Entering and becoming a recognized player in the global markets is harder than ever before. Manufacturers have to bring their companies to the highest level and optimize every part of their operations according to the latest practices.
Everything from the use of materials, to order management, product design, engineering, logistics, and services have to work in perfect harmony to ensure success. To do that, organizations have to ensure that they get the most out of the data they generate, and that's where AI can help a lot. It is transforming the manufacturing business, and it's here to stay.
You've probably already heard the term "artificial intelligence." Before we get into the details, let's start by saying that it's a general term used for all kinds of software solutions designed to mimic human behavior. There are many different types of AI. For example, some of them are designed for learning, others focus on solving problems, while some excel in making plans.
AI today has a huge application across many different industries, and it helps simplify tasks through automation. It took years of hard work and development to get artificial intelligence to where it is today. Machine learning and deep learning, AI software is now able not only to mimic human behavior but also surpass the capabilities of a human significantly. That's why many businesses, operations, and companies worldwide started using AI to improve their projects.
Most AI models use machine learning to understand what the operation needs to improve efficiency and productivity. ML is used to help gather and read massive amounts of data by using advanced algorithms to find connections between the data and find correlations between different pieces of information. After some time, the AI model can learn how the system works, find potential weak spots, and propose the best solution. With sensors and the internet of things or IoT, people can keep track of what the AI is doing.
Let's say that you work in a manufacturing factory where all machines and devices are connected to a single network. Every element generates data about what it does, the production, and other details you can see from the central control room. However, a human can't possibly keep track of every single element in the factory, no matter how hard they try. That's where machine learning makes the most difference. It's able to track every element, find anomalies and identify patterns. Once it learns how everything works, the AI can propose solutions to improve overall efficiency and get better results.
Artificial intelligence is slowly taking over managing manufacturing processes in organizations everywhere. The market keeps growing steadily every year, and it's predicted that Ai in manufacturing will hit $17.2 billion by 2025. Here are the most common use cases of AI in manufacturing business right now.
The combination of AI and IoT in manufacturing results in inaccurate predictions that can help avoid machine failure and drastically shorten downtime. Predictive maintenance is a practice that helps prevent issues and find solutions to problems quickly and efficiently.
From the manufacturer's viewpoint, predictive maintenance offers significant benefits. It's an asset that can save the company a lot of time and money. When set up correctly, manufacturers can boost productivity by as much as 40% while reducing maintenance costs by 10%.
Quality testing is a key part of any manufacturing process, and AI can help bring it to an entirely new level. ML and image recognition can help manufacturers automate all kinds of processes including visual inspection, error detection, etc.
Moreover, you can set up triggers that eject faulty products from production automatically. That can help boost savings substantially and increase productivity by as much as 50%. Defect detention rates can go up by 90% when compared to human inspection. AI simply doesn't make the mistakes an average worker does.
AI can also help decrease scrap rates from defective products to improve the overall value you get from the materials used during the production. By using ML, AI solutions can quickly identify losses and propose solutions on how to reduce waste. Sometimes, a simple change can make the most difference, and AI can help identify production processes and design flaws.
Better manufacturing processes and product design mean that you'll minimize scrap rates and testing costs, which can help reduce overall production costs by as much as 30%.
AI can also help improve workplace safety, and it turned out to be extremely efficient during the COVID-19 pandemic. AI can monitor employee interaction for contact tracing. Every employee can wear a small card on them, and the AI will quickly locate all potential contacts in case someone gets infected.
Furthermore, AI can also help find the best long-term solutions to minimize potential workplace injuries. As a result, all employees will work in a safer workplace, and the risk of injuries won't be an issue anymore.
Making sure that the products reach the right destination within a complex supply chain is no easy task. Many manufacturers have to handle hundreds of different components and tools to keep everything running smoothly. One wrong delivery can result in expensive delays or a complete product line shutdown, and no one wants that to happen.
AI is much better at identifying and managing complex interactions between different units than any human. It uses automation to ensure that all parts, tools, repairs, and labor are done on time. As a result, companies that use AI to manage supply chains can reduce forecasting errors by as much as 50 percent. The practice has a positive effect on sales and stock management, reducing inventory by up to 50 percent in some cases.
Product research and development usually involve multiple engineering teams and departments. The constant back and forth communication between departments often prolongs development and complicates the entire process. However, with the use of AI, engineering teams can improve collaboration. Artificial intelligence will find the best solutions, materials, and identify design flaws in the earliest stages of product development.
Designers can take a different approach to a problem by defining the goals of the product. Once it understands the final goals, AI is able to propose various design solutions, some of which would be impossible to create by humans. Not only that, but it will also help reduce overall costs up to 15% and improve product release time by up to 10%.
Cybercrime is a serious threat for companies worldwide. No matter how good of a system you might have, a single mistake can end up costing your company millions of dollars in damages. However, you can leverage AI to identify threats and find the best solutions before the damage is done.
Every manufacturing business or plant works with tons of sensitive data such as security logs, networking data, and security applications. AI can help filter through all data to identify potential risks, fraud, malware, and pinpoint risky employee behavior.
AI can also help companies manage human resources, improve financial operations, and organize IT management using automation. For example, when coupled with robotic process automation AKA RPA, AI can fully automate routine activities such as providing more efficient customer support. Automating most IT functions can boost the overall customer experience by as much as 90%.
Even though AI is still gaining popularity, it is already showing considerable improvements in manufacturing, business, and management processes. The right AI solution has the power to streamline everything from product development to manufacturing, logistics, customer support, and other critical elements.
Automation and RPA can help increase employee productivity, boost product release times, and ensure that all production lines keep working perfectly. There's no doubt that AI is transforming manufacturing, and we can't wait to see its full potential in the following years.