Cloud-Based Prognosis: Perspective and Challenge

Author:

Yang Yunjie1,Gao Robert X.1,Fan Zhaoyan1,Wang Jinjiang1,Wang Lihui2

Affiliation:

1. University of Connecticut, Storrs, CT

2. KTH Royal Institute of Technology, Stockholm, Sweden

Abstract

Comprehensive acquisition, distribution, and utilization of information about machine equipment and/or processes across spatial boundaries for improved productivity and decision have increasingly become the hallmark of advanced manufacturing. The emergence of cloud computing has created ample opportunities to achieve this goal. This paper presents a review of the state-of-the-art of prognosis technique for manufacturing and its future development motivated by the cloud infrastructure. Prevailing methods of prognosis are summarized, and their respective performance is comparatively evaluated. Basic principles and recent advances in cloud computing, as well as its application to cloud manufacturing, are introduced. Based on the survey, the concept of cloud-based prognosis is proposed, and its architecture as well as associated challenges are discussed.

Publisher

American Society of Mechanical Engineers

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1. Condition Monitoring for Predictive Maintenance;Cloud-Based Cyber-Physical Systems in Manufacturing;2017-11-17

2. Challenges in Cybersecurity;Cloud-Based Cyber-Physical Systems in Manufacturing;2017-11-17

3. Cloud Manufacturing: Current Trends and Future Implementations;Journal of Manufacturing Science and Engineering;2015-08-01

4. Cloud Computing for Cloud Manufacturing: Benefits and Limitations;Journal of Manufacturing Science and Engineering;2015-08-01

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