AI SearchExpert system for die and mold making cost estimation
Call Number: AIT Thesis no.ISE-99-20 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. ISE-99-20Publication details: Bangkok : Asian Institute of Technology, 1999Description: 194 p.: illSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology Summary: This thesis study presents an attempt to develop the knowledge based for plastic injection mold cost estimation. The system is developed in the form of a decision tree structure. Tlu·ough the use of a decision tree structure, numerous interrelated variables and technical data in the injection mold cost estimation process are organized and presented. When the features of a plastic part are input, this system will generate an estimated cost of inj ection mold required to produce the part. The knowledge acquisition has been done from expe1ts in the domain, textbooks, technical papers, database, reports, and real mold making study. The acquired knowledge has been organized by decision tree in seven different modules. This knowledge base system is based on production rules where both declarative and heuristic knowledge has been used. There are approximately 650 production rules in the knowledge base and data are driven forward chaining has been used as searching strategy.
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22-AIT Thesis (Replacement)
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Asian Institute of Technology Library AIT Publications | AIT Thesis no.ISE-99-20 (Browse shelf(Opens below)) | 3 | Available | 30050120814644 | |||||||||||||
40-Archives
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20-AIT Publication
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Asian Institute of Technology Library AIT Publications | AIT Thesis no.ISE-99-20 (Browse shelf(Opens below)) | 1 | Available | 30050121007297 |
Thesis (M.Eng.) - Asian Institute of Technology
A thesis submitted in partial fulfillment of requirements for the degree of Master of Engineering, School of Advanced Technologies
This thesis study presents an attempt to develop the knowledge based for plastic injection mold cost estimation. The system is developed in the form of a decision tree structure. Tlu·ough the use of a decision tree structure, numerous interrelated variables and technical data in the injection mold cost estimation process are organized and presented. When the features of a plastic part are input, this system will generate an estimated cost of inj ection mold required to produce the part. The knowledge acquisition has been done from expe1ts in the domain, textbooks, technical papers, database, reports, and real mold making study. The acquired knowledge has been organized by decision tree in seven different modules. This knowledge base system is based on production rules where both declarative and heuristic knowledge has been used. There are approximately 650 production rules in the knowledge base and data are driven forward chaining has been used as searching strategy.
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