Production scheduling in ERP systems: An AI-based approach to face the gap

Authors: Metaxiotis K.S.; Psarras J.E.; Ergazakis K.A.

Source: Business Process Management Journal, Volume 9, Number 2, 2003 , pp. 221-247(27)

Publisher: Emerald Group Publishing Limited

Buy & download fulltext article:

Price: $38.00 plus tax (Refund Policy)

Abstract:

In the current competitive environment, each company faces a number of challenges: quick response to customers' demands, high quality of products or services, customers' satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data-processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today's manufacturing and service industries. In this paper, the authors propose a knowledge-based system for production-scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.

Keywords: Resource Management; Production; Scheduling; Knowledge-Based Systems

Document Type: Research article

DOI: http://dx.doi.org/10.1108/14637150310468416

Publication date: 2003-04-30