Business rules management system for enterprises in iron and steel industry

by

Business rules management system for enterprises in iron and steel industry

Andrzej Macioł, Bartłomiej Gaweł, Rafał Jankowski

Faculty of Management, AGH University of Science and Technology,,ul. Gramatyka 10, 30-067 Kraków, Poland.

DOI:

https://doi.org/10.7494/cmms.2009.2.0251

Abstract:

The central idea behind Business Rules Engines (BRE) or Business Rules Management Systems (BRMS) is that any organization has a logic that is used to carry out its operational and managerial tasks. The major objective of modern business rules management systems is to allow describing business and technological processes independently of the software system which has to be implemented. Nowadays it is possible to automate some of the processes by implementing appropriate ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), SCM (Supply Chain Managment) or WfMS (Workflow Management System) solution. But there are still processes and decisions which are non-routine or cannot be well described by an appropriate semantic language. In this paper we present the idea of Interference with Queries methodology. Based on this method we propose the framework which brings together concepts of business rules and expert systems and decision-support systems which help business experts with business rules implementation in the natural language. We formulate special, graphical language, close to natural one, for describing business and technological processes. Completeness and preciseness of processes which were described in this language, are validated by BRMS using simulation for instance. Properly described processes are ready to be used by IT system without IT experts help.

Cite as:

Macioł, A., Gaweł, B., Jankowski, R., (2009). Business rules management system for enterprises in iron and steel industry. Computer Methods in Materials Science, 9(2), 335 – 340. https://doi.org/10.7494/cmms.2009.2.0251

Article (PDF):

Keywords:

Business rules management, Expert systems, Inference engine, Metal forming technology

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