Development of a step feature-based intelligent process planning system for prismatic parts

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2005

Author

Amaitik, Saleh Muhammed

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Computer aided process planning (CAPP) is generally acknowledged as a significant activity to achieve Computer Integrated Manufacturing (CIM). In coping with the dynamic changes in the modern manufacturing environment, the awareness of developing integrated and intelligent CAPP systems has been raised in an attempt to generate more successful implementation of intelligent manufacturing systems. The main objective of this research work has been to develop an integrated intelligent process planning system that helps designers and process planners to improve their design and planning in the early stages of the product life cycle. In order to achieve this goal, the following specific objectives have been accomplished: (1) Developed a STEP-based feature modeler for building mechanical parts using high-level 3D solid features as the basic design entities. The modeler is capable of generating high-level product data in XML format according to ISO 10303-AP224 standard. This file can be used to integrate into CAPP/CAM systems without using a complex feature recognition process. (2) Developed a STEP-based intelligent process planning system for prismatic parts. The system maps STEP AP224 XML data file and produces the corresponding machining operations to generate a digital process plan in XML format according to ISO 14649 (STEP-NC) standard. A Hybrid approach of most recent techniques of artificial intelligence (neural networks, fuzzy logic and rule-based) is used as the inference engine of the developed system. Three neural network models are implemented to select machining operations, cutting tools, and machine tools. Several fuzzy logic models are utilized to select machining parameters for different machining operations, work material, and tool material combinations. The rule-based functions are utilized to perform operation sequence and setup planning. An object-oriented

Subject Keywords

Machine design and drawing.

URI

http://etd.lib.metu.edu.tr/upload/12606104/index.pdf
https://hdl.handle.net/11511/15150

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

S. M. Amaitik, “Development of a step feature-based intelligent process planning system for prismatic parts,” Ph.D. - Doctoral Program, Middle East Technical University, 2005.