Applicability of Business Rules to Production Management in Foundries

• Autorzy: Stawowy A. , Duda J. , Wrona R.

Identyfikatory

DOI

10.1515/afe-2016-0008

• Języki publikacji: EN

Abstrakty

EN

The size and complexity of decision problems in production systems and their impact on the economic results of companies make it necessary to develop new methods of solving these problems. One of the latest methods of decision support is business rules management. This approach can be used for the quantitative and qualitative decision, among them to production management. Our study has shown that the concept of business rules BR can play at most a supporting role in manufacturing management, but alone cannot form a complete solution for production management in foundries.

Słowa kluczowe

EN

application of information technology; foundry industry; operation management; business rules

PL

zastosowanie technologii informatycznych; przemysł odlewniczy; zarządzanie operacyjne; reguły biznesowe

• Wydawca: Komisja Odlewnictwa Polskiej Akademii Nauk Oddział w Katowicach
• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2016
• Tom: Vol. 16, iss. 1
• Strony: 85--88
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Stawowy A.

• AGH University of Science and Technology, Faculty of Management, Gramatyka 10, 30-067 Krakow, Poland

autor

Duda J.

• AGH University of Science and Technology, Faculty of Management, Gramatyka 10, 30-067 Krakow, Poland

autor

Wrona R.

• AGH University of Science and Technology, Faculty of Foundry Engineering, Reymonta 23, 30-059 Krakow, Poland

Bibliografia

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• [2] Boyer, J. & Mili, H. (2011). Introduction to Business Rules. In Agile Business Rule Development. Berlin Heilderberg: Springer-Verlang. DOI 10.1007/978-3-642-19041-4_1.
• [3] Cheng, J. & Chou, C. (2008). A real-time inventory decision system using Western Electric run rules and ARMA control chart. Expert Systems with Applications 35(3), 755-761. DOI: 10.1016/j.eswa.2007.07.019.
• [4] Dilworth, J.B. (1992). Operations management. New York: McGraw-Hill.
• [5] ISA. (2007). ISA Draft TR 88/95.00.01, Batch Control and Enterprise-Control System Integration, Using ISA-88 and ISA-95 Together. Research Triangle Park: Systems and Automation Society.
• [6] Metaxiotis, K., Askounis, D. & Psarras, J. (2001). Expert systems in production planning and scheduling: a state-of-the-art survey. Journal of Intelligent Manufacturing 13(4), 253-260.
• [7] Kluska-Nawarecka, S. & Regulski, K. (2006). Diagnosis of defects in castings using expert system CastExpert. (In Polish). Retrieved May 20, 2015, from http://regulski.padlock.pl/pliki/instytut_odlewnictwa.pdf
• [8] Or, I. (1993). Development of a Decision Support System for maintenance planning. In Holsapple C.W. et al. (Eds.), Recent developments in Decision Support Systems (505–533). Berlin Heilderberg: Springer-Verlang.
• [9] Qian, Y., Xu, L., Li, X., Lin, L. & Kraslawski, A. (2008). LUBRES: An expert system development and implementation for real-time fault diagnosis of a lubricating oil refining process. Expert Systems with Applications 35(4), 1252-1266. DOI: 10.1016/j.eswa.2007.07.061.
• [10] Ross, R.G. (2003). Principles of the Business Rule Approach. Boston: Addison Wesley.
• [11] Stawowy, A., Wrona, R. & Ronduda, M. (2011). Classification of foundry clients using business rules approach. Archives of Foundry Engineering 11(4), 145-148.
• [12] Venkatraman, R. & Venkatraman, S. (2000). Rule-based system application for a technical problem in inventory issue. Artificial Intelligence in Engineering 14(2), 143-152. DOI: 10.1016/S0954-1810(00)00003-0.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.