Development of an intelligent system for real-time diagnosis of manufacturing systems
Automated and efficient system diagnosis is important for a manufacturing system to achieve high yield and good product quality. After reviewing and analyzing various techniques used for manufacturing diagnosis, this work presents a hybrid diagnostic approach based on fuzzy set and graphical theory....
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | Theses and Dissertations |
| اللغة: | English |
| منشور في: |
2009
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/10356/19884 |
| الوسوم: |
إضافة وسم
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| الملخص: | Automated and efficient system diagnosis is important for a manufacturing system to achieve high yield and good product quality. After reviewing and analyzing various techniques used for manufacturing diagnosis, this work presents a hybrid diagnostic approach based on fuzzy set and graphical theory. In this approach, triangular fuzzy numbers (membership functions)were incorporated into a directed graph, thus forming a fuzzy directed graph with its nodes representing the system components. A #45;first search strategy for the identification of possible fault propagation paths was established. Using the membership functions attached, the real-time condition of a node can be easily assessed. A prototype FDG-based diagnostic system which utilizes the bespoke approach was developed. This approach also provides an avenue for the worst-first search strategy developed in this work to interface with system modeling tools. Further work was carried out to integrate the prototype system with DESIGN IDEF™, a commercial software for systems design. |
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