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Artem Kroupenev


Four AI Trends That Will Impact Manufacturing in 2022

What is your organization’s digital strategy?

Published: Monday, January 17, 2022 - 13:02

The manufacturing industry was thrown into the spotlight early in the pandemic as consumers rushed to stores, panic-buying everything from canned goods to water bottles. Since then, the industry has had more than its fair share of challenges, including the critical ramp-up of vaccine and pharmaceutical production, supply chain disruptions, and more. All these factors have helped usher in a period of rapid digital transformation across the sector.

The pandemic has supercharged AI investment and adoption by manufacturers and other industrial sectors. Across the board, we’re hearing from customers that they have accelerated their digital strategy plans, many of which revolve around AI adoption, by years as a result. Below are a few key trends and predictions on how AI’s role will impact and evolve within the industrial sector over the next year.

AI will help address a growing skills gap

For the manufacturing industry, which has already been experiencing a talent gap and an aging workforce, an acceleration of AI adoption will help recruit new talent. As innovation speeds up, industrial markets and applications will be responsible for some of the biggest AI breakthroughs of 2022 and beyond. This will draw new tech talent into the industry that wants to be at the forefront of this innovation.

AI is also reshaping roles on the factory floor. Workers want to feel purpose in their jobs, and one way to achieve this is through creating technology that frees employees from repetitive tasks and allows them to take on more analytical, higher-value work. Investing in technology and reskilling employees to work in a high-tech environment with AI can shift the perception of manufacturing from the dirty job of yesterday to the high-tech environment of tomorrow.

Full-stack, problem-specific AI thrives as generic AI fades

Pre-pandemic, AI was a nice-to-have and often would get stuck in the pilot phase becuase the purpose of adoption was unclear. The pandemic has created a philosophy shift where manufacturers are using AI to solve real-world problems that can’t be addressed by traditional tactics. As a result, investment will be focused on full-stack AI solutions—which include the hardware required to gather data as well as the machine learning models using the data—that can solve specific problems fast. This will displace more generic AI tools that have to be trained and customized by customers before they show value.

Sensor-agnostic AI

Full-stack AI solutions like Augury’s Machine Health include sensors to gather vibration data and AI models that learn from and predict based on the data. The combination of IoT-enabled sensors and AI is a powerful one. However, it’s common for manufacturers to gather a variety of sensor technologies over the years as they seek the best solutions available on the market. It’s extremely difficult for an AI model trained with data from one vibration sensor to make accurate predictions using real-time data from another. AI vendors that rely on sensors are quickly seeking to become sensor-agnostic to overcome this challenge and to utilize existing infrastructure. At Augury, we developed a novel method for learning the frequency-response difference between various vibration sensors so that we could apply a pre-trained machine health model to any type of sensor, including those made by other companies. This is extremely rare, but this type of sensor-agnostic AI strategy is something we expect to become a major trend during the next year.

The movement toward insurable AI

Like humans, AI systems sometimes make mistakes that result in real-world losses. As more startups and companies enter the AI market, it becomes harder for customers to determine which vendors can deliver significant value and how to manage the potential risks. Insurers are already starting to vet and guarantee the outcomes of some AI products, and provide insurance products covering the risks gives enterprises the reassurance they need to speed up AI adoption. It’s a trend that manufacturers need to be aware of as the AI they adopt becomes responsible for more high-stakes activities.

Manufacturers need to be able to keep up with the AI trends that are developing because they will be responsible for shaping what the manufacturing plant of the future will look like. Some of these trends will move more quickly than others, but we expect them to all come to fruition over time.


About The Author

Artem Kroupenev’s picture

Artem Kroupenev

Artem Kroupenev is the Vice President of Strategy at Augury where he oversees AI-based machine health and digital transformation solutions.