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Three Production Benefits to AI in Manufacturing

AI is crucial to manufacturing. According to a recent Forbes Insights survey, AI is deemed important today by 44% of those surveyed. In the upcoming five years, 49% say artificial intelligence will be critical to success in manufacturing. Why is AI in manufacturing so important? Artificial intelligence in manufacturing can offer a host of benefits to a manufacturing operation. Let’s look at three ways artificial intelligence technology can be a major benefit to production in manufacturing.

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How 5G is Transforming Manufacturing

The advent of 5G technology is a highly anticipated tech innovation, particularly in the manufacturing sector, which is poised to benefit greatly from this development. With promising benefits such as super-fast connection, low latency, ultra-reliability, more bandwidth than Wi-Fi and 4G LTE, and support for thousands of devices in one location, no wonder everyone is excited about 5G technology.

With 5G, you can browse the Internet ten times faster, download a full-length movie in less than a minute and stream crisp, clear 4K video. However, the full potential of 5G technology can only be realized when the extent to which it can fundamentally change the manufacturing sector is established.

To understand how 5G technology can revolutionize manufacturing, we’ll talk about how 5G is set to transform the industry.

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Doing Machine Learning the Right Way

The work of MIT computer scientist Aleksander Madry is fueled by one core mission: “doing machine learning the right way.”

Madry’s research centers largely on making machine learning — a type of artificial intelligence — more accurate, efficient, and robust against errors. In his classroom and beyond, he also worries about questions of ethical computing, as we approach an age where artificial intelligence will have great impact on many sectors of society.

“I want society to truly embrace machine learning,” said Madry, a recently tenured professor in the Department of Electrical Engineering and Computer Science. “To do that, we need to figure out how to train models that people can use safely, reliably, and in a way that they understand.”

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Optimizing with Automation

Companies today see the potential that exists with automation. When looking towards the optimization of a facility, it is imperative to plan and understand the needs of the operation. Depending on each given business, different automated applications will be best-suited for each respective operation.

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Upcoming Trends in Automation: Looking Towards the Future

 

In today’s society there aren’t many places to go to escape technology. It is a never-ending evolution. The sooner technology is embraced, the sooner it will benefit the world. This is evident in how technological advancements have changed businesses operations.

Digitalization

With technology comes digitalization and with digitalization comes the ability to convert information into digital form. This ability has allowed businesses to increase efficiency, reduce operational cost, and eliminate human error. One example of a benefit is businesses can now keep important information on digital files instead of paper files. A computer with named files neatly organized to a specific format allows easier access compared to opening a file cabinet and shuffling through hundreds of manila folders.

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Is the Pulp and Paper Industry Ready for Machine Learning?

Few industries have seen more transformation over the past decade than that of the pulp and paper industry. Gone forever is the ability of the business to rely heavily on staples such as newsprint and glossy magazine paper. Use of electronic devices and media have reduced considerably even the need for paper in the office environment.

Add to this the constant external pressures from government and other organizations pushing for stricter environmental standards. To compete, the paper and pulp industry must embrace efficiency producing new technologies that can save time and money.

While some see machine learning and related technologies as a threat to companies and jobs, these developments will help ensure the long-term survival of both.

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PLM: Where It Began, Where It's Going

Product lifecycle management, or PLM, is the process of managing the entire lifecycle of a product from inception through end-stage disposal. It is sometimes considered one of four information technology cornerstones for a manufacturer, alongside customer relationship management (CRM), supply chain management (SCM) and enterprise resource planning (ERP).

The PLM concept began in the mid-1980s when American Motors Corporation (AMC), intent on establishing a competitive advantage over the auto industry giants of the time, put its focus on using technology to speed the product development process. Although AMC was ultimately acquired by one of those giants, its innovations were integrated into modern manufacturing tech and have played an invaluable role there ever since.

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Eight Keys to Better Asset Reliability

If you’re a manufacturing plant manager, what don’t you want to see out to the production floor? Probably a significant number of things, but near the top of that list would probably be a large group of workers congregating around a critical piece of machinery that should be running—yet isn’t. Rarely does such a sight have positive implications.

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A New Age Approach to Traditional Manufacturing Issues

As the virtual world collides with real-world manufacturing issues, the winners will be those who successfully navigate the challenges of both the technology and the people who will operate it. That was the central theme of the 2018 Global Automation and Manufacturing Summit (GAMS), presented by CFE Media and Hannover Messe USA and sponsored by Siemens, SAP, Advantech, Beckhoff, Infor, Stratus, UL, Universal Robots, and Lapp.

The half-day thought leadership event that took place Sept. 12 as part of IMTS 2018 in Chicago drew a full house of manufacturing leaders looking to navigate the challenges faced in an age of robotics, artificial intelligence (AI), and the Industrial Internet of Things (IIoT).

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