In 2023, Artificial Intelligence (AI) is becoming increasingly essential to the day-to-day operations of manufacturers all over the world. Autonomous robots and machine learning-powered predictive analytics means companies are able to streamline processes, increase productivity and reduce the damage done to the environment in many new ways.
Importantly, rather than replacing human workers, a priority for many organizations is doing this in a way that augments human abilities and enables us to work more safely and efficiently.
Today, the concept of AI technology in factories goes far beyond the robot-filled workplaces that have been a feature of industries since the 1960s to encompass smart, connected manufacturing plants where humans and machines work together, and data and analytics enable better predictions and decision-making at every stage of the process. So let’s take a look at some of the most interesting use cases for AI in manufacturing in 2023:
Cobots
Robots have been used to automate manual tasks in factories and manufacturing plants for decades, but cobots are a relatively new development. What makes them different is that they are designed to work alongside humans in a safe way while augmenting our abilities with their own.
One big advantage of cobots over traditional industrial robots is that they are cheaper to operate as they don’t need their own dedicated space in which to function. This means they can safely work on a regular plant floor without the need for protective cages or segregation from humans. They can pick components, carry out manufacturing operations like screwing, sanding, and polishing, and operate conventional manufacturing machinery like injection molding and stamping presses. They can also carry out quality control inspections using computer vision-enabled cameras.
Cobots are widely used by automotive manufacturers, including BMW and Ford, where they perform tasks including gluing and welding, greasing camshafts, injecting oil into engines, and performing quality control inspections.
And consumer goods manufacturers, including giant Procter & Gamble, use cobots to streamline their manufacturing processes, engaging in tasks such as assembling and packaging products while maintaining the required high standards of hygiene.
AI in Additive Manufacturing
Often known as 3D printing, the term additive manufacturing is used because it includes any manufacturing process where products and objects are built up, layer by layer. This differentiates it from more traditional, subtractive manufacturing processes where a product or component is made by cutting away at a block of material.
AI plays an important role in additive manufacturing by optimizing the way materials are dispensed and applied, as well as optimizing the design of complex products (see Generative Design below). It can also be used to spot and correct errors made by 3D printing technology in real-time.
Additive manufacturing equipment manufacturer Markforged has developed a tool called Blacksmith that uses AI to compare product designs with actual finished products and automate fine-tuning of the manufacturing process in order to bring them more closely into line.
Technology like this will be of benefit to manufacturers such as footwear giants Adidas and Reebok, which are now using 3D printing technology to create complex lattice structures for more comfortable and performance-enhancing running shoes.
Generative Design
Generative design is a bit like the generative AI we’ve seen in technologies like ChatGPT or Dall-E, except instead of telling it to create text or images, we tell it to design products.
Designers simply enter parameters such as what materials should be used, the size and weight of the desired product, what manufacturing methods will be used, and how much it should cost, and the generative design algorithms spit out blueprints and instructions.
Design engineers in the manufacturing industry can use this method to create a wide selection of design options for new products they want to create and then pick and choose the best ones to put into production. In this way, it accelerates product development processes while enabling innovation in design.
Generative design is particularly powerful when it comes to conceptualizing what can be done with new additive manufacturing processes, such as 3D printing, due to the complexity of the shapes and structures that can be created.
It has been used to create new types of components that are cheaper, lighter, and sturdier than existing components, improving the overall qualities of many products from cars and aircraft to prefabricated houses and structures.
Predictive Maintenance
Manufacturers use AI to analyze data from sensors and machinery on the factory floor in order to understand how and when failures and breakdowns are likely to occur. This means that they can ensure that resources and spare parts necessary for repair will be on hand to ensure a quick fix. It also means they can more accurately predict the amount of downtime that can be expected in a particular process or operation and account for this in their scheduling and logistical planning. Data from vibrations, thermal imaging, operating efficiency, and analysis of oils and liquids in machinery can all be processed via machine learning algorithms for vital insights into the health of manufacturing machinery.
Some examples of this in practice include Pepsi and Colgate, which both use technology designed by AI startup Augury to detect problems with manufacturing machinery before they cause breakdowns.
The Lights-Out Factory
A lights-out factory is a smart factory that’s capable of operating entirely autonomously without any humans on site. Although mostly theoretical, there are some examples in existence already – such as the factory operated by Japanese robotics manufacturer FANUC without humans since 2001, which is capable of operating without human supervision for periods of up to 30 days.
Electronics manufacturer Philips also operates a factory in the Netherlands that makes electric razors, where a total of nine human members of staff are required on site at any time. This is a trend that we can expect to see other companies working towards adopting as time goes by as technology becomes increasingly efficient and affordable. Using a robots-only workforce means a factory can potentially operate 24/7 with no need for human intervention, potentially leading to big benefits when it comes to output and efficiency. Of course, questions will need to be addressed about what the impact removing humans from the manufacturing workforce will have on wider society.
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