Design of dynamic facility layouts under production and material handling capacity constraints

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Issue Date
2014-12
Embargo End Date
Authors
Shah, Dhagash S.
Advisor
Krishnan, Krishna K.
Citation
Abstract

For a manufacturing facility to be competitive in today’s market driven conditions, it is inevitable that it meet the market’s demand with optimal resources within the required time. Resources and its utilization can be limited by logistic constraints, such as facility layout and material handling, and production constraints, such as machine capacity and type of machines. Research until now has focused on addressing demand requirements under static and dynamic conditions. However, facility layout approaches have assumed infinite capacities for the production system in determining the layout. In addition, facility layout research does not consider material handling capacity consideration in determining feasibility and adaptability of layout. This study conducts research on addressing dynamic facility layout designs in which the demand varies from one time period to the next while taking into consideration finite capacity constraints for both the logistics (facility layout and material handling system) and production systems (machine capacities-operational limitations). The research used a genetic algorithm and CRAFT program to develop the facility layout for each time period. Simulation studies are conducted for the developed layout to determine if demand can be met for the given time period in Chapter 2. The research also develops functions that can be used to evaluate the costs of changes in the parameters, such as increased production capacity, increased material handling capacity, or a combination of both parameters, to meet the demand. The research also evaluates alternative sequence as a parameter considered to design a dynamic facility layout in Chapter 3. The research develops and proposes a forward pass and backward pass approach to design dynamic facility layouts in Chapter 4. The aim of this research is to minimize the cost of meeting demand over a given time period under dynamic conditions.

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Thesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering
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