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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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Industrial Control via Application Containers:Maintaining determinism in IAAS

TL;DR: The challenges and opportunities of shifting industrial control software from dedicated hardware to bare‐metal servers or (edge) cloud computing platforms using off‐the‐shelf technology, that is, technologies commercially available are explored.
Book ChapterDOI

Cyber-Physical Resource Scheduling in the Context of Industrial Internet of Things Operations

TL;DR: A first cut, proof-of-concept, simulation was built to evaluate the capability of the system to offer effective decentralized scheduling and reconfigure the order sequences in the case of unexpected circumstances, such as cyber-physical resource processing delays, network cybersecurity attacks, or external order changes.
Book ChapterDOI

Fog Computing Architectures and Frameworks for Healthcare 4.0

TL;DR: Researchers have shown that the main factor in healthcare application is reduced latency which should be achieved by means of fog computing, and collection of frameworks developed for healthcare application with respect to fog computing and proposed architectures and implemented systems for the same are divided.
Book ChapterDOI

An Agent-Based Industrial Cyber-Physical System Deployed in an Automobile Multi-stage Production System

TL;DR: This work uses a MAS approach to design cyber-physical agents that can embed different data analysis capabilities, supporting the decentralization of intelligence.
Journal ArticleDOI

Geometric-thermal error control system for gear profile grinding machine

TL;DR: In this paper , a geometric-thermal error control system (GTECS) is designed for gear profile grinding machines, where the analytical model of the rolling guide/slider system is proposed to calculate geometric errors of X- and Z- axes, and the thermal boundary conditions are calculated, and thermal error models of the spindle and C-axis are proposed based on transfer learning model (TLM).
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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