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
不配.应助淡淡鱼采纳,获得50
2秒前
kiki发布了新的文献求助10
2秒前
2秒前
2秒前
nan完成签到,获得积分10
4秒前
都是废寝食忘啊完成签到,获得积分10
8秒前
易大人发布了新的文献求助10
9秒前
9秒前
无花果应助paofu泡芙采纳,获得10
9秒前
自信白梦完成签到,获得积分10
10秒前
充电宝应助宋灵竹采纳,获得10
11秒前
12秒前
SciGPT应助十六采纳,获得10
13秒前
单薄的大白菜真实的钥匙完成签到,获得积分20
14秒前
阿腾发布了新的文献求助10
14秒前
InfoNinja应助yy_ren采纳,获得30
14秒前
14秒前
慈祥的乐菱完成签到,获得积分10
15秒前
深情安青应助加百莉采纳,获得10
15秒前
kkdkg发布了新的文献求助10
15秒前
16秒前
18秒前
Huajing_Yang发布了新的文献求助10
19秒前
曾经忘幽发布了新的文献求助10
23秒前
dong发布了新的文献求助10
24秒前
28秒前
CipherSage应助科研通管家采纳,获得10
30秒前
大模型应助科研通管家采纳,获得10
30秒前
不配.应助科研通管家采纳,获得30
30秒前
CodeCraft应助科研通管家采纳,获得10
30秒前
30秒前
30秒前
CipherSage应助科研通管家采纳,获得10
30秒前
健壮不斜完成签到 ,获得积分10
30秒前
英姑应助zzz采纳,获得10
32秒前
晓书斋完成签到,获得积分10
32秒前
共享精神应助哈哈哈哈采纳,获得10
34秒前
ChenyuTian完成签到 ,获得积分10
34秒前
LIU完成签到 ,获得积分10
35秒前
一五完成签到,获得积分10
35秒前
高分求助中
Spray / Wall-interaction Modelling by Dimensionless Data Analysis 2000
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
Mathematics and Finite Element Discretizations of Incompressible Navier—Stokes Flows 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 3184481
求助须知:如何正确求助?哪些是违规求助? 2834823
关于积分的说明 8001452
捐赠科研通 2497193
什么是DOI,文献DOI怎么找? 1332689
科研通“疑难数据库(出版商)”最低求助积分说明 636663
邀请新用户注册赠送积分活动 603998