Once thought of as the preserve of large tech conglomerates, artificial intelligence is becoming more commonplace in today’s economy. In fact, 37% of businesses are already using AI, and that number is going to grow exponentially in the next few years.
By 2030, it’s thought that AI will make up $15.7 trillion of the global economy, and it is expected to have a particularly profound impact on manufacturing in the coming years. Here is how AI is shaping the manufacturing sector in 2022 and beyond.
How Is Artificial Intelligence Impacting Manufacturing in 2022?
More Resilient Supply Chains and Logistics
There are several ways that AI improves the manufacturing industry through logistics. First, it can observe production floor activity, helping companies to keep track of what is being built and ensuring products are not being wasted or overproduced.
Second, AI can estimate future customer demand by helping companies predict how much product they will need and when. In fact, businesses that utilized AI for demand planning throughout the pandemic had 33% fewer forecasting errors. This can help to prevent shortages and ensure that products are always available when customers need them. Last but not least, companies can use AI to avoid wasting money on unnecessary stock or products that are not selling well.
Intelligent Robot Labor
AI robots are increasingly taking over manual labor. This work includes tasks such as welding, painting, die casting, and assembling parts. AI robots are able to do this faster and more accurately than humans, and they are able to work continuously without getting tired. Large carmakers such as BMW, Ford, and General Motors have been using AI labor for several years now, and the benefits have been impressive.
AI robots have not only increased their overall production performance, but in some cases, they have even replaced human workers altogether. But although AI is predicted to eliminate 85 million jobs by 2025, it’s also expected to create 97 million new ones in the same time frame. In other words, AI is actually stimulating the manufacturing job market rather than squashing it!
Upgraded Internet Technology
Artificial intelligence for IT operations, or AIOps, is a relatively new technology that combines big data and machine learning to automate various IT processes. AIOps is most useful for automating big data management, but it can also be used for event correlation and analysis, performance analysis, and anomalous data detection.
In the manufacturing industry, AIOps can be used to improve process efficiency and identify issues early on so that they can be corrected before they cause any serious damage. It can also be used to monitor production lines and identify potential problems before they occur.
Cyberattacks are on the rise, and manufacturers are among the most commonly targeted groups. This is partly because of the number of IoT devices used in factories, which create many potential targets. The trend will only continue as cyber threats become more sophisticated, which presents a serious risk for manufacturers; cyberattacks can disrupt production or even damage equipment, which can cost a company millions.
In order to mitigate these risks, it’s crucial to have a robust cybersecurity system in place. This includes using AI-driven systems that can learn about new threats and spot them across cloud services and IoT devices. With this type of system, manufacturers can stop attacks within seconds before they have a chance to do any damage.
Better Product Development
In order to keep up with the ever-changing demands of consumers, manufacturers have to be able to quickly and efficiently produce new products. However, this can be challenging, as it often involves some amount of trial and error. However, AI can help reduce the costs involved in the product development stage by providing manufacturers with data-driven insights about how products can be improved. For example, AI can predict how changes to a product’s design will affect its performance.
This can prevent product problems from happening in the first place, which saves time and money. Additionally, AI can help speed up innovation by suggesting new product designs. By using AI to analyze data from past products, manufacturers can better understand what works and what doesn’t, helping them come up with ideas for new products that are likely to be successful.
Automated Production Processes
Industry leaders are increasingly turning to AI to improve performance and efficiency in their production processes as there are a number of different AI-powered tools that can help in this regard. For example, process mining tools can automatically analyze and track factory workflows, allowing for standardization and optimization. Similarly, robotic process automation (RPA) can automate repeatable tasks and reduce cycle times.
Less Machine Downtime
AI Predictive maintenance is becoming an increasingly important part of modern manufacturing. With the right tools in place, it can help companies prevent equipment breakages and keep their operations running smoothly.
By capturing and processing data from sensors on the shop floor, irregularities or inefficiencies can be spotted before they cause problems. Likewise, it can pinpoint specific malfunctions that can be fixed by replacing the faulty component, which is considerably less expensive than replacing the whole machine when it breaks.
Better Warehouse Management
AI can automate a number of warehousing tasks, such as data collection, demand forecasting, and inventory management. For example, by using sensors and RFID tags, data can be automatically collected about the location of items in the warehouse. This data can then be used to forecast future demand and optimize stock levels.
In addition, AI robots can be used to lift, move, and sort items in the warehouse. This decreases the need for manual labor and allows manufacturers to keep up with customer demand while increasing profit margins.
Driverless Delivery Trucks
The rapidly growing autonomous vehicle industry is expected to make up 15% of global car sales within the next decade. These vehicles are equipped with sensors that track information about traffic, road conditions, and accidents, allowing them to optimize delivery routes. Such technology helps to reduce delivery times and improve safety. Autonomous vehicles also operate 24/7, improving transit times.
For instance, if a company needs to transport goods from its factory to a customer’s doorstep 20 hours away, an autonomous vehicle can make the trip without stopping. This would not be possible with a human driver, as they are not legally allowed to drive for more than 14 consecutive hours.
AI sensors can also be used to track inventories and create purchases automatically. For example, a sensor can detect when a product is running low and generate a purchase requisition for more stock. This can help reduce inventory management costs and ensure that products are always available. AI-based order management can also help reduce order entry costs and ensure profit maximization; systems can be implemented to compare prices from different suppliers and select the vendor that offers the best price.
Improved Quality Control
Traditionally, quality control has been a manual process involving inspectors who visually inspect products for defects. However, this process is time-consuming and expensive. But today’s AI-powered cameras and machine learning algorithms can quickly and accurately detect defects that may not even be visible to the human eye.
For example, a fiberglass company called 3B-Fibreglass was having a problem manufacturing one of their products made of silica sand, limestone, and kaolin clay, which kept breaking at a certain point in the process. The AI found common patterns in the breaks and was then able to predict when a break would occur, which allowed the manufacturer to find and add address the root cause.
Safer Work Environments
AI-powered systems can also help with worker safety by monitoring emissions and alerting workers to any potential dangers. For instance, if a machine emits too much heat, the system can alert workers so they can take precautions. Or, if a chemical is leaking, the system can provide information about the toxicity level and recommend the appropriate safety measures.
AI can also help keep manufacturing facilities safe from the pandemic by performing thermal screenings and keeping tabs on employee interactions for contact tracing purposes. The AI system can then alert workers if they have been in close contact with someone who has tested positive for the virus, which can help prevent outbreaks that could threaten to shut down the plant.
We’ve seen that AI can be used for predictive maintenance, warehouse management, autonomous driving, automated order entry, and much more. Adopting artificial intelligence in the manufacturing industry isn’t only advantageous, it is necessary in order to keep up with the competition. Do you need help upgrading your manufacturing facility? Contact us at SAAB RDS today for a free consultation!