Skip to main content
Article thumbnail
Location of Repository

Development of a knowledge warehouse for grinding

By Asmaa Alabed and Xun Chen

Abstract

Successful of grinding in practice is highly depending on the level of expertise of the machinist and engineer. Knowledge Management might offer a strategy to keep the valuable knowledge. The main objective of Knowledge Management (KM) is to manage knowledge process, the knowledge itself could not be managed, what can be managed is the knowledge gathering, storing and organizing, retrieving, and sharing. The organization should have an effective and efficient information system to facilitate knowledge management process. This paper presents the current development of a Grinding Knowledge Warehouse (GKW) which facilitates and supports knowledge management process for grinding technology and provides a guidance to select the required grinding conditions or parameters for a given grinding operation taking account of the lessons learned from previous cases

Topics: T1, TJ
Publisher: University of Huddersfield
Year: 2009
OAI identifier: oai:eprints.hud.ac.uk:6869

Suggested articles

Citations

  1. A generic Intelligent Control System for Grinding, PhD theses,
  2. and Moruzzi J.L.,(1988), Avoidance of thermal damage in grinding and prediction of the damage threshold, doi
  3. and Shin C.,(2008) Generalized practical models of cylindrical plunge grinding processes, doi
  4. and Spijkerevet A.,(1997), A knowledge management: dealing intelligently with knowledge. knowledge management and its integrative elements, Liebowtiz & Wilcox,eds.
  5. (1994). Applications of artificial intelligence in grinding, Keynote paper. doi
  6. (1995). Developing industrial awareness of case based reasoning technology
  7. (2007). Generalized intelligent grinding advisory system, doi
  8. Intelligent CNC for grinding, doi
  9. (1993). Knowledge-based expert system for ballscrew grinding.J. doi
  10. (1987). Limit chart for high removal rate centreless grinding. doi
  11. (1991). Manufacturing processes for engineering Materials”, 2nd edition,
  12. (2003). model-based optimization of the surface grinding process for heat-treated 4140 steel alloys with aluminum oxide grinding wheels, doi
  13. Moruzzi J.L,.,and Rowe W.B,(2007), Design and implementation of an intelligent grinding assistant system,Int. doi
  14. (2001). Optimization of grinding process parameters using enumeration method. doi
  15. (1991). Optimum selection of grinding parameters using process modeling and knowledge-based system approach. doi
  16. (2002). Process Requirement for Precision Grinding”,
  17. (1996). Selection of Grinding Conditions, PhD theses,
  18. Study and selection of grinding conditions part 1: grinding conditions and selection strategy, doi
  19. (1999). study and selection of grinding conditions part 2:A hybrid intelligent system for selection of grinding conditions” doi
  20. (2005). the ABCs of knowledge management, CIO magazine,. Available at http://www.cio.com/research/knowledge/edit/kmabcs.html (2001) [ Accessed
  21. (1976). The proper selection of grinding conditions in cylindrical plunge grinding. doi
  22. (1973). the surface finish-metal removal relationship in precision grinding, doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.