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Knowledge management based process planning system

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Process planning knowledge (PPK) is one of the most important knowledge in production manufacturing enterprise. The traditional method of organizing data into knowledge relies on manual analysis and interpretation. This paper analyzes the source and composing of process planning knowledge and state of arts on process planning discovery in production manufacturing enterprise. On the basis of the application of computer aided process planning (CAPP) system in mechanical manufacturing enterprise, the concept of process planning information model (PPIM) is proposed based on process planning databases. This paper provides a CAPP database developed in own research, clarifying how PPK and PPIM in CAPP database are related both to each other and to related fields, the technology database of process planning knowledge discovery is modeled based on object-oriented model-driven technology, and the process planning knowledge discovery script is designed.
Rocznik
Strony
107--120
Opis fizyczny
Bibliogr. 14 poz., rys.
Twórcy
autor
  • Faculty of Mechanical Engineering, University Ss. Cyril and Methodius, Skopje, Macedonia
autor
  • Faculty of Mechanical Engineering, University of Maribor, Maribor
Bibliografia
  • 1. RODGERS A. PAUL., CALDWEL NICHOLAS H. M., CLARKSON JOHN P., 2000, Managing knowledge in dispersed design companies-Facilitating context-driven design support through multiple perspectives. Artificial Intelligence in Design. 147-167.
  • 2. SHAKERI M., 2004, Implementation of an automated operation planning and optimum operation sequencing and tool selection algorithms, Computers in Industry. SAiyili-Ti.
  • 3. BALIC J., PAHOLE I., 2003, Optimisation of intelligent FMS using the data flow matrix method. Journal of Materials Processing Technology, 133/1/2/13-20.
  • 4. SORMAZ D., 2005, Intelligent Manufacturing Based on Generation of Alternative Process Plans, Proceedings of Int. Conference on Flexible Automation and Intelligent Manufacturing, Tilburg, 35-49.
  • 5. HALEVI G., WEILL, R.D., 1995, Principles of Process Planning. Chapman& Hall.
  • 6. SHAH J. J., MANTYLA M., 1995, Parametric and Feature-Based CAD/CAPP/CAM. Wiley.
  • 7. MARRI H. B., GUNASEKARAN A., GRIEVE R. J., 2005, Computer-Aided Process Planning: A State of the Art, Int. J. of Advanced Manufacturing Technology 14/261-268,.
  • 8. STEPHAN H., KARL F., 2000, Knowing plant—Decision supporting and planning for engineering design, Intelligent Systems in Design and Manufacturing III. Proceedings of SPIE, 376-384.
  • 9. HALPIN T., 2006, Information Modelling and Relational Databases: from conceptual analysis to logical design, Morgan-Kaufmann, San Francisco.
  • 10. GECEVSKA V., CUS F., ZUPERL U., 2005, Evolutionary Computing with Genetic Algorithm in Manufacturing Systems, Journal of Machine Engineering, vol.5. No 3/4/188-198.
  • 11. GECEVSKA v., CUS F., LOMBARDI F., DUKOVSKI V., 2006, Intelligent Approach for Optimal Modelling of Manufacturing Systems, Journal of Achievements in Materials and Manufacturing Engineering, Elsevier, Vol.14, Issue 1-2/97-104.
  • 12. CUS F., ZUPERL U., 2006, Approach to Optimization if cutting conditions by using artificial neural networks, Journal of Materials Processing Technology, 1/112-122.
  • 13. CHANG T., 1990, Expert Process Planning for Manufacturing, Addison-Wesley, CA.
  • 14. GECEVSKA V., CUS F., 2009, Intelligent Production Systems Way to Conncurent and Innovative Engineering, Scientific Monography, Pub. Faculty of ME, Skopje, MK and Faculty of ME, Maribor, SLO, ISBN 978-9989- 2704-2-7, 289.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b5ea56b4-9b54-499c-a8f8-974f8599a28d
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