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Modeling and Analysis of Flexible Manufacturing Systems: A Simulation Study

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Conference

2015 ASEE Annual Conference & Exposition

Location

Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015

ISBN

978-0-692-50180-1

ISSN

2153-5965

Conference Session

Latest Trends and Implementations in Manufacturing Education

Tagged Division

Manufacturing

Page Count

19

Page Numbers

26.1162.1 - 26.1162.19

DOI

10.18260/p.24499

Permanent URL

https://peer.asee.org/24499

Download Count

3687

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Paper Authors

biography

Guanghsu A. Chang Western Carolina University

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Dr. Guanghsu A. Chang, Western Carolina University -
Dr. Chang is an associate professor in the Department of Engineering and Technology at Western Carolina University. He has spent the last 21 years in teaching industrial and manufacturing engineering programs. He earned his MSIE, and Ph.D. degrees from the University of Texas at Arlington. His research interests include robotic applications, manufacturing automation, Design for Assembly (DFA), and Case-Based Reasoning (CBR) applications. He was a vice president of Southern Minnesota APICS (2009-2012) and faculty advisor of APICS student chapter at Minnesota State University, Mankato.

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William R. Peterson WRP Associates

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Abstract

Modeling and Analysis of Flexible Manufacturing Systems: A Simulation Study AbstractFlexible Manufacturing Systems (FMS) are highly modular reconfigurable systems, consisting ofa group of processing workstations (such as CNC machining centers), and interconnected by anautomated material handling and storage system. The adoption of a Flexible ManufacturingSystem involves a big investment and a high degree of uncertainty for today’s factories. With theaim of combining production flexibility and productivity, the design decisions of a flexiblemanufacturing system must be based on FMS system performance. However, the currentliterature does not provide enough attention to analyze the system performance in a Flexiblemanufacturing system with different layout configurations. Obviously, deterministic modelsbased on discrete-event simulation can be utilized to design production systems such as FMSs.In this research, ProModel software is used to simulate different models and evaluate the systemperformance in different FMS layouts. Based on the simulation models, we investigated theeffectiveness and efficiency of FMS including the following system performance metrics such asmanufacturing lead time (MLT), resource utilization, inventory and queue levels, throughput,bottleneck analysis, and number of workstations. However, these decisions of FMS design arecritical and to be investigated in initial phase with extreme care ensuring that the designed FMSwill successfully fulfill the demands of fluctuating market. Finally, this paper presents a casestudy performed for performance evaluation of an existing manufacturing system. The resultshows that the simulation models can effectively help the users to rapidly response to the mix ofpart styles and the change of the demand patterns..

Chang, G. A., & Peterson, W. R. (2015, June), Modeling and Analysis of Flexible Manufacturing Systems: A Simulation Study Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24499

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