Manufacturers need to deploy their assembly systems in a timely manner to cope with expedited product development. Design of such responsive assembly systems consists of generation
of assembly/subassembly operations and their hierarchies, operation-machine assignment, selections of machine types and quantities, and the material flow among machines. Exploration of all
the feasible solutions to the assembly operations and their hierarchical relationships is vital to optimization of system designs. This research developed a theoretical framework based on
a recursive algorithm to automatically generate all feasible and non-redundant assembly hierarchies efficiently, thereby investigating its impact on assembly system designs. Then this
research further discussed the potential applications of the recursive framework in system optimization including joint determination of optimal assembly operations, operation-machine
assignment, machine types and quantities, and the material flows among machines. The work was also extended to the optimization of assembly systems for the products with complex liaison
relations and product families. / A Thesis submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the Master of Science. / Fall Semester 2015. / November 16, 2015. / assembly hierarchy, assembly system, generation algorithm, product family, system optimization / Includes bibliographical references. / Hui Wang, Professor Directing Thesis; Okenwa Okoli, Committee Member; Arda Vanli, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_291304 |
| Contributors | Jiang, Zhengqian (authoraut), Wang, Hui (professor directing thesis), Okoli, Okenwa (committee member), Vanli, Omer Arda, 1976- (committee member), Florida State University (degree granting institution), FAMU-FSU College of Engineering (degree granting college), Department of Industrial and Manufacturing Engineering (degree granting department) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (75 pages), computer, application/pdf |
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