Codification as Part of Knowledge Management in Research Projects in the Field of Metallurgy

Abstract:

Increasing requirements in the field of quality and management standards are the reason why knowledge management is regarded as an upcoming need for the metal processing industry. To fully benefit from the organisational achievements which are knowledge resources, and to meet the expectations of customers, one should think about functional, but also modern, computer system that allows the integration of heterogeneous sources of knowledge. The article describes practical aspects of the codification of metallurgical knowledge for the needs of a system of knowledge integration operating in industrial plants. The article propose successive steps to create objects of knowledge and requirements imposed onto the knowledge engineers. The presented methodology is consistent with the standards of knowledge management in the field of codification, and is based on the latest achievements of information science in the field of formal representation of knowledge.

• Periodical: Applied Mechanics and Materials (Volume 708)
• Pages: 288-293
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.708.288
• Online since: December 2014
• Authors: Krzysztof Regulski, Stanisława Kluska-Nawarecka, Dorota Wilk-Kołodziejczyk
• Keywords: Intellectual Capital, Knowledge Bases, Knowledge Codification, Knowledge Management, Metallurgy

References

[1] P. Murray, A. Myers, The Facts About Knowledge. Special Report, Information Strategy, (1997).

[2] G. Probst, S. Raub, K. Romhardt, Managing Knowledge: Building Blocks for Success, Wiley, Canada, (1999).

[3] B. Lundvall, B. Johnson, The Learning Economy, Journal of Industry Studies. 1-2 (1994).

[4] L. Edvinsson, P. Sullivan, Developing a Model for Managing Intellectual Capital, European Management Journal. 14-4 (1996).

[5] Z. Gorny, S. Kluska-Nawarecka, D. Wilk-Kolodziejczyk, K. Regulski, Diagnosis of casting defects using uncertain and incomplete knowledge, Archives Of Metallurgy And Materials. 55-3 (2010) 827-836.

[6] S. Kluska-Nawarecka, K. Regulski, M. Gurda, G. Lesniak, M. Krzyzak, System of semantic integration of non-structuralized documents in natural language in the domain of metallurgy, Archives of Metallurgy and Materials. 58-3 (2013) 927-930.

DOI: 10.2478/amm-2013-0103

[7] S. Kluska-Nawarecka, D. Wilk-Kolodziejczyk, K. Regulski, G. Dobrowolski, Rough Sets Applied to the Rough Cast System for Steel Castings, Intelligent Information and Database Systems, ACIIDS 2011 Pt II. 6592 (2011) 52-61.

DOI: 10.1007/978-3-642-20042-7_6

[8] B. Sniezynski, D. Kluska-Nawarecka, D. Wilk-Kolodziejczyk, The use of LPR (logic of plausible reasoning) to obtain information on innovative casting technologies, Archives of Civil and Mechanical Engineering. 14-1 (2014) 25-31.

DOI: 10.1016/j.acme.2013.05.011

[9] K. Regulski, S. Kluska-Nawarecka, Heuristic models of the toughening process to improve the properties of non-ferrous metal alloys, Archives of Metallurgy and Materials. 58-3 (2013) 849-852.

DOI: 10.2478/amm-2013-0085

[10] M. Warmuzek, K. Regulski, A Procedure for in situ Identification of the Intermetallic AITMSi Phase Precipitates in the Microstructure of the Aluminum Alloys, Praktische Metallographie-Practical Metallography. 48-12 (2011) 660-683.

DOI: 10.3139/147.110045

[11] Z. Jančíková, O. Zimný, P. Koštial, Prediction of Metal Corrosion by Neural Networks, Metalurgija. 52-3 (2013) 379-381.