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Manufacturing IT, MES

Courtesy: Litmus
IIoT, Industrie 4.0 May 7, 2020

Data flow is no longer hierarchical

Can industrial edge computing fit into the Purdue model?

By Vatsal Shah
Courtesy: Massachusetts Institute of Technology
AI and Machine Learning April 24, 2020

Reducing AI’s carbon footprint

MIT researchers have developed an automated AI system for training and running certain neural networks that also cuts down the pounds of carbon emissions involved.

By Rob Matheson
This figure shows the model prediction of the infected case count for the United States following its current model with quarantine control and the exponential explosion in the infected case count if the quarantine measures were relaxed. On the other hand, switching to stronger quarantine measures as implemented in Wuhan, Italy, and South Korea might lead to a plateau in the infected case count sooner. Courtesy: Massachusetts Institute of Technology (MIT)
AI and Machine Learning April 17, 2020

Machine learning model quantifies quarantine measures on COVID-19’s spread

A machine learning algorithm developed by MIT researchers combines data from COVID-19’s spread with a neural network to assess the impact of quarantine measures and predict when infections will slow down in each country.

By Mary Beth Gallagher
Remote Monitoring April 14, 2020

Remote monitoring and data visualization

Remote monitoring and data visualization are key to improving overall manufacturing efficiency.

By Jack Smith
Courtesy: MartinCSI
virtualization, Cloud, Analytics, Edge Computing April 2, 2020

Edge computing terms and skills

Six edge computing questions to ask about data collection, networking and control systems.

By Nate Kay, P.E.
Courtesy: CFE Media and Technology
Discrete Manufacturing March 17, 2020

Coronavirus reveals weaknesses, potential opportunities in supply chain

Even in the wake of COVID-19 (coronavirus), manufacturers still need human workers to manage the supply chain. The need for more automation and information is an opportunity for manufacturers.

By ABI Research
MIT computer scientist Aleksander Madry. Courtesy: Ian MacLellan, MIT
AI and Machine Learning March 15, 2020

Doing machine learning the right way

MIT Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable and robust.

By Rob Matheson
Table courtesy: Control Engineering with information from Evonik at ARC Forum 2020, by ARC Advisory Group
Automation March 12, 2020

How to compete and win with automation

With automation at an inflection point, a variety of technologies and interoperable standards efforts are bringing higher levels of flexibility, integration and optimization.

By Mark T. Hoske
Courtesy: Inductive Automation
Data Acquisition, DAQ March 10, 2020

Software readiness for data analytics and Big Data

Expand industrial data access and get more out of it with tools such as message queuing telemetry transport (MQTT), which can help manufacturers realize Industry 4.0’s benefits.

By Travis Cox
Courtesy: Chris Vavra, CFE Media
Maintenance Strategy March 10, 2020

Preventing coronavirus through preparation

Many manufacturers are becoming increasingly concerned with Covid-19 breakouts on the production floor. There are ways to improve worker safety through preventive best practices and proper preparation.

By Eagle CMMS