3 ways AI can be used in manufacturing

It is no secret that the application of Artificial Intelligence in manufacturing helps to solve many problems: it helps to automate work processes, such as equipment monitoring and diagnostics. AI also helps to increase productivity and reduce costs. There is no denying that AI is driving various fields, and the industrial field is no exception.

Kevin Shahnazar, founder and CEO of FinlyWealth, a credit card recommendation platform that helps users find personalized financial solutions through AI, notes the following:

“I look at AI’s transformation in manufacturing with very different eyes.

AI is the undisputed game-changer of modern manufacturing and promises to revamp productivity and efficiency. According to a study by McKinsey, AI-empowered factories can drive a productivity increase of as much as 20% and a reduction of unplanned downtime by as much as 50%. The effect is anything but conceptual; it is being carved out in reality and right into the industry.

The most potent application of AI in manufacturing is predictive maintenance. Imagine a factory where machines can see their failures coming. In the process of doing so, AI algorithms analyze real-time data streaming in from sensors and predict when a machine is likely to break down. Thus, they provide an opportunity for maintenance before it does, averting very expensive disruptions. This is not science fiction; it is happening now, saving millions for manufacturers.

Take Siemens, for example. It has introduced AI-driven predictive maintenance into the manufacturing process of its gas turbines, which has resulted in a 10% maintenance savings and a spectacular 20% rise in turbine availability. Figures like these show that AI has real worth.

While predictive maintenance is one area in which AI can make the largest difference, the technology is also changing the face of quality control. Traditional quality controls, manual in nature and thus prone to error, are giving way to AI-powered vision systems that can detect defects with almost superhuman acuity. These systems ensure a better-quality product while significantly reducing waste and its associated costs.

AI in supply chain management ensures optimal inventory levels, forecasts demand, and smoothes out logistics. This means lower inventory carrying costs, better on-time delivery, and higher customer satisfaction. AI’s impact on manufacturing is very wide-ranging, affecting each corner of the production process.

The manufacturing industry is on the cusp of revolution, and AI is leading in this new transformation. Potential productivity, efficiency, and added profitability are enormous in any such view; the competitive advantage for any company willing to board this train is huge. I’m very excited to see how AI will continue to reshape manufacturing.”

Other expert, Max Mikhaylenko, President & Co-founder at Snap Supplements, adds 2 ways to use AI in manufacturing:

“Forecasting Upkeep.

One of the most popular and revolutionary applications of artificial intelligence right now is predictive maintenance. It’s hardly surprising, given the immense potential for AI-powered predictive maintenance to enhance the production process. Machine learning systems can predict when machinery may break down by sifting through data gathered from telemetry, sensors, and other sources. This AI technology makes it possible for manufacturers to schedule maintenance proactively, which lowers maintenance costs and downtime.

Electronic Duplicates.

A digital twin is an electronic representation of a physical object that can monitor its status in real time and act similarly in a computer simulation. Artificial intelligence (AI) in manufacturing can predict equipment failures by analyzing patterns, finding anomalies, and integrating digital twin data with data from equipment sensors. Predictive insights from this data allow maintenance teams to plan actions in advance of equipment failure.”