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Journal ArticleDOI

A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing

TLDR
A new computational framework that enables remote real-time sensing, monitoring, and scalable high performance computing for diagnosis and prognosis is introduced and a proof-of-concept prototype is developed to demonstrate how the framework can enable manufacturers to monitor machine health conditions and generate predictive analytics.
About
This article is published in Journal of Manufacturing Systems.The article was published on 2017-04-01. It has received 223 citations till now. The article focuses on the topics: Prognostics & Wireless sensor network.

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Citations
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Journal ArticleDOI

A flexible data schema and system architecture for the virtualization of manufacturing machines (VMM)

TL;DR: This paper describes how streaming data can be stored in a scalable and flexible document schema based database such as MongoDB, a data store that makes up the virtual twin system that results in the virtualization of a machine resource to external factory manufacturing systems.
Journal ArticleDOI

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

TL;DR: The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.
Journal ArticleDOI

Framework of an IoT-based Industrial Data Management for Smart Manufacturing

TL;DR: This paper presents a framework of an IoT-based Industrial Data Management System (IDMS) which can manage the huge industrial data, support online monitoring, and control smart manufacturing, and contains five basic layers to provide a service-oriented architecture for the end users.
Book ChapterDOI

Industrial Internet of Things (IIoT) Applications of Edge and Fog Computing: A Review and Future Directions

TL;DR: The how edge and fog computing are poised to bring about a turnaround in several industrial applications through a use-case approach is highlighted and some research directions that should be followed are suggested to solve the current issues and challenges faced by these paradigms in IIoT.
Journal ArticleDOI

Fog Computing and Convolutional Neural Network Enabled Prognosis for Machining Process Optimization

TL;DR: An innovative fog enabled prognosis system for machining process optimization that consists of a terminal layer, a fog layer and a cloud layer to minimize data traffic and improve system efficiency is presented.
References
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Journal ArticleDOI

Random Forests

TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
ReportDOI

The NIST Definition of Cloud Computing

Peter Mell, +1 more
TL;DR: This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.
Journal ArticleDOI

A view of cloud computing

TL;DR: The clouds are clearing the clouds away from the true potential and obstacles posed by this computing capability.
Book

The Grid 2: Blueprint for a New Computing Infrastructure

TL;DR: The Globus Toolkit as discussed by the authors is a toolkit for high-throughput resource management for distributed supercomputing applications, focusing on real-time wide-distributed instrumentation systems.
Proceedings ArticleDOI

Fog computing and its role in the internet of things

TL;DR: This paper argues that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
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