4 Ways Machine Learning (ML) and Artificial Intelligence (AI) Are Transforming Manufacturing

The role of machine learning (ML) and artificial intelligence (AI) in our professional world continues to grow due to the benefits that they offer. These technologies have the ability to digitize operations and streamline work processes in order to reduce costs and boost a company’s ROI. This is especially true in the manufacturing world, where ML and AI are playing a role as the demand for customized products continues to increase.

A new AI report from Infosys discovered that in the manufacturing industry, machine learning is higher by 79%, while the use of cognitive AI-led processes is up by 61%. Additionally, 66% of manufacturing companies want to automate tasks to increase productivity and 61% want to use it to minimize errors. Intelligent automation company WorkFusion has a robotic process automation platform called RPA Express that can amass data, learn from that data and develop smart solutions for companies in the manufacturing industry.

Here are four ways ML and AI are changing manufacturing:

1) Predictive Maintenance Technology

Most manufacturing plants currently rely on having a fixed schedule to perform preventive maintenance, even if the operating conditions at a plant are working or not. Having preventive maintenance on a schedule results in equipment downtime, a waste of labor and production losses. Cognitive AI technology, smart sensors and a network of machines allows plant engineers to monitor the devices on the floor. This allows floor managers to come up with predictive analytics that ensure that a company performs maintenance on its equipment only when necessary.

2) Improved Quality Control

Machine learning is playing a role in quality assurance as one of the latest research initiatives in the manufacturing sector. Previously, manufacturing companies had to rely on a network of computers and sensors to eliminate low-quality products from their assembly line. This is where AI and ML come in as their systems offer a seamless quality control system over the entire manufacturing process. Instead of relying on manual inspections, computers and sensors have the capability of finding defects with high efficiency and accuracy. This will allow companies to improve low-quality products instead of eliminating them.

3) Enhanced Supply Chain

AI and ML are also capable of optimizing a company’s global supply chain management. With AI, companies can analyze data and organize supply chain processes, better adapting to changing market conditions. These can collect and analyze data from social media, news feeds, weather forecasts and historical data to better the supply chain. With AI and ML, companies can create self-sustaining ecosystems that pave the way for the seamless exchange of information. This can improve everything from warehouse operations, transportation, production, packaging and customer feedback.

4) Considering What the Consumer Wants

After all, a company is only successful when it’s appeasing the needs of the consumer. AI and ML have the ability to build smart manufacturing processes that can adapt quickly as the consumer demand shifts at any given point. Doing so is not easy as it requires an interconnected network that links consumers directly with manufacturers. AI plays a role here by connecting IoT with IIoT, which means that companies can amass data from smart homes in order to better understand the latest consumer trends. This data can then be used to create items that consumers want.