A data-driven generic simulation model for logistics-embedded assembly manufacturing lines q Juyoung Wy a , Sangwon Jeong a , Byung-In Kim a,⇑ , Junhyuk Park a , Jaejoon Shin a , Hyunjoong Yoon b , Sujeong Lee c a Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, 790-784, Republic of Korea b School of Mechanical and Automotive Engineering, Catholic University of Daegu, Daegu, 712-902, Republic of Korea c Mechatronics & Manufacturing Center, Samsung Electronics Co., Suwon, Kyunggi, 441-742, Republic of Korea article info Article history: Received 28 April 2009 Received in revised form 13 September 2010 Accepted 18 October 2010 Available online 23 October 2010 Keywords: Generic simulation Logistics Assembly lines abstract Simulation has been used to evaluate various aspects of manufacturing systems. However, building a simulation model of a manufacturing system is time-consuming and error-prone because of the complex- ity of the systems. This paper introduces a generic simulation modeling framework to reduce the simu- lation model build time. The framework consists of layout modeling software and a data-driven generic simulation model. The generic simulation model was developed considering the processing as well as the logistics aspects of assembly manufacturing systems. The framework can be used to quickly develop an integrated simulation model of the production schedule, operation processes and logistics of a system. The framework was validated by developing simulation models of cellular and conveyor manufacturing systems. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Simulations have been used for various purposes in manufac- turing. They are used for strategic capacity planning, automation systems design, manufacturing process validation, and evaluation of various manufacturing execution scenarios. They can be used to analyze how system performance is affected by the layout con- figuration, the number of material handling resources used, the resource operating policies, and the usage of different types of material handling systems (MHS). A typical example simulation study can be found in Mackulak and Savory (2001). However, a simulation model that encapsulates the details of a manufacturing system is very time-consuming to build and debug. Engineers and researchers typically build simulation models with their own style based on their own experiences, without consider- ation of reusability, and the models are sometimes error-prone. The severe competitive pressures in the manufacturing industry require much quicker turnarounds for simulation projects. In order to cope with this challenge, we recently proposed a data-driven generic simulation modeling framework for semiconductor fabri- cation lines (Kim et al., 2009). As Mackulak, Lawrence, and Colvin (1998) stated, using a generic simulation model has two primary advantages: quick model construction and the reuse of more accu- rate (bug-free) models. This paper applies the framework to assembly manufacturing lines with development of a data-driven generic simulation model for the lines. The generic model described in this paper was devel- oped with in-depth consideration of the logistics aspects, i.e., the material flows. The data representation scheme for the generic simulation model and the logical flow of the model are presented. The remainder of this paper is organized as follows: A brief lit- erature review of the simulation program generator and generic simulation models is provided in Section 2. After our proposed generic modeling framework is briefly described in Section 3, the generic simulation model is presented for logistics-embedded assembly manufacturing lines in Section 4. Section 5 discusses the model verification and application of the proposed framework. Section 6 contains concluding remarks. 2. Literature review Various approaches have been used to reduce the simulation model build time. A simulation program generator can automati- cally generate simulation models in the target simulation language based on user input. Mathewson (1984) defines a simulation pro- gram generator as ‘‘an interactive software tool that translates the logic of a model described in a relatively general symbolism into the code of a simulation language.’’ Pidd (1992) defines a data-driven generic simulation model as ‘‘one which is designed 0360-8352/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.cie.2010.10.011 q This manuscript was processed by Area Editor Paul Savory. ⇑ Corresponding author. Tel.: +82 54 279 2371; fax: +82 54 279 2870. E-mail address: bkim@postech.ac.kr (B.-I. Kim). Computers & Industrial Engineering 60 (2011) 138–147 Contents lists available at ScienceDirect Computers & Industrial Engineering journal homepage: www.elsevier.com/locate/caie