v News Roundup: Physics, Machines and Data - May 2020 - Tignis

News Roundup: Physics, Machines and Data – May 2020

Author: Jon Herlocker

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Tignis May 2020 Roundup

Our team is always keeping an eye on news surrounding digital twins, machine learning, data analytics and more. Here are a few articles that we found especially interesting during the month of May.

Adopt Digital Twins to Mitigate Impact of Pandemic – MachineDesign

MachineDesign wrote an excellent article on how organizations navigating the pandemic are preparing for the “new normal.” According to the interview of Karen Panetta, dean of graduate engineering at Tufts University, and pioneer in the development of digital twins, “The pandemic acts as a catalyst for extending technologies and digital twin simulation can be a critical tool in a proactive, strategic response.”

In a detailed Q&A, Ms. Panetta discusses the utility of digital twins, as well as what we can expect in the future. She shares, “Employing digital twins can expedite an enterprise’s efforts by giving it the ability to anticipate stress points, enable more efficient model adaptations and more quickly rework its processes.”

Don’t Rush Digital Transformation: 8 Considerations in a New Era – Industry Week

Stephan Liozu breaks down eight considerations for manufacturing leaders to think about as they redesign their digital programs. He presents how to best approach “digital transformation 2.0” – a new normal that will be much more practical, realistic, and focused on impact.

He shares valuable considerations including clear focus, greater levels of integration and coordination between the core legacy entities and the digital business, recognition of true digital innovations as new business models, and more.

A Guide to Industry 4.0 Predictive Maintenance – IoT For All

IoT For All takes a deep look at predictive maintenance – everything from the differences between preventative and predictive, to how it works, advantages, and implementation. With the introduction of machine learning, the manufacturing sector is presented with a massive opportunity to improve the efficiency of their maintenance programs.

This article’s takeaway: “The advancement of AI and ML will assist in predictive maintenance, ultimately providing businesses with an extreme advantage over anyone not moving towards industry 4.0.”

3 Real-World Applications for Pneumatics and IIoT – Design World Online 

This article provides specific and insightful scenarios for real-world applications of IIoT-enabled pneumatics. It touches on common goals for manufacturers and industrial operations, such as improving safety, improving predictive and preventative maintenance effectiveness, increasing energy efficiency, and more.

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