SIMPLIFICATION AND AGGREGATION STRATEGIES APPLIED FOR FACTORY ANALYSIS IN CONCEPTUAL PHASE USING SIMULATION Matías Urenda Moris Amos H.C. Ng Jacob Svensson Virtual Systems Research Centre University of Skövde Skövde, SE-541 28, SWEDEN ABSTRACT Despite that simulation possesses an establish background and offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the conceptual phase of factory design. This paper presents how simplification and aggregation strate- gies are incorporated in a modeling, simulation and analy- sis tool, with the aim of supporting decision making in conceptual phase. Conceptual modeling is guided by a framework using an object library with generic drag and drop system components and system control objects. Data inputs are simplified by the use of Effective Process Time distributions and a novel aggregation method for product mix cycle time differences. The out coming specification is through a Web Service interface handle by modeling sys- tem architecture, automatically generating a simulation model and analysis. Case studies confirm a breakthrough in project time reduction without appreciable effects on the model’s fidelity. 1 INTRODUCTION Today, industry has very limited support from working procedures, methods, and tools for analysis of complete plants in early program stages. This leads to difficulties in predicting the consequences from the early decisions that are basic for robust, flexible and cost effective production. Despite that simulation possesses an establish background and offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the early conceptual phase of factory design (McNally and Heavey 2004). Unfortunately, simulation analysis for system design is used in later phases when cost and system performance are more or less locked. There are several reasons to the poor use of simulation at this phase. Industrial experience shows that decisions are many times based on heuristic and historical approaches. If tools are used they are mainly limited to analytical tools. The arguments suggesting an analytical solution, instead of a discrete event simulation (DES) approach, are among others a more effective use of time and the lack of detail process data (Jägstam and Klingstam 2002; Patchong et al. 2003). Remember that many conceptual models have a very short life span, due to the nature of the task which is evaluating different production concepts and control strategies towards each other. The production manager is therefore dependent on the help of a simulation expert and needs to order models for the different concepts. If the company has in-house experts there is still a time- consuming dialog and process between the manager and the expert. That particular dialog is somewhat intricate. The simulation specialist, used to work with detail models for planning and scheduling of existing production lines, gets into an “ethical dilemma”. Not used to build simple models he has his own lack of credibility to the models an the use of estimated data. The troubles with models at con- ceptual phase are therefore summarized in lack of data, time and knowledge. Can these problems be overcome or should production managers continue to design production lines based on guesses, “this is the way we have always done” attitude or be limited to basic queuing network mod- els which will most certain result in bigger assumptions than a DES model? The objective of this research is to overcome these problems and “frontload” the use of virtual methods to analyze complete factories. The project targets were to in- crease the use of simulation analysis, make them faster and more accurate in the early conceptual phase. This is through developing a new work method and a correspond- ing toolset that tightly integrates model abstraction, input data management and simulation-based optimization under an innovative framework that is specifically designed for production system’s designer/managers in the conceptual design phase. As a part of the research work within the Factory Analyses in ConcepTual phase using Simulation (FACTS) project, which is funded by VINNOVA in Swe- den (see Acknowledgement) and took place between Janu- 1913 978-1-4244-2708-6/08/$25.00 ©2008 IEEE Proceedings of the 2008 Winter Simulation Conference S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds.