Intelligent materials selection inconceptural design
Dissertant
University
University of Technology
Faculty
-
Department
Department of Production Engineering and Metallurgy
University Country
Iraq
Degree
Ph.D.
Degree Date
2006
English Abstract
Materials selection is an integral part of the design of a product.
The needs to combine selection of materials (SM) processes during the early stages of the design have previously been realized.
The work documented in this dissertation is an attempt to ensure that there is no disconnect between function oriented design and the material that are applicable to that design.
Since the information in the conceptual stage is fuzzy and ambiguous and properties are dealt within ranges, which make the selection process very difficult.
The work proposes methodology which helps a designer to select the best sub-group material that satisfy the design requirements in the early design stages which help to move the decisions on selection of materials to the explore conceptual solution.
The developed methodology serves the concurrent engineering (CE) Philosophy to take the correct decision early in the design process.
This leads in avoiding additional cost, the transient mutations in manufacturing stage and improving the quality of product.
The developed methodology consists of two concurrent SM methods ; the first one is neural network selection of materials method which helps the designer in selecting correct sub-group materials when the design concept is in its beginning.
Neural network tool was being used to resemble the human's intuitive ability in solving problems though learning.
An algorithm was being built to perform SM where design is still a concept and only described verbally.
The second one was concurrent qualitative selection of materials method (CQM).
The method is modified from quantitative method called weighted property method used for selecting materials in the detailed stage.
The method was modified to qualitative method, which means that the input data for the materials property of the design must be qualitative data which consisting of groups or sub-groups material, range value properties-and approximate values.
Two case studies (turbine blades and aircraft skin) were examined and satisfactory results were obtained.
The results of the second developed method supports the results obtained from the first method but in a more accurate manner.
This is because the neural network environment resembles the human approach in selecting material in the conceptual stage.
Main Subjects
Topics
American Psychological Association (APA)
Abbas, Suad Hamzah. (2006). Intelligent materials selection inconceptural design. (Doctoral dissertations Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305819
Modern Language Association (MLA)
Abbas, Suad Hamzah. Intelligent materials selection inconceptural design. (Doctoral dissertations Theses and Dissertations Master). University of Technology. (2006).
https://search.emarefa.net/detail/BIM-305819
American Medical Association (AMA)
Abbas, Suad Hamzah. (2006). Intelligent materials selection inconceptural design. (Doctoral dissertations Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305819
Language
English
Data Type
Arab Theses
Record ID
BIM-305819