The modern factory is a highly digitized environment, with machines and sensors everywhere. Assembly lines have been early adopters of automation technologies for years, but there’s still room for improvement. Artificial intelligence enables manufacturers to reach the full potential of assembly lines, fully automated or otherwise.
AI is still a relatively new technology, so some manufacturers may be hesitant about adopting it. While it’s often a significant investment, AI systems can lead to an impressive return. Running an assembly line involves a lot of data points that AI can use to create a more efficient environment.
Here are just a few ways artificial intelligence can change assembly lines for the better.
Finding and Fixing Inefficiencies
One of AI’s greatest talents is finding connections in data sets that humans may miss. It’s why many organizations use machine learning programs to handle their big data analytics. It’s also why AI is particularly helpful for assembly lines wanting to become more efficient.
If an assembly line gathers enough data from their process, AI can analyze it to find inefficiencies. It can then use predictive analytics to suggest possible changes or even implement them automatically. A busy human employee may not be able to see all the room for improvement that AI can.
In one case, an AI asset optimizer improved production output 11.2% more than a manual optimizer after just eight months. That may seem like a small increase, but it would certainly produce a noticeable difference over time.
Predictive Maintenance
Automating an assembly line with robotic arms and other machinery is an excellent way to increase efficiency. While robots don’t need a salary, they do come with some economic concerns of their own. They run the risk of malfunctioning or breaking down unexpectedly, which can be a problem.
Manufacturers can account for gradual wear and tear, but sometimes machines break down seemingly out of the blue. If this happens, it can take weeks to repair, which can cost a lot of money and upset customers. AI can analyze machines’ performance and warn workers if they need maintenance soon.
This process, called predictive maintenance, can help manufacturers address issues they may not see otherwise. While a potential problem may not be visible to a person, it could be to an AI system. By warning of malfunctions ahead of time, predictive maintenance can help assembly lines avoid expensive downtime.
Detecting Defects with Machine Vision
Even if the rest of the assembly line isn’t automated, AI can still offer substantial improvements. One of its most promising applications is in quality control, which it can handle through machine vision. Intelligent systems at the end of an assembly line can find defects faster and more accurately than people.
A lot of factors could lead to human quality control checkers failing to notice product defects. While things like exhaustion and boredom can hinder people, machines don’t get tired or bored. An AI quality checker would give a consistently accurate analysis no matter how long it’s been working.
With machine vision, manufacturers translate the visible world into data, and AI can analyze that information faster. As a result, AI quality control could provide better results in less time than a traditional system. Assembly lines could ensure that they produce defect-free products and do so in less time.
The Assembly Line of Tomorrow
The advantages of AI in the assembly line are too substantial to go unnoticed. Before long, using AI in at least one area of the assembly line could be standard practice. It will more than likely see widespread adoption across multiple areas.
The fourth Industrial Revolution, or Industry 4.0, is one driven by data and data-centric technologies. Without AI, manufacturers can’t use this data to its fullest extent. AI isn’t just another possible improvement ” it’s a necessity for companies to make the most of Industry 4.0.
