91 |
Hierarchical operational control of automated manufacturing systems李小龍, Lee, Siu-lung, James. January 1997 (has links)
published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy
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92 |
Adaptive Layer-based machiningYang, Zhengyi, 楊正宜 January 2003 (has links)
published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy
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93 |
A hybrid multi-agent system architecture for manufacturing cell controlTang, Hon-ping., 鄧漢平. January 2005 (has links)
published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy
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94 |
Multiple choice modular design when linear and separable constraints are presentZhu, Ji, 1964- January 1988 (has links)
In this thesis we give two extensions to the multiple choice modular design problem. In the first case, we consider the situation that parts are purchased from different vendors. In the second case, we consider the situation that linear and separable constraints are present in our model. We propose a heuristic for solving each of the problems. Some computational results are included.
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95 |
Integrating machine grouping and layout by using knowledge based system approachAl-Awadhi, Waleed January 1998 (has links)
No description available.
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96 |
Task difficulty assessment : a contribution towards improved buildability through simplificationMoore, David Ronald January 1996 (has links)
No description available.
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97 |
A hybrid multi-agent system architecture for manufacturing cell controlTang, Hon-ping. January 2005 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2005. / Also available in print.
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98 |
A genetic algorithm approach in distributed scheduling in multi-factory production networksChung, Sai-ho, January 2006 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.
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99 |
An innovative decision support system for CIM justification and optimisationNagalingam, Sev Verl January 1999 (has links)
Thesis (PhD) -- University of South Australia, 1999
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100 |
A hierarchical heuristic approach for machine loading problems in a partially grouped environmentLee, Jong Hwan 30 September 2004 (has links)
The loading problem in a Flexible Manufacturing System (FMS) lies in the allocation of operations and associated cutting tools to machines for a given set of parts subject to capacity constraints. This dissertation proposes a hierarchical approach to the machine loading problem when the workload and tool magazine capacity of each machine are restrained. This hierarchical approach reduces the maximum workload of the machines by partially grouping them. This research deals with situations where different groups of machines performing the same operation require different processing times and this problem is formulated as an integer linear problem. This work proposes a solution that is comprised of two phases. In the first phase (Phase I), demand is divided into batches and then operations are allocated to groups of machines by using a heuristic constrained by the workload and tool magazine capacity of each group. The processing time of the operation is different for each machine group, which is composed of the same identical machines; however, these machines can perform different sets of operations if tooled differently. Each machine and each group of machines has a limited time for completing an operation. Operations are allocated to groups based on their respective workload limits. In the second phase (Phase II), demand is divided into batches again and operations are assigned to machines based on their workload and tool magazine capacity defined by Longest Processing Time (LPT) and Multifit algorithms. In Phase II, like Phase I, partial grouping is more effective in balancing the workload than total grouping. In partial grouping, each machine is tooled differently, but they can assist one another in processing each individual operation. Phase I demonstrates the efficiency of allocating operations to each group. Phase II demonstrates the efficiency of allocating operations to each machine within each group. This two-phase solution enhances routing flexibility with the same or a smaller number of machines through partial grouping rather than through total grouping. This partial grouping provides a balanced solution for problems involving a large number of machines. Performance of the suggested loading heuristics is tested by means of randomly generated tests.
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