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
Cited by
5 articles.
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