Thesis (M.S.)--University of Kentucky, 2002. / Title from document title page. Document formatted into pages; contains viii, 66 p. : ill. Includes abstract. Includes bibliographical references (p. 64-65).

Thesis (Ph. D.)--Lehigh University, 2003. / Includes vita. Includes bibliographical references (leaves 80-85).

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Thesis (PhD)--University of South Australia, 1996

Ph.D thesis 1970 from the Dept. of Computing Science, University of Adelaide / 134 leaves : ill., graphs, appendices / Title page, contents and abstract only. The complete thesis in print form is available from the University Library.

Assembly Sequence Planning (ASP) is part of Assembly Planning. The assembly sequence is the most important part of an assembly plan. Assembly has an important share in both lead time and cost of a product. Therefore, its optimisation is necessary to ensure the competitivity of manufactured goods. The aim of this thesis is the optimisation of assembly sequences for mechanical products, for real/realistic problems and constraints. This thesis represents an integrated approach in assembly sequence planning and optimisation. It tackles real problems by building the generality in the models. The ASP problem is a large scale, highly constrained, combinatorial problem, with an extraordinarily diverse character. Assembly can address sequential or non-sequential, linear or non-linear, monotone or non-monotone, coherent or non-coherent assembly plans or any combination of those, involving rigid, elastic, non elastic, solid, liquid or gaseous components or subassemblies. To be applicable in practice and useful, an assembly sequence planning and optimisation algorithm has to be general enough to accommodate any type of assembly plan and component. For this reason, modelling becomes critically important. A model has been developed for the assembly process, to determine what the assembly process is in mathematical terms. A second model has been developed to model/represent assembly plans as chromosomes that encode any type and combination of assembly plans. Another model has been developed for modelling/representing products for assembly. This model constitutes the database containing all information necessary for generating feasible assembly sequences, for any type of component and subassembly. A framework has been developed for the definition of a fitness function to assess the quality of an assembly sequence and plan from optimisation criteria. Solving the ASP problem (prior to its optimisation), implies generating a sequence to assemble an n-part product given its description and a number of supplementary constraints. A guided search algorithm has been developed to solve the ASP problem. To optimise the ASP, Genetic Algorithms (GA) were used in this research. The GA has a classic structure and modified genetic operators: it only generates and manipulates legal and feasible chromosomes. An initial population of feasible chromosomes is generated through guided search. This population, then, undergoes transformations over a number of generations, through crossover and selection. The crossover, based on the guided search algorithm, is also designed to produce only legal chromosomes. The selection is a classical operation, through a weighed roulette algorithm. It operates on an extended population of parent and children chromosomes. The output of the GA is a population of chromosomes with a high fitness value, corresponding to optimal/near optimal assembly sequences, from which the best one is selected. A number of examples are used in each chapter to illustrate each significant aspect considered. A final example illustrates the application of the whole algorithm to produce optimised assembly sequences for an industrial-size product. / thesis (PhD)--University of South Australia, 2003.

Thesis (M.S.)--Ohio University, August, 2000. / Title from PDF t.p.