Keywords

Automate, Custom software, Data, Data collection, Input data, Manufacturing, Modeling, Simulation

Abstract

In past years many industries have utilized simulation as a means for decision making. That wave has introduced simulation as a powerful optimization and development tool in the manufacturing industry. Input data collection is a significant and complex event in the process of simulation. The simulation professionals have grown to accept it is as a strenuous but necessary task. Due to the nature of this task, data collection problems are numerous and vary depending on the situation. These problems may involve time consumption, lack of data, lack of structure, etc. This study concentrates on the challenges of input data collection for Discrete Event Simulation in the manufacturing industry and focuses particularly on speed, efficiency, data completeness and data accuracy. It has been observed that many companies have recently utilized commercial databases to store production data. This study proposes that the key to faster and more efficient input data collection is to extract data directly from these sources in a flexible and efficient way. An approach is introduced here to creating a custom software tool for a manufacturing setting that allows input data to be collected and formatted quickly and accurately. The methodology for the development of such a custom tool and its implementation, Part Data Collection, are laid out in this research. The Part Data Collection application was developed to assist in the simulation endeavors of Lockheed Martin Missiles and Fire Control in Orlando, Florida. It was implemented and tested as an aid in a large simulation project, which included modeling a new factory. This implementation resulted in 93% reduction in labor time associated with data collection and significantly improved data accuracy.

Notes

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Graduation Date

2004

Semester

Spring

Advisor

Mollaghasemi, Mansooreh

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Degree Program

Industrial Engineering and Management Systems

Format

application/pdf

Identifier

CFE0000025

URL

http://purl.fcla.edu/fcla/etd/CFE0000025

Language

English

Release Date

May 2004

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science; Engineering and Computer Science -- Dissertations, Academic

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Engineering Commons

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