{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/22387"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/22387","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies","abstract":"The Assembly sequencing problem (ASP) is part of the assembly planning process. The ASP is basically a large scale, combinatorial problem which is highly constrianed. The aim of this thesis is to automatically generate assembly sequence(s) for mechanical products. In this thesis, the CAD model of an assembly is represented or modeled as a label-rich graph. The assembly sequences are generated using graph grammar rules that are applied on the graph. The sequences are stored in a search tree and to find an optimal sequence multiple evaluation criteria like time, subassembly stability and accessibility measures are used. This research implements a novel tree search algorithm called "Ordered Depth First Search" (ODFS) to find an optimal assembly sequence in very low processing time. The software has successfully generated an optimized assembly sequence for an assembly with 14 parts.","abstract_html":"The Assembly sequencing problem (ASP) is part of the assembly planning process. The ASP is basically a large scale, combinatorial problem which is highly constrianed. The aim of this thesis is to automatically generate assembly sequence(s) for mechanical products. In this thesis, the CAD model of an assembly is represented or modeled as a label-rich graph. The assembly sequences are generated using graph grammar rules that are applied on the graph. The sequences are stored in a search tree and to find an optimal sequence multiple evaluation criteria like time, subassembly stability and accessibility measures are used. This research implements a novel tree search algorithm called "Ordered Depth First Search" (ODFS) to find an optimal assembly sequence in very low processing time. 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The ASP is basically a large scale, combinatorial problem which is highly constrianed. The aim of this thesis is to automatically generate assembly sequence(s) for mechanical products. In this thesis, the CAD model of an assembly is represented or modeled as a label-rich graph. The assembly sequences are generated using graph grammar rules that are applied on the graph. The sequences are stored in a search tree and to find an optimal sequence multiple evaluation criteria like time, subassembly stability and accessibility measures are used. This research implements a novel tree search algorithm called "Ordered Depth First Search" (ODFS) to find an optimal assembly sequence in very low processing time. 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The assembly sequences are generated using graph grammar rules that are applied on the graph. The sequences are stored in a search tree and to find an optimal sequence multiple evaluation criteria like time, subassembly stability and accessibility measures are used. This research implements a novel tree search algorithm called "Ordered Depth First Search" (ODFS) to find an optimal assembly sequence in very low processing time. 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