Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-23T19:12:23.872Z Has data issue: false hasContentIssue false
  • English
  • Français

CoStorm: a term map system to aid in a collaborative ideation process

Published online by Cambridge University Press:  15 October 2018

Chengwei Zhang ,
Marcelo López-Parra ,
Junyu Chen  and
Ling Tian
Chengwei Zhang
Affiliation:
Beijing Key Laboratory of Precision/Ultra-precision Manufacturing Equipments and Control, Department of Mechanical Engineering, Tsinghua University, Beijing, China
Marcelo López-Parra
Affiliation:
Unidad de Alta Tecnología, Facultad Ingeniería, UNAM, Queretaro, Mexico
Junyu Chen
Affiliation:
Beijing Key Laboratory of Precision/Ultra-precision Manufacturing Equipments and Control, Department of Mechanical Engineering, Tsinghua University, Beijing, China
Ling Tian*
Affiliation:
Beijing Key Laboratory of Precision/Ultra-precision Manufacturing Equipments and Control, Department of Mechanical Engineering, Tsinghua University, Beijing, China
*
Author for correspondence: Ling Tian, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The decisions made during the early stages of a design process have a huge impact on a product. Owing to the explosion of preliminary ideas, however, designers easily lose track of important ideas and significant information and end up being buried in a pile of plain words. Failing to locate an idea in the context of idea generation makes it difficult to generate new ideas or take optimized decisions. In this study, the authors propose the term map approach to provide a complete bird's eye view of all ideas, which is a higher-dimension graphical representation that helps in inspiring ideas and making decisions among design team members. A software application named CoStorm is developed. Through the case study of the cash-flattener module, which is a crucial component of an automated teller machine, this method is found to contribute in facilitating the ideation and decision-making progress.

Keywords

Computer-aided conceptual designdecision-makingelectronic brainstormingideation
Type
Research Article
Information
AI EDAM , Volume 33 , Issue 3 , August 2019 , pp. 247 - 258
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aurisicchio, M, Bracewell, R and Armstrong, G (2013) The function analysis diagram: intended benefits and coexistence with other functional models. AI EDAM 27, 249–257.Google Scholar
Bracewell, R, Wallace, K, Moss, M and Knott, D (2009) Capturing design rationale. Computer-Aided Design, Computer Support for Conceptual Design 41, 173–186.Google Scholar
Cardoso, C and Badke-Schaub, P (2011) Fixation or inspiration: creative problem solving in design. The Journal of Creative Behavior 45, 77–82.Google Scholar
Chakrabarti, A, Sarkar, P, Leelavathamma, B and Nataraju, BS (2005) A functional representation for aiding biomimetic and artificial inspiration of new ideas. AI EDAM 19, 113–132.Google Scholar
Chandrasegaran, SK, Ramani, K, Sriram, RD, Horváth, I, Bernard, A, Harik, RF and Gao, W (2013) The evolution, challenges, and future of knowledge representation in product design systems. Computer-Aided Design, Solid and Physical Modeling 2012 45, 204–228.Google Scholar
Chiu, S-C and Tomimatsu, K (2013) User Involvement in Idea Brainstorming of Design Process: Finding the Effective Strategy in Social Network Service. In Design, User Experience, and Usability. Design Philosophy, Methods, and Tools Berlin/Heidelberg, Germany: Springer, pp. 593–598. https://doi.org/10.1007/978-3-642-39229-0_63.Google Scholar
Dennis, AR, Minas, RK and Bhagwatwar, AP (2013) Sparking creativity: improving electronic brainstorming with individual cognitive priming. Journal of Management Information Systems 29, 195–216.Google Scholar
Diehl, M and Stroebe, W (1987) Productivity loss in brainstorming groups: toward the solution of a riddle. Journal of Personality and Social Psychology 53, 497–509.Google Scholar
Elias, EW, Chamakiotis, P, Howard, TJ, Dekoninck, EA and Culley, SJ (2011) Can a Virtual Design Environment Enhance Group Creativity and the Use of Stimuli? ICORD 11: Proceedings of the 3rd International Conference on Research into Design Engineering, Bangalore, India, 10.-12.01.2011.Google Scholar
Furnham, A (2000) The brainstorming myth. Business Strategy Review 11, 21–28.Google Scholar
Gallupe, RB and Cooper, WH (1993) Brainstorming electronically. Sloan Management Review 35, 27–36.Google Scholar
Gruber, TR (1993) A translation approach to portable ontology specifications. Knowledge Acquisition 5, 199–220.Google Scholar
Hoover, CW and Jones, JB (1991) Improving Engineering Design: Designing for Competitive Advantage. Washington, DC: National Research Council.Google Scholar
Howard, TJ, Culley, S and Dekoninck, EA (2011) Reuse of ideas and concepts for creative stimuli in engineering design. Journal of Engineering Design 22, 565–581.Google Scholar
Hsu, W and Woon, IMY (1998) Current research in the conceptual design of mechanical products. Computer-Aided Design 30, 377–389.Google Scholar
Jiang, JJ and Conrath, DW (1997) Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy. ArXiv Preprint Cmp-Lg/9709008. http://arxiv.org/abs/cmp-lg/9709008.Google Scholar
Jin, Y and Benami, O (2010) Creative patterns and stimulation in conceptual design. AI EDAM 24, 191–209.Google Scholar
Kletke, MG, Mackay, JM, Barr, SH and Jones, B (2001) Creativity in the organization: the role of individual creative problem solving and computer support. International Journal of Human-Computer Studies 55, 217–237.Google Scholar
Linsey, JS, Wood, KL and Markman, AB (2008) Increasing Innovation: Presentation and Evaluation of the Wordtree Design-by-Analogy Method, January, 21–32. https://doi.org/10.1115/DETC2008-49317.Google Scholar
MacCrimmon, KR and Wagner, C (1994) Stimulating ideas through creative software. Management Science 40, 1514–1532.Google Scholar
Moulin, C, Kaeri, Y, Sugawara, K and Abel, M-H (2016) Capitalization of remote collaborative brainstorming activities. Computer Standards & Interfaces, Special Issue on Information System in Distributed Environment 48, 217–224.Google Scholar
Murphy, J, Fu, K, Otto, K, Yang, M, Jensen, D and Wood, K (2014) Function based design-by-analogy: a functional vector approach to analogical search. Journal of Mechanical Design 136, 101102.Google Scholar
Nagel, JKS, Nagel, RL, Stone, RB and McAdams, DA (2010) Function-based, biologically inspired concept generation. AI EDAM 24, 521–535.Google Scholar
Osborn, AF (1953) Applied Imagination. http://psycnet.apa.org/psycinfo/1954-05646-000.Google Scholar
Pahl, G, Beitz, W, Feldhusen, J and Grote, K-H (2007) Engineering Design: A Systematic Approach. Berlin, Germany: Springer Science & Business Media.Google Scholar
Pal, U, Liu, Y-C and Chakrabarti, A (2014) Evaluating FuncSION: a software for automated synthesis of design solutions for stimulating ideation during mechanical conceptual design. AI EDAM 28, 209–226.Google Scholar
Srinivasan, V, Chakrabarti, A and Lindemann, U (2015) An empirical understanding of Use of internal analogies in conceptual design. AI EDAM 29, 147–160.Google Scholar
Sutton, RI and Hargadon, A (1996) Brainstorming groups in context: effectiveness in a product design firm. Administrative Science Quarterly 41, 685–718.Google Scholar
Vallecillos, J, Criado, J, Iribarne, L and Padilla, N (2014) Dynamic Mashup Interfaces for Information Systems Using Widgets-as-a-Service. In On the Move to Meaningful Internet Systems: OTM 2014 Workshops, 438–47. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-45550-0_44.Google Scholar
Weas, A and Campbell, M (2004) Rediscovering the analysis of interconnected decision areas. AI EDAM 18, 227–243.Google Scholar
West, DB (2001) Introduction to Graph Theory, vol. 2. Prentice hall Upper Saddle River. http://math.illinois.edu/~dwest/igt/igtpref.ps.Google Scholar
Youmans, RJ (2011) Design fixation in the wild: design environments and their influence on fixation. The Journal of Creative Behavior 45, 101–107.Google Scholar
Youmans, RJ and Arciszewski, T (2014) Design fixation: classifications and modern methods of prevention. AI EDAM 28, 129–137.Google Scholar
Yuizono, T, Xing, Q and Furukawa, H (2014) Effects of Gamification on Electronic Brainstorming Systems. In Collaboration Technologies and Social Computing, 54–61. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-44651-5_5.Google Scholar
Zhang, C, Tian, L and Wu, Y (2015) Ontology-Based Adaptive Object Model for Simulation Physical Parameter Management. In ASME 2015 International Mechanical Engineering Congress and Exposition, V011T14A001–V011T14A001. American Society of Mechanical Engineers. http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=2501296.Google Scholar