Labor and machine sizing through a Simulation-Expert-System-based Approach Wassim Masmoudi a , He ´di Chtourou b, * , Aref Y. Maalej a a Laboratoire des Syste `mes, Electro-Me ´ caniques, Ecole Nationale d’Inge ´nieurs de Sfax, BP W 3038 Sfax,Tunisia b De ´partement de Technologie, Institut Pre ´paratoire aux Etudes d’Inge ´nieurs de Sfax, Sfax,Tunisia Received 13 May 2005; received in revised form 25 May 2006; accepted 15 October 2006 Available online 4 December 2006 Abstract This work presents the development of an enhanced version of the Simulation-Expert-System-based Approach (SESA) previously used to solve the manufacturing system (MS) machine sizing problem. The SESA is improved by considering operator sizing along with machine sizing. The proposed approach consists in coupling an expert system (ES) with a sim- ulation tool. The main performance measures considered in this work are related to the manufacturing orders due dates. Accordingly, labor resources are now implemented in the MS simulation model and ES reasoning mechanism is adjusted in order to optimise both machine and operator quantities. Finally, an illustrative example showed the potential benefits of the approach enhancements through the enrichment of both simulation model and the expert system reasoning mechanism. Ó 2006 Elsevier B.V. All rights reserved. Keywords: Machine sizing; Labor sizing; Simulation; Performance measures; Expert system 1. Introduction The fierce competition in the industrial field impels the manufacturers, throughout the world, to continu- ously review their methods of manufacturing systems (MS) design and operation. This research work is inter- ested in one of the major MS design issues, required while designing a new or expanding an existing system [1]. It is related to the resource sizing problem defined as the specification of the number of each type of resources to be used in a production process for a given time period [2]. The approaches that tackled this problem can be classified in two principal categories: analytical and sim- ulation-based. Approaches belonging to the first category are based on mathematical models that oversimplify the studied MSs. Whereas, approaches of the second category ensure a more realistic representation of the manufacturing contexts even though many of them are strongly related to ‘‘trial and error’’. Some other 1569-190X/$ - see front matter Ó 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.simpat.2006.10.001 * Corresponding author. Tel.: +216 98 667 530; fax: +216 74 246 347. E-mail addresses: wassim_masmoudi@yahoo.fr (W. Masmoudi), hedi.chtourou@ipeis.rnu.tn (H. Chtourou), aref.maalej@enis.rnu.tn (A.Y. Maalej). Simulation Modelling Practice and Theory 15 (2007) 98–110 www.elsevier.com/locate/simpat