Ever since artificial intelligence went mainstream, people have been finding new ways to use it for different applications. If we take a look at recent events, ChatGPT and Midjourey are perfect examples of the innovative ways we can use AI.
However, these AI-based web apps are manufacturing digital products. What about their application in more practical scenarios, say warehouse automation in a car manufacturing company? Can they help with those as well?
Today, we’ll be taking a closer look at the matter to understand how artificial intelligence is being used to revolutionize the everyday manufacturing industry.
What Is AI in Manufacturing?
Taking a look at the machinery being used in manufacturing plants, we see that most of them come with different sensors that generate real time data. Using all this information, it’s possible to apply machine learning algorithms to analyze it and make better decisions.
That is actually the essence of AI in manufacturing. One of the most common applications that I’ve found in this regard is predictive maintenance. It uses the generated real-time data to anticipate repairs and when they might be needed.
By planning ahead of time and identifying the underlying issues, it’s possible to reduce the cost of maintenance in the manufacturing process.
It’s important to note that AI based predictive maintenance isn’t the only application in the manufacturing industry. Production lines can apply the same technology to get more accurate results for demand forecasting.
Another popular case of applying AI in manufacturing is reducing material waste. For example, the sensors built into the machines at a smart factory can be used to calculate the exact amount of materials needed. This data can then be used to program the machines to stop creating additional waste.
Key AI Segments That Impact Manufacturing
Artificial intelligence isn’t just one concept. Rather it’s a combination of technologies and systems that mimic a human being that can solve different problems. Some of the popular examples of AI are image and video recognition, image classification (telling the image of a dog apart from a cat), supply chain management, simulation for different systems, and so on.
But as I’m focusing on AI in manufacturing, there’s no need to focus on all the concepts. Here are the ones that we need for today:
- Machine Learning: An application of artificial intelligence, machine learning algorithms can be used to teach the machine the process of carrying out a task. It can also be used to analyze data and make predictions. This is the foundation for predictive maintenance that I was talking about.
- Deep Learning: Think of this as an application of machine learning. By using different algorithms and neural networks, we can use deep learning to analyze images and videos. In the manufacturing industry, this can be used for quality assurance.
- Autonomous Objects: A lot of machines are needed in the different manufacturing processes. You can see AI being used for Robotic process automation where it acts as the brains of the machine.
How is AI Used in the Manufacturing Industry?
From robotic workers to autonomous vehicles, AI is being used in the different spheres of the manufacturing industry to do complex tasks. It also takes care of the time consuming tasks that human workers struggle with.
Let’s dive a little deeper and see how artificial intelligence is being used in more detail.
Robotic Process Automation
Industrial robots are one of the most common examples of advanced manufacturing technologies. These can greatly reduce the rate of human error and improve efficiency. This eventually results in higher production rates.
It also frees human workers who can be reassigned to tasks that can’t be carried out by AI technologies.
Supply Chain Management
Supply chains can greatly benefit from the use of artificial intelligence. This is made possible through forecasting and taking stock of their products.
Let’s say a cyclone is due to pass over a small town forcing people to remain inside their homes. Families will want to stock up with supplies so that they don’t need to endanger themselves when going out.
The sudden increase in the sale of these products can be predicted using AI, informing the supplier to increase production. That way, the supply chain won’t be disrupted.
AI Based Product Development
AI solutions can be used to create products directly from scratch with the right specifications. For example, Fusion 360 from Autodesk can suggest different iterations of your product during the initial stages. Using artificial intelligence, the tool can suggest different designs for connecting two faces of your product. All this is done while reducing waste and minimizing the manufacturing costs.
Internet of Things (IoT Devices)
If you don’t know what IoT is, here’s an example to help you understand. These days, most of us are using smartwatches like the Apple Watch, or an Amazfit. Using the smartwatch apps, you can track how many steps you’ve taken in a day. That’s used to calculate the amount of calories that you’ve burnt.
All of this is made possible because of the sensors built into the watch to track your movement. This is a prime example of the application of an IoT device.
If I have to put it in the perspective of the manufacturing industry, then there are sensors within the machine that transmit real time data on the machines. If the production of a particular design causes a machine to overheat, that’s an indication that you need to make changes to it.
Quality Assurance and Inspections
Earlier, I was talking about how AI can be used to recognize images and videos and classify the subject of a picture. These things are part of a concept called computer vision which deals with image recognition and classification. But how does that fit into the manufacturing process?
Quality assurance and control are two important parts of any production process. Using high-resolution cameras and computer vision programs, it’s possible to assess the product quality as soon as it’s made. If there are any defects, the software will catch those immediately and they can be fixed before they’re shipped out.
This will ultimately result in recalling fewer products and reducing waste. Customers will also be satisfied when they get exactly what they paid for.
Success Stories of Customers Using AI in Manufacturing
The use of AI in manufacturing companies is not just a concept. Several well-known companies have been implementing AI for a while now. This has allowed them to reduce operating costs, preserve product quality, improve productivity, and increase the efficiency of the assembly line.
To give you more context, here are some manufacturing examples from companies that are using AI systems.
Improving Safety in Manufacturing Settings
Schneider Electric is a company from France that specializes in digital automation and energy management. It’s well-known for its predictive maintenance approaches using IoT devices. The predictive analytics solution has been reported to improve safety resulting in revenue growth.
The tool is based on Microsoft Azure Machine Learning service and Azure IoT Edge. With the help of these two programs, a production floor operator can build models. These programs can predict failures based on equipment performance. If there’s a need for machine maintenance, these models can forecast when and for what capacity it’s needed.
Unleashing the Value of Instrumentation Data
No one can deny the value of instrumentation data in the manufacturing industry. It can increase efficiency and reduce the production time. Several manufacturers are already using precise values to assess the quality of their products.
We’re all familiar with the popular snack, Cheetos. While you might have had it on several occasions, did you know, PepsiCo is implementing AI in manufacturing it? The company is using a tool called Project Bonsai which uses computer vision to asses the production quality.
The production of Cheetos requires precise information on the water ratio in the mix and the cutting speed for each individual chip. Keeping these parameters in mind, the system can detect changes when something’s out of place and inform the operator. That’s how you get the same taste every time you buy a pack of Cheetos.
Besides this, AI is also being used in the semiconductor industry to increase the efficiency of chip production. AI solutions like Synopsys DSO.ai are completely changing the way these electronic components are being manufactured using
How Does AI Drive the Manufacturing Process?
So far, I’ve talked about the different uses of AI in manufacturing. But we need to consider the effects of taking advantage of the AI’s ability. The priority should be placed on minimizing risks and any possible negative impact that they may have on human counterparts and the environment. Here are some of the things to consider.
Using AI Responsibly
Just because it increases production and improves infrastructure performance, doesn’t mean we should use AI without any ethical consideration. As robotic workers powered by artificial intelligence pose a risk of job displacement, manufacturing companies need to think about this before going for AI automation.
A good alternative could be to train human counterparts to use AI systems to do a better job. An employee could be trained on how to read the data generated by IoT sensors. This person can later be reassigned to a job of continuous monitoring.
Transforming Production and Distribution
Thanks to AI we’re able to give birth to a physical object down to the minute specifications from our concepts and imagination. We’ve already seen how the application of different AI systems and tools can be used to automate the production process from start to finish.
And once it’s ready, AI tools can also be used for last-minute quality checks to ensure everything goes as planned. Improving production efficiency can also increase distribution rates with the help of AI.
Manufacturing a Resilient, Sustainable Future
If you think about what drives the AI system, it’s mostly machine learning algorithms working behind the scenes. The models created with these require a large amount of computational power. This means more energy consumption which can leave a huge carbon footprint every year.
Another obstacle to consider would be waste disposal. Since AI programs are built to maximize efficiency, faulty machinery will need to be replaced earlier than companies are used to. This can tally up to become a huge source of waste being produced. A solution for these issues needs to be found before you want to adopt AI.
How Is AI Used in Manufacturing?
AI can be used in different ways in manufacturing processes from autonomous robots making complex products to catching errors naked to the human eye. It can also lower costs and inform workers about machine maintenance as well as improve supply chain efficiency.
What Is the Future of AI in Manufacturing?
As AI technology is constantly evolving, AI will soon be implemented to remove the need for human intervention. These human workers can be reallocated to perform tasks that require human thought and oversee QC.
What Are the Challenges of AI in Manufacturing?
Although it has several benefits, like all other technologies, artificial intelligence comes with its fair share of challenges as well. Early adopters of AI in manufacturing need to consider issues like job displacement, energy consumption, electronic waste, and storage solutions for big data.
How Do You Leverage AI in Manufacturing?
Production facilities are concerned with decreasing production times, lower costs, and improving efficiency by having machines carry out repetitive tasks. You can leverage automation and AI solutions to carry out these tasks by utilizing instrumentation data from sensors and AI models.