A Framework for the Capture and Analysis of Product Usage Data for Continuous Product Improvement

计算机科学 背景(考古学) 产品生命周期 产品设计说明书 产品(数学) 新产品开发 产品设计 产品工程 系统工程 工程类 几何学 数学 生物 业务 古生物学 营销
作者
Henning Voet,Max Altenhof,Max Ellerich,Robert Schmitt,Barbara Linke
出处
期刊:Journal of Manufacturing Science and Engineering-transactions of The Asme [ASME International]
卷期号:141 (2) 被引量:24
标识
DOI:10.1115/1.4041948
摘要

Product improvement, usually through changes in design and functionality, is relying more and more on the continuous analysis of large amounts of data. Product data can come from many sources with varying effort in obtaining the data, e.g., condition monitoring and maintenance data. Intelligent products, also known as “product embedded information devices” (PEID), are already equipped with sensors and onboard computing capabilities and therefore able to generate valuable data such as the number of user interactions during the use phase. The internet of things (IoT) makes data transfer possible at any time to close the loop for the product lifecycle data and methods like machine learning promote new uses of those data. This paper proposes a methodology to capture the most relevant data on product use and human–product interaction automatically and utilize it as part of data-driven product improvement. Product engineers and designers will gain insights into the use phase and can derive design changes and quality improvements. The methodology guides the user through research on product use dimensions based on the principles of user-centered design (UCD). The findings are applied to define what usage elements, such as specific actions and context, need to be available from the use phase. During systems development, machine learning is suggested to fuse sensor data to efficiently capture the usage elements. After product deployment, use data are retrieved and analyzed to identify the improvement potential. This research is a first step on the long way to self-optimizing products.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
桐桐应助wsl采纳,获得10
刚刚
mqthhh完成签到,获得积分10
1秒前
SciGPT应助moralz采纳,获得10
2秒前
xx应助瞿访云采纳,获得10
2秒前
科研通AI2S应助赫绮琴采纳,获得10
2秒前
zm完成签到,获得积分10
2秒前
G.Yee完成签到,获得积分10
3秒前
3秒前
3秒前
也是难得取个名完成签到 ,获得积分10
3秒前
酸奶七发布了新的文献求助10
4秒前
鱼女士完成签到,获得积分10
4秒前
乐乐应助亦亦采纳,获得10
4秒前
wanci应助奋斗采纳,获得10
5秒前
小明的食堂完成签到,获得积分10
6秒前
瓜瓜发布了新的文献求助10
6秒前
zyc完成签到,获得积分20
6秒前
四观人完成签到,获得积分10
7秒前
赚钱的君完成签到,获得积分10
8秒前
烟花应助明帅采纳,获得10
8秒前
CipherSage应助梅一一采纳,获得10
9秒前
9秒前
科研通AI2S应助淡定吃吃采纳,获得10
9秒前
10秒前
玮哥不是伟哥完成签到,获得积分10
11秒前
zyzy完成签到,获得积分10
12秒前
Akim应助科研通管家采纳,获得10
12秒前
12秒前
华仔应助科研通管家采纳,获得10
12秒前
思源应助科研通管家采纳,获得30
13秒前
彭于晏应助科研通管家采纳,获得10
13秒前
英俊的铭应助科研通管家采纳,获得10
13秒前
fedehe完成签到 ,获得积分10
13秒前
科研通AI2S应助科研通管家采纳,获得10
13秒前
科研通AI2S应助科研通管家采纳,获得10
13秒前
321完成签到 ,获得积分10
13秒前
科研通AI2S应助科研通管家采纳,获得10
13秒前
敬老院N号应助科研通管家采纳,获得20
13秒前
良辰应助科研通管家采纳,获得10
13秒前
高分求助中
Evolution 3rd edition 1500
保险藏宝图 1000
Lire en communiste 1000
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 700
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 700
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
2-Acetyl-1-pyrroline: an important aroma component of cooked rice 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3181206
求助须知:如何正确求助?哪些是违规求助? 2831448
关于积分的说明 7984853
捐赠科研通 2493457
什么是DOI,文献DOI怎么找? 1330153
科研通“疑难数据库(出版商)”最低求助积分说明 635934
版权声明 602955