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Industrial Processes & Wireless Communications – Part II: Manufacturing Logistics

Cisco Manufacturing

The Internet is littered with articles about Industry 4.0. Examples are, mobile robots, AGV(automated guided vehicles), and manufacturing infrastructure. Such articles often leave out critical details, such as what is actually needed from the network. 2) Manufacturing logistics. 2) Manufacturing logistics.

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Latest IIC publication discusses role of IoT in future of supply chains

Automation Mag

The Industry IoT Consortium (IIC) released the latest edition of its Journal of Innovation (JoI) titled The Role of IoT in Shaping the Future of Supply Chains. Early Learnings from a Logistics Testbed – Investigates data logistics ecosystems based on existing IIC testbeds.

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Boosting supply chains through automation and robotics

Control Engineering

Supply Chains Insights. The pandemic has put a spotlight on supply chain issues when demand for critical products went up and the supply side couldn’t keep up. are small and medium-sized manufacturers (SMMs), according to the U.S. Since over 98% of suppliers in the U.S.

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Logistics, robotics advances at the heart of improving automation

Control Engineering

ProMat emphasized material handling and logistics; Automate emphasized robotics and automation. This is the way of the future in manufacturing, warehousing and logistics. Robots — industrial and collaborative — are being applied to more manufacturing applications. It’s a twofold challenge,” said Steve Pinsky at Fortna.

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More sensors, despite strained supply chain

Control Engineering

Other issues in 2022 include threats of energy shortages in Europe, high inflation and rising interest rates in many countries, supply and logistics chains that are strained and persistent COVID lockdowns in China. The post More sensors, despite strained supply chain appeared first on Control Engineering.

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2023 Manufacturing Outlook

ATS

Share The manufacturing outlook for 2023 is best described as cautiously optimistic. That component of the manufacturing industry outlook is derived from several underlying — and in some cases, ongoing — industry and macroeconomic factors that may threaten sustained growth in the near term. So, why “cautiously”?

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Applications of Machine Learning in Manufacturing

ATS

is increasingly commonplace in manufacturing, with one subset in particular gaining a strong foothold: machine learning. As manufacturers look for more innovative ways to increase stability, resiliency, responsiveness and, as always, efficiency and profit margins, machine learning and manufacturing are proving to be a natural fit.