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Journal articles on the topic 'Design knowledge'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Cooper, Rachel. "Design Knowledge." Design Journal 4, no. 1 (2001): 1–2. http://dx.doi.org/10.2752/146069201789378478.

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2

Drucker, Johanna. "Knowledge Design." Design and Culture 6, no. 1 (2014): 65–83. http://dx.doi.org/10.2752/175470814x13823675225117.

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3

Linzner, Felix. "World. Knowledge. Design." Ethnologia Fennica 47, no. 1 (2020): 111–14. http://dx.doi.org/10.23991/ef.v47i1.91710.

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4

Addis, T. R. "Knowledge for design." Knowledge Acquisition 2, no. 2 (1990): 95–105. http://dx.doi.org/10.1016/s1042-8143(05)80006-8.

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5

Hunter, Bruce. "Knowledge and Design." Philosophy and Phenomenological Research 59, no. 2 (1999): 309. http://dx.doi.org/10.2307/2653674.

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6

Logan, B. S. "Conceptualizing design knowledge." Design Studies 10, no. 3 (1989): 188–95. http://dx.doi.org/10.1016/0142-694x(89)90037-9.

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7

Manzini, Ezio. "New design knowledge." Design Studies 30, no. 1 (2009): 4–12. http://dx.doi.org/10.1016/j.destud.2008.10.001.

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8

Yang, Cheng, Zheng Liu, Haobai Wang, and Jiaoqi Shen. "Reusing design knowledge based on design cases and knowledge map." International Journal of Technology and Design Education 23, no. 4 (2013): 1063–77. http://dx.doi.org/10.1007/s10798-013-9239-7.

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9

Nakakoji, Kumiyo, and Yasuhiro Yamamoto. "Knowledge Interaction Design for Creative Knowledge Work." Transactions of the Japanese Society for Artificial Intelligence 19 (2004): 154–65. http://dx.doi.org/10.1527/tjsai.19.154.

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10

Woo, Chi-Moon, Mi-Kyoung Kim, and Han-Jong Jun. "Design Knowledge Classification based BIM Design System Framework - Representation of Building Scale Estimation Design Knowledge -." Journal of the architectural institute of Korea planning & design 32, no. 7 (2016): 21–28. http://dx.doi.org/10.5659/jaik_pd.2016.32.7.21.

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11

Marshall-Baker, Anna. "Knowledge in Interior Design." Journal of Interior Design 31, no. 1 (2005): xiii—xxi. http://dx.doi.org/10.1111/j.1939-1668.2006.tb00412.x.

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12

Coyne, R. D., and J. S. Gero. "Design knowledge and context." Environment and Planning B: Planning and Design 12, no. 4 (1985): 419–42. http://dx.doi.org/10.1068/b120419.

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13

Cennamo, Katherine S. "Design as Knowledge Construction." Computers in the Schools 20, no. 4 (2003): 13–35. http://dx.doi.org/10.1300/j025v20n04_03.

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14

Yoshikawa, Hiroyuki. "Systematization of Design Knowledge." CIRP Annals 42, no. 1 (1993): 131–34. http://dx.doi.org/10.1016/s0007-8506(07)62409-3.

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15

Haron, Haryani, Mohd Nazri Mustafa, M. Hamiz, and Nor Diana Ahmad. "Modeling Product Design Knowledge." Advanced Science Letters 21, no. 10 (2015): 3132–36. http://dx.doi.org/10.1166/asl.2015.6453.

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16

Rutherford, James H., and Thomas W. Maver. "Knowledge-based design support." Automation in Construction 3, no. 2-3 (1994): 187–202. http://dx.doi.org/10.1016/0926-5805(94)90019-1.

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17

Akman, V., P. ten Hagen, J. Rogier, and P. Veerkamp. "Knowledge engineering in design." Computer-Aided Design 20, no. 7 (1988): 425. http://dx.doi.org/10.1016/0010-4485(88)90250-3.

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18

Kumar, B. "Knowledge-based design systems." Computing Systems in Engineering 2, no. 4 (1991): 425. http://dx.doi.org/10.1016/0956-0521(91)90009-t.

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19

Akman, Varol, Paul ten Hagen, Jan Rogier, and Paul Veerkamp. "Knowledge engineering in design." Knowledge-Based Systems 1, no. 2 (1988): 67–77. http://dx.doi.org/10.1016/0950-7051(88)90001-9.

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20

Heylighen, Ann, Francis Heylighen, Johan Bollen, and Mathias Casaer. "Distributed (design) knowledge exchange." AI & SOCIETY 22, no. 2 (2007): 145–54. http://dx.doi.org/10.1007/s00146-007-0122-5.

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21

Clibbon, Kelvin, and Ernest Edmonds. "Representing strategic design knowledge." Engineering Applications of Artificial Intelligence 9, no. 4 (1996): 349–57. http://dx.doi.org/10.1016/0952-1976(96)00038-3.

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22

Joo, Jae-Woo, and Dong-Woo Oh. "User Research Method for Service Design: From Conceptual Knowledge To Design Knowledge." Journal of the Ergonomics Society of Korea 31, no. 1 (2012): 15–21. http://dx.doi.org/10.5143/jesk.2012.31.1.15.

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23

Plappert, S., L. Hoppe, P. C. Gembarski, and R. Lachmayer. "APPLICATION OF KNOWLEDGE-BASED ENGINEERING FOR TEACHING DESIGN KNOWLEDGE TO DESIGN STUDENTS." Proceedings of the Design Society: DESIGN Conference 1 (May 2020): 1795–804. http://dx.doi.org/10.1017/dsd.2020.300.

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AbstractFor an optimal preparation of mechanical engineering students for their future work life, the use of problem-based methods in design teaching is investigated. Therefore an intelligent tutoring system for computer aided design education will be developed, which can automatically evaluate computer aided design models of design students. A knowledge-based engineering system will be used to assistance the design students in the execution of design tasks. Using a practice-oriented example, the application and the advantages for teaching will be verified and discussed.

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24

Gruber, Thomas R., and Paul R. Cohen. "Design for acquisition: principles of knowledge-system design to facilitate knowledge acquisition." International Journal of Man-Machine Studies 26, no. 2 (1987): 143–59. http://dx.doi.org/10.1016/s0020-7373(87)80088-3.

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25

Garcia, Ana Cristina Bicharra, and H. Craig Howard. "Acquiring design knowledge through design decision justification." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 6, no. 1 (1992): 59–71. http://dx.doi.org/10.1017/s0890060400002948.

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Currently design documentation rarely records the designer's decision process or the reasons behind those decisions. This paper describes an effort to improve design documentation by having the computer act as an intelligent apprentice to the designer to capture the rationale during the design process. The apprentice learns about the features that make a specific case different from the standard. Whenever the designer proposes a design action that differs from the apprentice's expectations, the interface will ask for the designer for justifications to explain the differences. Later queries for

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26

Yinhua, Hai. "A Framework Design of Mongolian Idioms Knowledge Base." International Journal of Machine Learning and Computing 4, no. 5 (2014): 428–32. http://dx.doi.org/10.7763/ijmlc.2014.v4.449.

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27

Zechang Xiong, Zechang Xiong, Cheng Chen Cheng Chen, Haojie Feng Haojie Feng, Xiong Xu Xiong Xu, and Zhenyan Jing Zhenyan Jing. "Architecture Design of Embedded Software IP Knowledge Base." 電腦學刊 35, no. 4 (2024): 259–76. http://dx.doi.org/10.53106/199115992024083504018.

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<p>Effective management and reuse of existing embedded software knowledge is vital for enhancing development efficiency. To better reuse embedded software knowledge, embedded software intellectual property is designed. Embedded software IP refers to a collection of reusable knowledge entities with intellectual property. Software IP knowledge base has been designed and implemented to store and manage software IP efficiently. The architecture design based on the microservice architectural pattern makes the IP knowledge base flexible and extensible. Specifically, considering software IP&amp

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28

SATO, Seiki, Satoshi SUZUKI, and Muneyoshi NUMADA. "3D Knowledge Design System in Product Design." Transactions of the Japan Society of Mechanical Engineers Series C 74, no. 745 (2008): 2107–13. http://dx.doi.org/10.1299/kikaic.74.2107.

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29

AOYAMA, Kazuhiro, and Tsuyoshi KOGA. "3318 Design Knowledge Template for Product Design." Proceedings of the JSME annual meeting 2008.4 (2008): 213–14. http://dx.doi.org/10.1299/jsmemecjo.2008.4.0_213.

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30

Maier, Ronald. "Modeling Knowledge Work for the Design of Knowledge Infrastructures." JUCS - Journal of Universal Computer Science 11, no. (4) (2005): 429–51. https://doi.org/10.3217/jucs-011-04-0429.

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During the last years, a large number of information and communication technologies (ICT) have been proposed to be supportive of knowledge management (KM). Several KM instruments have been developed and implemented in many organizations that require support by ICT. Recently, many of these technologies are bundled in the form of comprehensive, enterprise-wide knowledge infrastructures. The implementation of both, instruments and infrastructures, requires adequate modeling techniques that consider the specifics of modeling context in knowledge work. The paper studies knowledge work, KM instrumen

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31

Zhang, Dong Min, Zi Chao Yin, and Yu Chun Xu. "Knowledge Tracing Modeling for Product Design Knowledge Management." Applied Mechanics and Materials 483 (December 2013): 506–9. http://dx.doi.org/10.4028/www.scientific.net/amm.483.506.

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Knowledge management in advanced manufacturing industries is a complex process. The paper analyzes knowledge application scenarios in product development processing. There are complex relationships between knowledge, product, process and designers, which four key elements are proposed for knowledge tracing modeling. Knowledge tracing modeling based four key elements for product design knowledge management is studied carefully. The research for knowledge tracing modeling will enable software function development.

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32

Benaroch, Michel. "Roles of design knowledge in knowledge-based systems." International Journal of Human-Computer Studies 44, no. 5 (1996): 689–721. http://dx.doi.org/10.1006/ijhc.1996.0029.

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33

Nworie, John, and Francis Dwyer. "Knowledge management & instructional design optimizing organizational knowledge." Performance Improvement 43, no. 7 (2004): 27–32. http://dx.doi.org/10.1002/pfi.4140430709.

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34

Oxman, Rivka. "Prior knowledge in design: a dynamic knowledge-based model of design and creativity." Design Studies 11, no. 1 (1990): 17–28. http://dx.doi.org/10.1016/0142-694x(90)90011-z.

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35

Zhang, Dong Min, Yan Yun Wu, and Ye Huang. "Design Knowledge Reuse Strategies for Complex Equipment Design." Applied Mechanics and Materials 190-191 (July 2012): 74–77. http://dx.doi.org/10.4028/www.scientific.net/amm.190-191.74.

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Series products and variant products are the basic strategy for enterprise product development. Product designers reuse the knowledge, experience in the various stages of product development. The design reuse strategies for mechanical products are studied. The concepts of product design reuse level and product design reuse dimensions are presented. The enabling techniques for design reuse are concluded, including CBR, KM/KBE, design reuse modeling. A case-based design tool and a design knowledge management tool are developed based on studying product design reuse strategies.

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36

Ko, Jae Sung. "Design Phenomenological Methodology - Tacit Knowledge and Design Paradigm -." JOURNAL OF THE KOREAN SOCIETY DESIGN CULTURE 28, no. 2 (2022): 1–15. http://dx.doi.org/10.18208/ksdc.2022.28.2.1.

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37

Maher, Mary Lou, and Heng Li. "Automatically Learning Preliminary Design Knowledge from Design Examples." Computer-Aided Civil and Infrastructure Engineering 7, no. 1 (1992): 73–80. http://dx.doi.org/10.1111/j.1467-8667.1992.tb00418.x.

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38

Howard, H. Craig, Jenmu Wang, Francois Daube, and Taufiq Rafiq. "Applying design-dependent knowledge in structural engineering design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 3, no. 2 (1989): 111–23. http://dx.doi.org/10.1017/s0890060400001141.

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Recent knowledge-based expert systems for structural engineering design have focused on design-independent knowledge (abstract reasoning rules for designing), and while great strides have been made in that area, there is still a significant need to develop systems to take advantage of the wealth of knowledge contained in every substantial structural design. On the other hand, previous database-oriented design efforts have focused primarily on knowledge-poor databases of solutions, in which the traditional engineering handbook of solutions has simply been replaced by digital data. The challenge

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39

Kremer, Gerald, Ina Peter, Berkay Bingoel, and Rainer Stark. "Better Design through Shared Knowledge via Design Heuristics." Procedia CIRP 119 (2023): 957–62. http://dx.doi.org/10.1016/j.procir.2023.03.140.

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40

Walch, Michael, and Dimitris Karagiannis. "Design Thinking and Knowledge Engineering: A Machine Learning Case." International Journal of Machine Learning and Computing 10, no. 6 (2020): 765–70. http://dx.doi.org/10.18178/ijmlc.2020.10.6.1003.

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41

Kovalenko, O. E. "Knowledge based design of convergent systems of situational management." Mathematical machines and systems 3 (2019): 67–74. http://dx.doi.org/10.34121/1028-9763-2019-3-67-74.

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42

Kozhasova, N. L. "STUDENT TEACHER KNOWLEDGE AND ITS IMPACT ON TASK DESIGN." DULATY UNIVERSITY BULLETIN 2, no. 10 (2023): 36–41. http://dx.doi.org/10.55956/vzhm3266.

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This study looked at how student teachers created and altered mathematical assignments using their pedagogical and subject-specific knowledge of mathematics. It also looked at the connection between instructor expertise and a task's cognitive requirements. The framework of Hill, Ball, and Schilling outlines many domains of knowledge in mathematics for instruction. The Stein, Smith, Henningsen, and Silver framework also characterizes the cognitive demands of mathematical tasks in research. Findings show that when student teachers lack the expertise in other areas, particularly subject matter ex

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43

Hua, Er Tian, Da Qiang Chen, Xiao Juan Gong, Lei Hu, Yan Zhen He, and Dan Zhi Sun. "Personalized Product Design Knowledge Acquisition Based on Knowledge Reduction and Knowledge Mining." Applied Mechanics and Materials 738-739 (March 2015): 275–80. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.275.

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This paper makes the historical data which customers bought the products as the foundation, and suggests a method of personalized product design knowledge acquisition based on knowledge reduction and knowledge mining. Firstly, the core matrices of each specific customer group were taken as the decision variables of the decision table based on the key customer segmentation. Secondly, the knowledge reduction algorithm of Skowron discernibility matrix was use to acquire the product design information by reducing the decision table, and deleting the redundant and even product matrices that are not

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44

Jerrard, Bob. "Design-Based Knowledge Transfer Partnerships." Design Journal 9, no. 3 (2006): 1–2. http://dx.doi.org/10.2752/146069206789331410.

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45

Bazylev, V. N., I. A. Kuperman, E. V. Chmykhova, and M. L. Aranovich. "Consolidated Knowledge Corpus: Design Technique." Alma mater. Vestnik Vysshey Shkoly, no. 12 (December 2021): 69–76. http://dx.doi.org/10.20339/am.12-21.069.

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The article presents the results of a pilot study for the structural transformation of 18 Bachelor’s Degree Programs for e-learning using Consolidated Knowledge Corpus. Consolidated Knowledge Corpus is a multidimensional object-oriented structure of educational content objects and their connections. All academic topics from 224 disciplines were combined into a Consolidated Knowledge Corpus to unify similarities and eliminate duplication. A unified matrix of educational content for the first year of study for 18 bachelor’s programs was compiled and an optimized modular structure of the curricul

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46

Gillam, April. "Vehicles knowledge-based design environment." Journal of Spacecraft and Rockets 30, no. 3 (1993): 342–47. http://dx.doi.org/10.2514/3.25521.

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47

Wood, Richard M., and Steven X. S. Bauer. "Discussion of Knowledge-Based Design." Journal of Aircraft 39, no. 6 (2002): 1053–60. http://dx.doi.org/10.2514/2.3034.

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48

Houe, Raymond, and Bernard Grabot. "Knowledge Modeling for Eco-design." Concurrent Engineering 15, no. 1 (2007): 7–20. http://dx.doi.org/10.1177/1063293x07076272.

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49

Mark, William. "Knowledge-Based User Interface Design." Human–Computer Interaction 1, no. 4 (1985): 339–57. http://dx.doi.org/10.1207/s15327051hci0104_3.

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50

Li, Q., and W. J. Zhang. "Computer comparison of design knowledge." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 212, no. 8 (1998): 635–45. http://dx.doi.org/10.1243/0954405981515905.

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Automatic comparison of design knowledge generated and consumed during a design process is very useful. Basically, design knowledge can be classified into four categories: (a) artefact (product) structures, (b) artefact behaviours, (c) artefact functions and (d) causalities among structures, behaviours and functions. This paper proposes an intelligent hybrid graph approach to represent design knowledge associated with these categories. Comparison of design knowledge thus turns out to be the comparison of hybrid graphs. A general algorithm is developed for the graph comparison purpose. In this

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