Design knowledge acquisition: task analysis and a partial implementation |
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| Institution: | 1. Department of Control and Systems Engineering, School of Management and Engineering, Nanjing University, Nanjing, 210093, PR China;2. School of Information Engineering, Nanjing Audit University, Nanjing, 211815, PR China;3. College of Artificial Intelligence, Southwest University, Chongqing, 400715, PR China;1. Marine and Freshwater Research Centre, Galway-Mayo Institute of Technology, Ireland;1. College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou 730070, PR China;2. State Key Laboratory of Advanced Processing and Recycling of Non-ferrous Metals, Key Laboratory of Nonferrous Metal alloys and Processing, Ministry of Education, School of Materials Science & Engineering, Lanzhou University of Technology, Lanzhou 730050, China |
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| Abstract: | Design is conceptualized as an ill-structured process that requires diverse knowledge that is hard to acquire. Systematic analysis of design and the knowledge requirements it has in general and in the context of bridge design, shows that the knowledge needed can be semi-automatically acquired by using machine learning techniques. Although there are limitations to the approach, preliminary results in the bridge design domain are promising and can potentially transfer to other design domains. |
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