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Cloud-enabled prognosis for manufacturing
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-8679-8049
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2015 (English)In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 64, no 2, 749-772 p.Article in journal (Refereed) Published
Abstract [en]

Advanced manufacturing depends on the timely acquisition, distribution, and utilization of information from machines and processes across spatial boundaries. These activities can improve accuracy and reliability in predicting resource needs and allocation, maintenance scheduling, and remaining service life of equipment. As an emerging infrastructure, cloud computing provides new opportunities to achieve the goals of advanced manufacturing. This paper reviews the historical development of prognosis theories and techniques and projects their future growth enabled by the emerging cloud infrastructure. Techniques for cloud computing are highlighted, as well as the influence of these techniques on the paradigm of cloud-enabled prognosis for manufacturing. Finally, this paper discusses the envisioned architecture and associated challenges of cloud-enabled prognosis for manufacturing.

Place, publisher, year, edition, pages
2015. Vol. 64, no 2, 749-772 p.
Keyword [en]
Predictive model, Condition monitoring, Cloud manufacturing
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-175948DOI: 10.1016/j.cirp.2015.05.011ISI: 000362051000009Scopus ID: 2-s2.0-84940450168OAI: oai:DiVA.org:kth-175948DiVA: diva2:866217
Note

QC 20151102

Available from: 2015-11-02 Created: 2015-10-26 Last updated: 2017-12-01Bibliographically approved

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Wang, Lihui

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