arrow
返回

Collaborative service-component integration in cloud manufacturing

delete2017-09-13
delete65
PRE
AI
M
Mohsen Moghaddam *
S
Shimon Y. Nof
DOI:10.1080/00207543.2017.1374574delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
The Industrial Internet technologies are anticipated to enable agile manufacturing processes in response to the growing demand for personalised products/services with shorter lifecycles. This trend has resulted in a gradual transformation of traditional tree-like' and monolithic systems into complex networks of self-contained and autonomous components' (a.k.a., Internet of things) and services' (a.k.a., Internet of services). Cloud Manufacturing is an emerging concept that enables modularisation and service-orientation in the context of manufacturing, in which systematic orchestration, matching, and sharing of services and components are the key. This work develops a framework for dynamic integration of manufacturing services and components in a collaborative network of organisations. The framework dynamically recommends the best matching of services, components and organisations, as well as the best collaboration decisions in terms of sharing (shareable) services and/or components between organisations. The problem is formulated as a bi-objective mixed-integer program, and solved via an efficient socio-inspired tabu search. The objectives of the model are to increase service level and enhance collaboration through maximising service fulfilment and minimising unnecessary sharing of services/components, respectively. Numerical experiments are conducted to demonstrate the benefits of the developed framework for efficient and optimal (re)configuration of collaborative networked organisations, addressing the Industry 4.0 demand for agility through modularisation and service-orientation.
Keyword:
cyber-physical systems
best matching
collaboration
collaborative control theory
Internet of things
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

International Journal of Production Research 封面图
International Journal of Production Research
IF:
7.3
论文数:
1.1W
被引数:
3.7W

机构

Purdue University System 封面图
Purdue University System
学者数:
4.0W
论文数: 3.6W
被引数: 66
引用论文

引用论文

Heterogeneous teams of modular robots for mapping and exploration
err2000-01-01
err135
PREAI
errGrabowski, R; Navarro-Serment, LE; Paredis, CJJ; Khosla, PK
err分享
err收藏
Taxonomy and Pathology of Togninia (Diaporthales) and its Phaeoacremonium Anamorphs
err2006-01-01
err0
errOAAI
errLizel Mostert; Johannes Z. Groenewald; Richard C. Summerbell; Walter Gams; Pedro W. Crous
err分享
err收藏
学者 查看更多内容