Top 8 AI Applications In Manufacturing in 2021

AI in Industries

During the COVID-19 pandemic, economic ramifications and uncertainties have greatly influenced manufacturers and manufacturing companies, who are striving to master cost cutting, resourcefulness, time management and the ability to adapt. Louis Columbus writes that these goals have led to a level of determination in manufacturers to utilize “AI driven pilots and analytics” wherever possible, combining them with human effort while “driving down costs and protecting margins,” among other goals.

Here are our Top 10 AI applications in manufacturing, what they achieve, and how they can benefit manufacturing companies during the economic overhaul of 2020 and 2021.

Quality Control

Manufacturing companies are incorporating machinery designed with cameras into their business models, which are able to detect flaws in products that “are too small to be noticed with the naked eye,” which in turn allows for human effort to be focused on other tasks, in addition to more efficient quality control. Furthermore, machines are able to notice design flaws while the production process is ongoing, leading to necessary improvements before it is too late and products are about to be shipped. Another positive aspect to AI focused quality checks is an improved social distancing environment for employees during the COVID-19 pandemic, with less human employee presence needed for quality control purposes.

Machinery Maintenance

Modern AI applications allow for faster repairs when setbacks in production occur, such as any machinery deterioration or defects in crucial equipment. Louis Columbus notes that “29% of AI implementations in manufacturing are for maintaining machinery and production assets.” These implementations are able to predict when machinery will fail, again by using cameras that analyze and take photos of the assembly area, allowing for prevention of outages or major setbacks in production.

Customer Satisfaction

Manufacturing isn’t the first sector that comes to mind when we consider customer service, since these jobs are not typically customer facing roles. It is important to not overlook the importance of customer satisfaction, however, and strategies involving AI that focus on customer insight are becoming more prominent. An example of this would be the reveal of Nokia’s 2018 Cognitive Analytics For Customer Insight software, which allowed for the company to begin rapidly noticing any flaws, such that they could make any necessary improvements.


Keeping up with supply and demand is one of the most important tasks for manufacturers, and rapid shifts in demand during the COVID-19 crisis can make that extremely difficult for human employees to manage alone. Artificial intelligence assets used by companies in 2021 are able to predict demand through AI-powered demand forecasting, allowing them to sufficiently manage and prevent inventory-related issues, such as running out of stock or having too much stock on hand.

Business Modelling

When machines and artificial intelligence are able to learn and observe a company’s performance, they can then generate data that company executives can use to create “new, comprehensive business models and protocols.” Extending the company and the company’s influence, generating more business opportunities, and developing new protocols to follow are just a few ways that AI technology can influence business modelling. This is mainly due to its ability to objectively pinpoint trends, void of human bias and opinion.

Safety Measures

Some companies have taken on the responsibility of protecting their employees by using robotic presence in highly dangerous areas where production occurs, such as industrial plants. There can be up to 3000 injuries per year in “the highest risk industrial sectors,” such as plastic and metal manufacturers. The goal in 2021 for several of these companies is to make use of robotic overseers who are able to detect dangerous conditions and prevent these tragedies.

Production Continuation

A new trend in 2021, “dark factories,” otherwise known as factories with little to no human labour, can function 24/7, with no need for meal breaks and of course, wages. What’s more, robots arguably require no light to function, cutting back on the cost of utilities for companies and allowing for the name “dark factory.” Dark factories seem to be an inevitability for certain sectors as they maximize efficiency and production, drastically cut costs and reduce workplace injuries.


It’s common knowledge that a human being needs an adequate amount of training to perform their job well, which can sometimes take up to two or three months to achieve in the manufacturing sector where detail and proficiency are key. You only have to train artificial intelligence and robots once, and programming these machines properly the first time will allow for production optimization and less time spent hiring and training employees. Moreover, companies can save time by focusing less on correcting human errors, replacing unsatisfactory employees and searching for adequate employees.

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