A Bayesian network model for supporting the formation of PSS design knowledge
A Bayesian network model for supporting the formation of PSS design knowledge
复制标题
支持PSS设计知识形成的贝叶斯网络模型
DOI：
10.1016/j.procir.2018.04.002
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Shimomura Yoshiki
中科院分区：
文献类型：
--
作者：
Tsutsui Yusuke;Kubota Yosuke;Shimomura Yoshiki
最近，产品服务系统（PSS）引起了制造业的兴趣。设计PSS以提升其核心产品的价值时，制造商应假设其产品是其优势或约束，并逻辑地推导出服务解决方案。然而，用于确定适合制造商核心产品的服务的 PSS 设计知识尚不清楚。因此，确定与其核心产品兼容的服务解决方案非常困难。因此，这一困难阻碍了制造业实现高质量的 PSS。为了有效地形成PSS设计知识，本研究旨在支持分析产品特性与服务内容之间复杂多样的关系。具体而言，通过基于PSS案例的统计数据的计算学习，构建表示现有PSS案例中常见的产品特征和服务内容之间的逻辑结构的贝叶斯网络模型。
Recently, product-service systems (PSS) have drawn the interest of the manufacturing industry. Designing PSS to enhance the value of their core products, manufacturers should assume that their products are their strength or constraint and also derive the service solution logically. However, PSS design knowledge to determine the services suitable for manufacturers’ core products is unclear. As a result, determining a service solution that is compatible with their core products is difficult. This difficulty consequently prevents the manufacturing industry from realising high-quality PSS. To form PSS design knowledge efficiently, this study aims to support the analysis of the complicated and diverse relationships between product characteristics and service contents. Specifically, a Bayesian network model that represents the logical structure between the product characteristics and service contents common among existing PSS cases is constructed through computational learning based on statistical data on PSS cases.
一种基于多领域知识的支持服务设计的方法
影响因子：
3.2
作者：
Kazuhiro Oki;Kentaro Watanabe;R. Chiba;Y. Shimomura
通讯作者：
Y. Shimomura
DOI：
10.1299/kikaic.72.274
发表时间：
2006
期刊：
Transactions of the Japan Society of Mechanical Engineers. C
影响因子：
--
作者：
Y. Shimomura;Masaharu Yoshioka;Hideaki Takeda;T. Tomiyama
通讯作者：
T. Tomiyama