Rethinking How to Purchase Industrial Automation


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Rethinking Your Approach for How you Purchase Automation

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🏒 Organizations: Yaskawa

The past 20 years have seen a transformation in new automation components and in the way that they are designed and applied. Consider a variable frequency drive that operates a motor at a different speed depending on the needs of the application, instead of constantly running all out. Today, VFDs have become specialized for particular industries and packed with more functionality that makes them easier to integrate and operate for specific applications. Open network communications and industry standards have enabled automation manufacturers to design their products to be more interoperable with those of their competitors.

Read more at Food Engineering Magazine

Getting Industrial About The Hybrid Computing And AI Revolution

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✍️ Author: Jeffrey Burt

πŸ”– Topics: IIoT, machine learning, reinforcement learning

🏭 Vertical: Petroleum and Coal

🏒 Organizations: Beyond Limits

Beyond Limits is applying such techniques as deep reinforcement learning (DRL), using a framework to train a reinforcement learning agent to make optimal sequential recommendations for placing wells. It also uses reservoir simulations and novel deep convolutional neural networks to work. The agent takes in the data and learns from the various iterations of the simulator, allowing it to reduce the number of possible combinations of moves after each decision is made. By remembering what it learned from the previous iterations, the system can more quickly whittle the choices down to the one best answer.

Read more at The Next Platform

Seeq Accelerates Chemical Industry Success with AWS

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πŸ”– Topics: IIoT

🏭 Vertical: Chemical

🏒 Organizations: Seeq, AWS, Covestro, allnex

Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, today announced agreements with two of the world’s premier chemical companies: Covestro and allnex. These companies have selected Seeq on Amazon Web Services (AWS) as their corporate solution, empowering their employees to improve production and business outcomes.

Read more at Automation

The Challenge with AM Process Substitution

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✍️ Author: @PSUMakerProf

πŸ”– Topics: additive manufacturing, 3D printing

🏒 Organizations: Pennsylvania State University

I have lost track of how many times I have stressed the economic (and technical) challenges companies face when attempting process substitutions with additive manufacturing (AM), or what I often refer to as β€œreplicating” a part with AM. In short, everyone thinks a metal AM part is going to be cheaper than the machined, cast or forged version of the part (or as strong as the injection-molded part for those working in plastics) based on the hype, only to find that it is not. The β€œsticker shock” and disappointment that ensue often dampens the enthusiasm for AM and can undermine future AM investments, creating an uphill battle for AM.

Read more at Modern Machine Shop

Improving Cycle Time with Veo FreeMove – Estimating the Benefits with a General Example

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✍️ Author: Alberto Moel

πŸ”– Topics: robotics, cobot

🏒 Organizations: Veo Robotics

In our model, the design and operation of the application will determine how and how often the human and robot will collaborate. At one extreme, there is no collaboration, and the application runs unattended throughout the operating cycle. At the other end, human interactions can occur multiple times a cycle, as in a parts presentation for assembly application. We concluded that the shorter the cycle time and the more frequent the required human interaction the more collaborative the application.

Read more at Veo Robotics Blog