Complexity Measurement Model and Methods of Crowd Intelligence Collaborative Innovation for Design Activities

被引：0
|
作者：
Zheng Q. [1 ]
Ding G. [1 ]
机构：
[1] School of Mechanical Engineering, Southwest Jiaotong University, Chengdu
来源：
Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2021年 / 56卷 / 05期
关键词：
Complexity; Crowd intelligence; Design activity; Information entropy; Product innovation;
D O I：
10.3969/j.issn.0258-2724.20200238
中图分类号：
学科分类号：
摘要：
Crowd intelligence (CI) innovation has become an important product innovation tool in the environment of Internet as it can amass huge design resources outside the enterprises through online community. It is an important way for enterprises to expand design capabilities, solve design problems, and realize transformation and upgrading. The design activity complexity of crowd intelligence collaborative innovation is difficult to quantitatively describe. As a result, it leads to the absence of a quantitative basis for the release, push, and dynamic adjustment of design activities in the Internet innovation community. To solve these problems, a design activity complexity measurement method based on information entropy theory is put forward. First, the characteristics of the collaborative design process in Internet innovation community, as well as user types and capacity characteristics are analyzed. Second, three dimension including process complexity, problem complexity, and solvability complexity, are proposed to valuate design activities. Then, the quantitative methods are proposed on the basis of information entropy theory. Finally, the suspension design of project LM SF-01 in the Local Motors community is used as an example to calculate its complexity. The complexity in the three dimensions are respectively 318.15, 477.66 bit, and 134.46 bit. According to the characteristics of user participation, the weighted complexity of the design activity is 331.76 bit, which validates the effectiveness and feasibility of the complexity measurement model. © 2021, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.
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页码：989 / 994and1010
相关论文
共 18 条
  • [1] MICHELUCCI P, DICKINSON J L., The power of crowds, Science, 351, 6268, pp. 32-33, (2016)
  • [2] AMERI F, SUMMERS J D, MOCKO G M, Et al., Engineering design complexity:an investigation of methods and measures, Research in Engineering Design, 19, 2, pp. 161-179, (2008)
  • [3] SUMMERS J D, SHAH J J., Mechanical engineering design complexity metrics:size,coupling,and solvability, Journal of Mechanical Design, 132, (2010)
  • [4] ZHANG Peng, YANG Bojun, ZHANG Huangao, Et al., Conflict determination oriented to CAI based on design-centric complexity, Computer Integrated Manu- facturing Systems, 19, 2, pp. 330-337, (2013)
  • [5] XU Jiang, WANG Xiuyue, WANG Yi, Et al., Complexity computation approach of design cognition using deterministic information theory, China Mechanical Engineering, 28, 5, pp. 596-602, (2017)
  • [6] ZHANG Genbao, ZENG Haifeng, WANG Guoqiang, Et al., Effectiveness evaluation of manufacturing process quality by measurement of extended information entropy, China Mechanical Engineering, 21, 20, pp. 2451-2458, (2010)
  • [7] MA Jing, LIU Mingzhou, WANG Qiang, Et al., Complexity metrics for assembly system of mechanical products based on IOT-entropy, Computer Integrated Manufacturing Systems, 22, 1, pp. 248-256, (2016)
  • [8] WANG H, ZHU X W, WANG H, Et al., Multi-objective optimization of product variety and manufacturing complexity in mixed-model assembly systems, Journal of Manufacturing Systems, 30, 1, pp. 16-27, (2011)
  • [9] ANTORINI Y M, MUNIZ A M., Invited article:the benefits and challenges of collaborating with user communities, Research-Technology Management, 56, 3, pp. 21-28, (2013)
  • [10] LI W, WU W J, WANG H M, Et al., Crowd intelligence in AI 2.0 era, Frontiers of Information Technology & Electronic Engineering, 18, 1, pp. 15-43, (2017)
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