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IJAT Vol.6 No.6 pp. 765-774
doi: 10.20965/ijat.2012.p0765
(2012)

Paper:

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Application of Automated Context-Based DSS for Determining CNC Machining Parameter

Wikan Sakarinto*, Setyawan Bekti Wibowo*, Hiroshi Narazaki**,
and Keiichi Shirase***

*Diploma Program of Mechanical Engineering, Gadjah Mada University, Jl. Yacaranda, Sekip Unit IV, Yogyakarta 55281, Indonesia

**Production System Laboratory, Kobe Steel, Ltd, 5-5 Takatsukadai 1-chome, Nishi-ku, Kobe 651-2271, Japan

***Department of Mechanical Engineering, Graduate School of Engineering, Kobe University, 1-1 Rokko-dai, Nada, Kobe 657-8501, Japan

Received:
May 1, 2012
Accepted:
September 6, 2012
Published:
November 5, 2012
Creative Commons License
Keywords:
knowledge-based system, expert system, contextual knowledge
Abstract
This paper describes the implementation of proposed KBS automatically aware of context or constraints in which the user has to deal with to come up with intelligent DSS. Context is a fundamental information resource that has to do closely with the use of knowledge. The proposedKBS is equipped with the Expert System (ES) providing Decision Support System (DSS), aimed for realizing effective utilization of captured CNC operator knowledge when they assess machining parameters within product data. The newest module in the proposed KBS is equipped with automated contextbased DSS constructed from incoming task restraints and other related machining aspects, such as machining parameter values, cutting tool, workpiece material, etc. In this work, the discussions are focussing on CNC milling operations. According to the implementation result, CNC operators have shown enhanced accuracy on defining machining parameter values with respect to specific constraints.
Cite this article as:
W. Sakarinto, S. Wibowo, H. Narazaki, and K. Shirase, “Application of Automated Context-Based DSS for Determining CNC Machining Parameter,” Int. J. Automation Technol., Vol.6 No.6, pp. 765-774, 2012.
Data files:
References
  1. [1] W. Sakarinto, H. Narazaki, and K. Shirase, “A Knowledge-based Model for Capturing and Managing the Knowledge of CNC Operators for Intergrating CAM-CNC Operation,” Int. J. of Automation Technology, Vol.5, No.4, pp. 575-586, 2011.
  2. [2] W. Sakarinto, H. Narazaki, and K. Shirase, “A Knowledge-based Product Model Data for Integrating CAMCNC Operation,” Proc. of The 5th Int. Conf. on Leading Edge Manufacturing in 21st Century (LEM21 2009 Osaka), 2009.
  3. [3] W. Sakarinto, H. Narazaki, and K. Shirase, “A Decision Support System for CNC Machining Parameter Assessment on CNC Operator Knowledge Capturing System,” Proc. of 2010 the 14th Int. Conf. on Mechatronics Technology (2010 ICMT Osaka-Japan), 2010.
  4. [4] W. Sakarinto, S. B. Wibowo, H. Narazaki, and K. Shirase, “Automated Context-based Approach on Decision Support System for Capturing and Utilizing CNC Operators Knowledge,” Proc. of 2011 the 15th Int. Conf. on Mechatronics Technology (2011 ICMT Melbourne-Australia), 2011.
  5. [5] A. K. Dey and G. D. Abowd, “Towards a better understanding of context and context-awarness,” Technical Report GIT-GVU-99-22, Georgia Institute of Technology, College of Computing, 1999.
  6. [6] M. R. S. Borges, J. A. Pino, and R. M. Araujo, “Common context for decisions and their implementations, Group Decision and Negotiation,” Vol.15, pp. 221-242, 2006.
  7. [7] A. Abecker, A. Bernardi, K. Hinkelmann, O. Kuhn, and M. Sintek, “Context-aware, proactive delivery of task-specific information: The KnowMore project,” J. of Information System Frontiers, Vol.2, Issues 3-4, 2000.
  8. [8] W. Sakarinto, H. Narazaki, and K. Shirase, “A Decision Suport System for Capturing CNC Operator Knowledge,” Int. J. of Automation Technology, Vol.5 No.5, 2011.
  9. [9] J. V. D. Bussche and A. Heuer, “Using SQL with Object-oriented database,” Information Systems, Vol.18, Issue 7, pp. 461-487, 1993.
  10. [10] J. A. Hoffer, M. B. Prescott, and F. R. McFadden, “Modern Database Management,” Pearson-Prentice Hall, 2005.
  11. [11] T. Rochim, “Klasifikasi, Proses, Gaya & Daya Pemesinan,” Penerbit ITB, 1993.
  12. [12] G. Schreiber, H. Akkermans, A. Anjewierden, R. D. Hoog, N. Shadbolt, W. V. D. Velde, and B. Wielinga, “Knowledge Engineering and Management: The CommonKADS Methodology,” A Bradford Book, The MIT Press, Cambridge, Massachusetts, London, England, 2000.

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