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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

Thermal error prediction for heavy-duty CNC machines enabled by long short-term memory networks and fog-cloud architecture

TL;DR: In this paper , a new system for thermal error prediction on heavy-duty CNC machines enabled by a Long Short-Term Memory (LSTM) networks and a fog-cloud architecture is presented.
Journal ArticleDOI

A cyber-physical production monitoring service system for energy-aware collaborative production monitoring in a smart shop floor

TL;DR: This work proposes a Cyber-Physical Production Monitoring Service System (CPPMSS) for the collaborative production monitoring of individualized product orders and shows that it can satisfy the collaborative manufacturing operations among different stakeholders in the mass individualization environment.
Proceedings ArticleDOI

Workers to super workers: A brief discussion on important technologies for industry 5.0 manufacturing systems

TL;DR: In this article, the authors discuss the important technologies for the design of Industry 5.0 manufacturing systems and emphasize on the adaptability of Industry5.0 concepts for the mass customization of products.
Journal ArticleDOI

Analyzing interrelated enablers of industry 4.0 for implementation in present industrial scenario

TL;DR: This is the first-ever attempt to conduct a structured literature review combined with text analysis and linguistic assessment to identify the enablers of Industry 4.0 for implementation.
Book ChapterDOI

Data Scheduling and Resource Optimization for Fog Computing Architecture in Industrial IoT

TL;DR: This work integrates the decentralized resources of fog nodes to form a cluster which can deliver sufficient processing power to deal with a complicated computational task and proposes an optimal data scheduling policy with multiple communication channels to minimize real-time processing delay and increase stability of the system.
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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