Artificial Intelligence in Manufacturing: Industrial AI Use Cases
Among large industrial companies, 83 percent believe AI produces better results—but only 20 percent have adopted it, according to The AspenTech 2020 Industrial AI Research. Domain expertise is essential for the successful adoption of artificial intelligence in the manufacturing industry. Together, they form Industrial AI, which uses machine learning algorithms in domain-specific industrial applications. AI can be leveraged in the manufacturing industry through machine learning, deep learning, and computer vision.
Let’s explore some of the important trends in artificial intelligence technologies in the manufacturing industry to get a clearer picture of what you can do to keep your business up to date.
For all of the technologies that we’ll discuss that have applications in manufacturing industries, artificial intelligence is not the most accurate way to describe them. AI is a very broad subject that has many different methods and techniques that fall under its scope. Robotics, natural language processing, machine learning, computer vision, and more are all different techniques that deserve a great deal of attention all on their own.
Keeping that in mind, let’s talk about the many applications of artificial intelligence in the manufacturing industry– here are some industrial AI use cases.
Artificial intelligence studies ways that machines can process information and make decisions without human intervention. A popular way to think about this is that the goal of AI is to mimic the way that humans think, but this isn’t necessarily the case. Although humans are much more efficient at performing certain tasks, they aren’t perfect. The best kind of AI is the kind that can think and make decisions rationally and accurately.
Probably the best example of this is that humans are not well equipped to process data and the complex patterns that appear within large datasets. However, AI can easily sort through sensor data of a manufacturing machine and pick out outliers in the data that clearly indicate that the machine will require maintenance in the next several weeks. AI can do this in a fraction of the time that a human would spend analyzing the data.
Many, if not most, applications of artificial intelligence involve software instead of hardware. However, robotics is primarily focused on highly specialized hardware. The manufacturing industry utilizes this technology a great deal for many different types of applications. According to Global Market Insights, Inc, the industrial robotics market is forecasted to be worth more than $80 billion by 2024. In many factories, such as Japan’s Fanuc plant, the robot to human ratio is about 14:1. This shows that it’s possible to automate a great deal of a factory to reduce product cost, protect human workers, and achieve higher efficiency.
Industrial robotics requires very precise hardware and most importantly, artificial intelligence software that can help the robot perform its tasks correctly. These machines are extremely specialized and are not in the business of making decisions. They can operate supervised by human technicians or they can be unsupervised. Since they make fewer mistakes than humans, the overall efficiency of a factory improves greatly when augmented by robotics.
When artificial intelligence is paired with industrial robotics, machines can automate tasks such as material handling, assembly, and even inspection.
A term that often gets thrown around related to artificial intelligence and robotics is robotic processing automation. However, it’s important to note that this is not related to hardware machinery and is instead related to software.
Robotic processing automation is all about automating tasks for software, not hardware. It applies the principles of assembly line robots to software applications such as data extraction, form completion, file migration and processing, and more.
