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浙江大学学报(工学版)  2024, Vol. 58 Issue (10): 2084-2095    DOI: 10.3785/j.issn.1008-973X.2024.10.012
机械工程、能源工程     
多源数据驱动的主控式创新框架
石庆林1,2(),张凯瑞1,2,侯亮1,3,郭小暄1,2,张文博1,3,连晓振1,3,陈永超4,穆瑞1,2,*()
1. 厦门大学 机电工程系,福建 厦门 361102
2. 厦门大学 航空航天学院,福建 厦门 361102
3. 厦门大学 萨本栋微米纳米科学技术研究院,福建 厦门 361005
4. 厦门盈趣科技股份有限公司,福建 厦门 361027
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
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摘要:

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    
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
收稿日期: 2023-08-23 出版日期: 2024-09-27
CLC:  TH 122  
基金资助: 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).
通讯作者: 穆瑞     E-mail: 1927607116@qq.com;murui@xmu.edu.cn
作者简介: 石庆林(1998—),男,硕士生,从事产品创新设计、自然语言处理、数据挖掘研究. orcid.org/0009-0001-2574-7317. E-mail:1927607116@qq.com
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引用本文:

石庆林,张凯瑞,侯亮,郭小暄,张文博,连晓振,陈永超,穆瑞. 多源数据驱动的主控式创新框架[J]. 浙江大学学报(工学版), 2024, 58(10): 2084-2095.

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.

链接本文:

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

图 1  多源数据驱动的主控式创新框架
图 2  基于词典的情感分析方法
图 3  运行性能分布及性能需求区间
图 4  基于运行数据的性能满意度分析流程
图 5  基于评论数据的过渡矩阵生成流程
图 6  基于运行数据的过渡矩阵生成流程
图 7  技术成熟度预测模式
图 8  隐性需求预测方法
特征集群Sfc特征集群Sfc特征集群Sfc
体积大小1. 125产品品牌0. 900产品重量0. 750
型号款式1. 000用户操作0. 859运行声音0. 750
产品价格0. 938配套软件0. 857开关按键0. 750
产品运行0. 929产品形状0. 815打印效果0. 602
产品颜色0. 927产品用途0. 771打 印 纸0. 583
表 1  GO的特征集群满意度
图 9  运行数据分布情况
性能指标$p_i$$S(p_i)$${\mathrm{Pv}}_r$
清 晰 度437.840.44481.00
打印速度6.89650.97170.00
马达温度41.30.82830.15
噪 声68.00.65660.41
表 2  GO的性能满意度
图 10  2022年迷你打印机市场调研结果
特征集群CrvrMvr特征集群CrvrMvr
体积大小0.0000.083产品形状0.4110.032
型号款式0.1130.187产品用途0.4950.075
产品价格0.2150.055产品重量0.5390.083
产品运行0.2280.450运行声音0.5390.439
产品颜色0.2300.032开关按键0.5390.000
产品品牌0.2690.000打印效果0.9351. 000
用户操作0.3340.407打 印 纸1. 0000.859
配套软件0.3370.296
表 3  特征集群的需求价值和市场价值
图 11  基于评论数据生成的过渡矩阵
模块impj${\widetilde {\mathrm{imp}}}_j $
充电管理模块0.0150.039
主控芯片0.2620.703
蓄电池0.0370.099
通信模块0.0240.063
马达驱动模块0.1580.425
按键按钮0.0000.000
热敏机芯0.3731.000
表 4  GO不同模块的重要度
图 12  基于运行数据生成的过渡矩阵
图 13  热敏打印机专利公开数量变化趋势
技术进化定律隐性需求预测
提高理想化水平自动裁剪,自动装订,无损害打印头,声音提示
动态化增长学习分析系统,可选装模块实现定制化
缩短能量流路径长度太阳能充电
增加可控性实时动态监测,防水抗摔,恒温打印头,语音指令识别
增加和谐性便携3D打印机,无声打印机
表 5  产品成长期的隐性需求预测结果
图 14  GO系列的主控式创新矩阵
用户群体使用场景描述需 求
学生群体学生群体使用迷你打印机进行学习和错题打印自动裁剪、自动装订、无损打印头、学习分析系统、恒温打印头、无声打印机,低噪声、高质量打印纸、优质打印效果,小体积、款式新颖、高速打印······
居家老人老人使用智能产品不便,子女通过打印机远程提醒老人到点吃药和交流无损打印头、声音提示、恒温打印头、语音指令识别,优质打印效果,APP顺畅、操作简单、运行流畅······
情侣/户外摄影情侣需要远程打印传递消息以及户外拍照打印,户外摄影爱好者可以随时打印照片自动裁剪、太阳能充电、防水抗摔、语音指令识别,优质打印效果,小体积、小重量、款式新颖、连续打印······
特定人群有户外3D打印需求的群体或其他功能需求的群体可选装模块实现定制化、便携3D打印
表 6  迷你打印机的需求市场细分
产品说明产品型号体积/mm3款式数量Lp/dBvp/(cm2·s?1)打印纸DPI连接方式评论数量
目标产品GO80×79×334686.8965不干胶203无线513
同期竞品QL-800125×213×1421717.3043不干胶300有线219
下一代产品G486×79×394626.3809不干胶
单色/粘贴式
300无线1654
下一代竞品QL-820NWB125×213×1422707.4085不干胶300有线/无线123
表 7  不同产品性能对比
图 15  不同数据驱动的需求挖掘结果
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