Dominant innovation framework driven by multi-source of data

doi:10.3785/j.issn.1008-973X.2024.10.012

Journal of ZheJiang University (Engineering Science)

2024, Vol. 58

Issue (10): 2084-2095 DOI: 10.3785/j.issn.1008-973X.2024.10.012

Dominant innovation framework driven by multi-source of data

Qinglin SHI1,2(

),Kairui ZHANG1,2,Liang HOU1,3,Xiaoxuan GUO1,2,Wenbo ZHANG1,3,Xiaozhen LIAN1,3,Yongchao CHEN4,Rui MU1,2,*(

)

1. Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361102, China
2. School of Aerospace Engineering, Xiamen University, Xiamen 361102, China
3. Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen 361005, China
4. Xiamen Intretech Incorporated, Xiamen 361027, China

Download:

HTML

PDF(1626KB) HTML
Export: BibTeX | EndNote (RIS)

Abstract

A new dominant innovation framework was proposed to address the shortcomings of the design knowledge and single-source data-driven traditional requirement mining methods, such as over-reliance on design experience, incomplete requirement mining, and lack of requirement forecasting. The unstructured text data was used as the object to extract and classify the features of requirement from the users’ perspective. The operational big data of product was used as the object to mine the users’ requirement from the product’s perspective. The requirement prediction theory was applied to predict the implicit requirement of future products and construct a data-driven dominant innovation matrix. Compared with the traditional knowledge-driven market research and the single-source data requirement mining methods, the proposed framework was more objective and comprehensive for explicit requirement mining, while taking into account the future implicit requirement mining. The mini-printer of an intelligent manufacturing enterprise was used as a case to verify the effectiveness of the proposed framework.

Key words： multi-source of data dominant innovation online review operational big data innovation matrix requirement forecasting

Received: 23 August 2023 Published: 27 September 2024

CLC:	TH 122
	TB 472

Fund: 科技部创新方法专项基金资助项目（2020IM010100）；厦门市自然科学基金资助项目（3502Z20227186）；福建省科技计划创新战略研究项目（2022R0006）.

Corresponding Authors: Rui MU E-mail: 1927607116@qq.com;murui@xmu.edu.cn

	Service
	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Qinglin SHI
	Kairui ZHANG
	Liang HOU
	Xiaoxuan GUO
	Wenbo ZHANG
	Xiaozhen LIAN
	Yongchao CHEN
	Rui MU

Cite this article:

Qinglin SHI,Kairui ZHANG,Liang HOU,Xiaoxuan GUO,Wenbo ZHANG,Xiaozhen LIAN,Yongchao CHEN,Rui MU. Dominant innovation framework driven by multi-source of data. Journal of ZheJiang University (Engineering Science), 2024, 58(10): 2084-2095.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2024.10.012 OR https://www.zjujournals.com/eng/Y2024/V58/I10/2084

多源数据驱动的主控式创新框架

为了解决设计知识和单源数据驱动的传统需求挖掘方法过于依赖设计经验、需求挖掘不全面、缺乏需求预测等问题，提出新的主控式创新框架. 以非结构化文本数据为对象，从用户角度对需求进行特征提取及分类；以产品运行大数据为对象，从产品角度挖掘用户需求；运用需求预测理论对未来产品隐性需求进行预测，构建数据驱动的主控式创新矩阵. 相较于知识驱动为主的传统市场调研和单源数据的需求挖掘方法，所提框架显性需求挖掘更为客观全面，兼顾未来隐性需求挖掘. 以某智能制造企业的迷你打印机为案例，验证了所提框架的有效性.

关键词： 多源数据, 主控式创新, 在线评论, 运行大数据, 创新矩阵, 需求预测

Fig.1 Dominant innovation framework driven by multi-source of data

Fig.2 Lexicon-based sentiment analysis method

Fig.3 Operational performance distribution and performance requirement interval

Fig.4 Process of performance satisfaction analysis based on operational data

Fig.5 Process of transition matrix generation based on review data

Fig.6 Process of transition matrix generation based on operational data

Fig.7 Technology maturity prediction model

Fig.8 Methods of implicit requirement forecasting

Tab.1 Satisfaction of GO feature cluster

Fig.9 Distribution of operational data

Tab.2 Satisfaction of GO performance

Fig.10 Result of mini printer market research in 2022

Tab.3 Requirement value and market value of feature clusters

Fig.11 Transition matrix based on review data

Tab.4 Importance of different modules of GO

Fig.12 Transition matrix based on operational data

Fig.13 Trend of number of patent disclosures for thermal printers

Tab.5 Results of implicit requirement forecasting

Fig.14 Dominant innovation matrix of GO series

Tab.6 Requirement market segmentation of mini printer

Tab.7 Performance comparison of different products

Fig.15 Results of different data-driven requirement mining


[1]	GUO Q, XUE C, YU M, et al A new user implicit requirements process method oriented to product design[J]. Journal of Computing and Information Science in Engineering, 2019, 19 (1): 011010 doi: 10.1115/1.4041418

[2]	IMBESI S, SCATAGLINI S A user centered methodology for the design of smart apparel for older users[J]. Sensors, 2021, 21 (8): 2804 doi: 10.3390/s21082804

[3]	王超, 谷美利, 龙若佳, 等基于乘客行为分析的列车卧铺布局创新设计研究[J]. 包装工程, 2023, 44 (18): 27- 34 WANG Chao, GU Meili, LONG Ruojia et al. Innovative design of sleeper layout based on passenger behavior analysis[J]. Packaging Engineering, 2023, 44 (18): 27- 34

[4]	YANG X, ZHANG J, WANG Y, et al. Construction of a product design model based on multi-scenario FBS-QFD [C]// International Conference on Mechanical Design and Simulation . [S. l.]: SPIE, 2022.

[5]	耿秀丽, 潘亚虹考虑用户体验的产品服务系统模块重要度判定方法[J]. 计算机集成制系统, 2020, 26 (5): 1295- 1303 GENG Xiuli, PAN Yahong Importance degree determination approach for product service system modules based on user experience[J]. Computer Integrated Manufacturing Systems, 2020, 26 (5): 1295- 1303

[6]	苏珂, 崔元面向相似认知用户集群的TRIZ超系统资源需求获取模型[J]. 计算机集成制造系统, 2021, 27 (7): 2065- 2077 SU Ke, CUI Yuan Demand acquisition model of TRIZ super system resources for similar cognitive user clusters[J]. Computer Integrated Manufacturing Systems, 2021, 27 (7): 2065- 2077

[7]	LEE J, ABUALI M Innovative product advanced service systems (I-PASS): methodology, tools, and applications for dominant service design[J]. The International Journal of Advanced Manufacturing Technology, 2011, 52: 1161- 1173 doi: 10.1007/s00170-010-2763-7

[8]	王新, 乔文文基于云平台的用户隐式需求分析方法研究[J]. 机械设计与研究, 2020, 36 (5): 8- 11 WANG Xin, QIAO Wenwen Research on user implicit demand analysis based on cloud platform[J]. Machine Design and Research, 2020, 36 (5): 8- 11

[9]	LI Y, DONG Y, WANG Y, et al. Product design opportunity identification through mining the critical minority of customer online reviews [J]. Electronic Commerce Research , 2023: 1–29.

[10]	王克勤, 刘朝明基于在线评论的重要度绩效竞争对手分析的产品设计改进方法[J]. 计算机集成制造系统, 2022, 28 (5): 1496- 1506 WANG Keqin, LIU Chaoming Product design improvement based on importance performance competitor analysis of online reviews[J]. Computer Integrated Manufacturing Systems, 2022, 28 (5): 1496- 1506

[11]	侯亮, 林浩菁, 王少杰, 等基于运行数据驱动反向设计的复杂装备个性化定制[J]. 机械工程学报, 2021, 57 (8): 65- 80 HOU Liang, LIN Haojing, WANG Shaojie, et al Mass personalization for complex equipment based on operating data-driven inverse design[J]. Journal of Mechanical Engineering, 2021, 57 (8): 65- 80 doi: 10.3901/JME.2021.08.065

[12]	ZHANG L, CHU X, CHEN H, et al Identification of performance requirements for design of smartphones based on analysis of the collected operating data[J]. Journal of Mechanical Design, 2017, 139 (11): 111418 doi: 10.1115/1.4037475

[13]	叶文涛, 韩宇翃基于Kano模型和TRIZ技术进化法则的老年代步车设计[J]. 包装工程, 2023, 44 (Suppl.1): 312- 319 YE Wentao, HAN Yuhong Elderly mobility scooter design based on Kano model and evolutionary laws of TRIZ technique[J]. Packaging Engineering, 2023, 44 (Suppl.1): 312- 319

[14]	张建辉, 李勇, 张鹏, 等需求进化和技术进化集成的产品用户需求获取研究[J]. 机械设计, 2017, 34 (7): 15- 22 ZHANG Jianhui, LI Yong, ZHANG Peng, et al Customer needs acquisition by integrating needs evolution with technology evolution[J]. Journal of Machine Design, 2017, 34 (7): 15- 22

[15]	王慧. 基于特征提取和情感分析的用户需求挖掘研究[D]. 杭州: 浙江理工大学, 2019: 40–43. WANG Hui. Research on user demand mining based on feature extraction and emotion analysis [D]. Hangzhou: Zhejiang Sci-Tech University, 2019: 40–43.

[16]	ZHANG L, CHU X, CHEN H, et al A data-driven approach for the optimisation of product specifications[J]. International Journal of Production Research, 2019, 57 (3): 703- 721 doi: 10.1080/00207543.2018.1480843

[17]	ZHAO Z, LI Y, CHU X Data-driven approach to identify obsolete functions of products for design improvements[J]. Journal of Intelligent and Fuzzy Systems, 2021, 40 (3): 5369- 5382 doi: 10.3233/JIFS-202144

[18]	YANG Z L, SONG Y W, DUAN Z F, et al New sigmoid-like function better than fisher z transformation[J]. Communications in Statistics-Theory and Methods, 2016, 45 (8): 2332- 2341 doi: 10.1080/03610926.2013.771750

[19]	CHOU Y M, POLANSKY A M, MASON R L Transforming non-normal data to normality in statistical process control[J]. Journal of Quality Technology, 1998, 30 (2): 133- 141 doi: 10.1080/00224065.1998.11979832

[20]	SAKIA R M The Box-Cox transformation technique: a review[J]. Journal of the Royal Statistical Society: Series D (The Statistician), 1992, 41 (2): 169- 178

[21]	邱凯, 苏建宁, 张书涛, 等面向多域协同的复杂产品再设计模块主从识别[J]. 浙江大学学报: 工学版, 2022, 56 (12): 2358- 2366 QIU Kai, SU Jianning, ZHANG Shutao, et al Leader-follower identification of complex product redesign modules for multi-domain collaboration[J]. Journal of Zhejiang University: Engineering Science, 2022, 56 (12): 2358- 2366

[22]	檀润华. TRIZ及应用: 技术创新过程与方法[M]. 北京: 高等教育出版社, 2010: 93.

[23]	张文焘, 张建辉, 张文旭, 等基于多方法融合的需求提取模型研究[J]. 机械设计与研究, 2021, 37 (1): 10- 15 ZHANG Wentao, ZHANG Jianhui, ZHANG Wenxu, et al Research on requirement extraction model based on multi-method fusion[J]. Machine Design and Research, 2021, 37 (1): 10- 15

[24]	孙群. 基于TRIZ的六足仿生机器人创新设计[D]. 天津: 河北工业大学, 2018. SUN Qun. Innovative design of hexapod robot based on TRIZ [D]. Tianjin: Hebei University of Technology, 2018.

No related articles found!

Viewed

Full text

Abstract

Cited

Shared

Discussed