Artificial Intelligence (AI) has made its impact on manufacturing, and the results have made it an absolute game changer. Those who adopted AI capabilities early have found them to be incredibly useful in automating tasks typically done by hand, which not only saved them a ton of time but also reduced the number of errors. But for others, AI still seems like something out of a science fiction movie, like I-Robot, and not a realistic option that can help with those real-life scenarios.
No matter which group you fall into, this blog is for you. We will be covering 4 real-world scenarios where manufacturers are using AI on their shop floor today, and what AI implementations you can expect to see in the near future.
AI is here to stay, let’s figure out where it can help your manufacturing business the most.
AI may seem like a new concept, but its use in manufacturing actually dates back to the late 1970s, when the robotic arm was created and used on assembly lines. Since then, AI has come a long way. Here are 4 real-world examples of AI’s use in manufacturing today.
One of the most significant ways AI is being used in manufacturing today is through predictive maintenance. Predictive maintenance is a proactive approach where data from equipment is collected and analyzed to identify patterns that can predict when maintenance is required. AI-powered predictive maintenance can detect potential equipment issues before they cause a breakdown, which can reduce costly machine repairs and downtime for your business. Most machines generate data, but there are many reasons why it can be tricky to retrieve and analyze it. If you have older machinery or inherited a machine that is hard to configure, there are improvements that can be made! Experts, like Software InsITe, specialize in working with this type of equipment and modernizing it so that you can receive the accurate, reliable data it outputs.
In addition to the cost-savings of avoiding downtime, think of the time-savings from not needing an employee to regularly check machinery for issues. This employee can now spend their time working on more essential tasks that will move your business forward, which will be a common theme in our real-world AI examples.
AI is also being used to improve the quality of manufactured products. AI-powered quality control systems use machine learning algorithms to identify defects, inconsistencies, and anomalies in the production process. AI can also be used to analyze data from sensors and cameras to detect defects in real time, which can reduce the number of faulty products and improve product quality.
For manufacturers, quality control is essential. Think about how this process has gone in the past, employees are tasked with inspecting products by hand, and if they were not there at the right time, a faulty machine could create hundreds of defective products before anyone noticed. Combining this with the ever-present possibility of human error proves the need for AI-powered quality control.
If you just want to dip your toe into AI, a small improvement in quality could pay back on the investment quickly.
Right now, supply chain optimization is on the mind of most manufacturers. With lengthy lead times and a growing amount of back orders, Manufacturers have been consistently searching for a better way to better forecast their products, delivery times, and cost. AI-powered supply chain optimization can analyze data from various sources, such as inventory levels, production rates, and transportation costs, to identify the most efficient and cost-effective ways to move products from one point to another. This helped reduce delivery times and costs, improve customer satisfaction, and increase profitability.
Predictive optimization on the complete supply chain is another handy tool. Companies like Llamasoft and Autoscheduler.ai are just two examples.
When discussing automation in manufacturing, we often think of it in terms of robots and heavy machinery. But AI can revolutionize many other processes manufacturers use daily. By using machine learning, AI can be used to automate repetitive tasks, streamline workflows, and improve efficiency.
Take your accounts payable processes for example, AI can process invoices, matching them with corresponding purchase orders and verifying their accuracy, significantly reducing the time and effort spent on manual data entry.
Another process that AI has made easier for manufacturers is quoting. AI-powered quoting systems use algorithms that can take your data, such as cost of materials and labor, time to manufacturer, and any other elements that are needed and generate accurate quotes in a fraction of the time.
AI can also be used as a powerful document management tool that can categorize and organize important documents. This makes it easier to find the most relevant information you need that will allow you to make quick business decisions. With AI's ability to learn and adapt over time, manufacturing companies can expect improved accuracy, increased productivity, and reduced costs associated with those processes.
As AI technology continues to evolve, we can expect to see more innovative applications of AI in manufacturing in the future. One of the more talked about trends in AI that can be used in manufacturing is ChatGPT and Chatbots.
Chatbots have emerged as a valuable tool for manufacturers. These virtual assistants have many potential uses, including customer service, technical support, and supply chain management. Chatbots can provide instant and personalized client communication in real-time, such as answering inquiries, order updates, and troubleshooting.
Chatbots can also be used to work with clients, employees, or other equipment users on ways to maintain your machinery and fix common problems, which are typically time-consuming jobs done by humans.
As mentioned above, AI is here to stay. As we dive deeper into Industry 4.0 and into Industry 5.0, manufacturers are finding AI more and more ingrained into their manufacturing processes. To put it simply, if a task is repeatable, then it can and will be automated in the future. So where do you start?
Working with a partner, like Software InsITe, can help your organization identify which processes can be automated, and work with you to implement AI and machine learning to achieve that automation. They can get you set up with the right tools, tracking, and sustainable processes to get you started on your automation journey.