Journal of Manufacturing Systems 28 (2009) 115122Technical paperThe simulation design and analysis of a Flexible Manufacturing System with Automated Guided Vehicle SystemInsup Um, Hyeonjae Cheon, Hongchul Lee Division of Information Management Engineering, Korea University, 136-701 Seoul, South Koreaa r t i c l e i n f o a b s t r a c tArticle history:Available online 30 June 2010Keywords:SimulationFlexible Manufacturing System Automated Guided Vehicle System Multi Objective Nonlinear Programming Evolution StrategyThis paper presents the simulation design and analysis of a Flexible Manufacturing System (FMS) with an Automated Guided Vehicle system (AGVs). To maximize the operating performance of FMS with AGVs, many parameters must be considered, including the number, velocity, and dispatching rule of AGV, part- types, scheduling, and buffer sizes. Of the various critical factors, we consider the following three: (1) minimizing the congestion; (2) minimizing the vehicle utilization; and (3) maximizing the throughput. In this paper, we consider the systematic analysis methods that combine a simulation-based analytic and optimization technique that is Multi-Objective Non-Linear Programming (MONLP) and Evolution Strategy (ES). MONLP determines the design parameters of the system through multi-factorial and regression analyses. ES is used to verify each parameter for simulation-based optimization. A validation test for the two methods is conducted. This method-based approach towards design yields the correct experimental results, ensures confidence in the specification of design parameters and supports a robust framework for analysis.Crown Copyright 2010 Published by Elsevier Ltd on behalf of The Society of Manufacturing Engineers.All rights reserved.1. IntroductionA Flexible Manufacturing System (FMS) consists of a Numeri- cally Controlled (NC) machine, a Material Handling System (MHS), and a computer control system for integrating the NC machine and the MHS 1. The Integration of these machines and facilities gener- ally involves the use of a controller, complex software and an over- all computer control network that coordinates the machine tools, the material handling, and the parts 2,3. Material handling in FMS is becoming easier with advances in automated-machine technol- ogy. The rapid development in technology presents manufacturing firms with a variety of alternatives for in-plant transportation 4. In FMS, the Automated Guided Vehicle system (AGVs) is an excellent choice for MHS because of its automation of loading and unloading, flexibility in path movement, ease of modification of the guide-path network and computer control. AGVs can be used in two different ways. The first approach is to attach a part to the AGV that helps to execute all manufacturing processes by carrying the part from station to station. In this approach, the AGV is freed only after all the processes are completed for the part. The second approach is to use the vehicle only for moving the part from one station to another. The vehicle is assigned to the part only for a Corresponding author. Tel.: +82 2 3290 3389.E-mail addresses: uis27korea.ac.kr (I. Um), slashkorea.ac.kr (H. Cheon), hcleekorea.ac.kr (H. Lee).single trip 4. In this paper, we analyze the latter case for the FMS with AGVs, because the required number of vehicles is significantly less than in the former case.FMS are complex and expensive systems that require an accurate designing phase. In particular, it is important to closely examine the dynamic behavior of the different FMS components to predict the performance of the production system 5. Simulation analysis is perhaps the best technique to use for an intricate system that cannot be easily described by analytical or mathematical models 6,7.There are a number of commercially available software tools or simulators for assisting in the design and analysis of FMS 8. There are two broad approaches in such software. One is the use of a general simulation language, such as GPSS/H, SLAM II, SIMAN IV, SIMULA, etc., to build specific FMS simulation software or simulators. The other is the direct use of an FMS simulator that has been developed using some general computer languages such as FORTRAN, Pascal, or C or even some general simulation language that is combined with C, LISP, or PROLOG, to yield applications such as AutoMod II, Simfactory II.5, FACTOR, FMS+, and MAST, for simulating manufacturing systems or FMS 9.Many researchers have suggested various approaches for FMS design and analysis 10,11.