taper turning. Computers in Industry, Volume 35, Issue 2, March 1998, Pages 109-120
C. Acosta, W. Switek and E. Garcia. Dynamic modeling in turning machining. Computers & Industrial Engineering
Volume 33, Issues 1-2, October 1997, Pages 397-400 Proceedings of the 21st International Conference on Computers and Industrial Engineering
Li Qian, and Mohammad Robiul Hossan. Effect on cutting force in turning hardened tool steels with cubic boron nitride inserts. Journal of Materials Processing Technology. Volume 191, Issues 1-3, 1 August 2007, Pages274-278 Advances in Materials and Processing Technologies, July 30th - August 3rd 2006, Las Vegas, Nevada
Raid Al-Aomar, and Ala’a Al-Okaily. A GA-based parameter design for single machine turning process with high-volume production. Computers & Industrial Engineering Volume 50, Issue 3, July 2006, Pages 317-337
Y. Kevin Chou and Hui Song. Thermal modeling for white layer predictions in finish hard turning. International Journal of Machine Tools and Manufacture
Volume 45, Issues 4-5, April 2005, Pages 481-495.
Yue Jiao, Shuting Lei, Z. J. Pei and E. S. Lee. Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations. International Journal of Machine Tools and Manufacture. Volume 44, Issue 15, December 2004, Pages 1643-1651
Yongjin Kwon, Gary W. Fischer and Tzu-Liang Tseng. Fuzzy neuron adaptive modeling to predict surface roughness under process variations in CNC turning. Journal of Manufacturing Systems
Volume 21, Issue 6, 2002, Pages 440-450.
Downloads
Published
How to Cite
Issue
Section
License
- Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
- It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
- The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
- The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.