4 ways artificial intelligence will change design and manufacturing

Artificial intelligence and machine learning will soon replace trial and error as businesses strive to improve product performance. While technology has taken over many aspects of our lives, our product design and manufacturing processes are largely stuck in the industrial age. Businesses strive to efficiently create better-performing products and keep costs down. After extensive experimentation, they came up with the best design. They then feed the instructions into a manufacturing machine, which makes thousands of identical products or parts, with little room for customization.

All this is about to change. We are on the cusp of a revolution in designing and manufacturing products. Specifically, AI and machine learning will transform product design and manufacturing in the following four areas:

1. Optimize multivariate
Product designers often have a good idea of ​​what to expect when using different materials. But things can quickly get complicated when designers have to balance multiple desired outcomes. For example, when designing a car, designers should optimize not only performance, but also cost, durability, safety, and fuel efficiency. Using artificial intelligence and machine learning tools, design teams can quickly iterate through thousands or even millions of different potential designs, then spend valuable time on the most promising designs algorithmically determined.

In this context, the term “design” usually refers to performance design, not aesthetic design. While humans are still better than computers at creating beautiful products with consumer appeal, artificial intelligence and machine learning can figure out how small changes in products will affect several different aspects of performance. This will be an invaluable improvement for design teams, as it will allow engineers to spend their time on the more creative aspects of their work, rather than countless hours of laborious and inefficient trial-and-error experimentation. Also, it will lead to better products.

2. Unprecedented customization
Product customization requires a lot of manual labor. Even fairly standard products, like sneakers, often require assembly lines with dozens of workers. But AI and machine learning will soon open the door to more automated product customization.

For example, in keeping with the sneaker example, emerging technologies will allow each pair of sneakers to be fully customized, improving the individual athlete performance of the sneaker. Shoe buyers will soon use new input devices, such as sensors that create foot pressure maps and capture information that will lead to unique custom designs. Then, based on the high-level specification, generative design tools automatically synthesize the design and convert it into machine-readable assembly instructions.

Recent advances in artificial intelligence and computing have ushered in a whole new world where every product is unique and has unprecedented complexity.

3. Automated test
For many products, it is difficult or even impossible to predict their performance without first experimenting. For example, there are no numerical models that can help product designers determine how effective a given drug is in relieving a patient’s symptoms, or how efficient a solar cell is in generating electricity.

While AI and machine learning have not eliminated the need for experimentation, they can help researchers plan and even conduct experiments effectively. In the near future, we will see fully automated workflows, where designers set parameters for desired outcomes, and robots then conduct experiments and evaluate the results.

4. Intelligent Manufacturing
Most manufacturing systems these days are utterly stupid. Manufacturing equipment may be able to produce standardized products at a consistent rate, but it cannot assess and respond to changing conditions. However, adding sensors to manufacturing facilities, as well as layering artificial intelligence and machine learning algorithms onto equipment, will enable companies to use smarter manufacturing processes that are more dynamic, responsive and resilient.

For example, a manufacturing plant’s temperature rose sharply overnight, or a machine was thrown into a batch of material that was slightly different from the standard material. Without sensors and intelligent systems, machines will continue to function normally regardless of changes in the environment or materials. This can lead to delays, machine degradation and product damage.

In contrast, smart manufacturing systems are able to detect failures and automatically adapt to changing conditions. This, in turn, improves quality control, reduces costs, and increases reliability.

We may not even be able to imagine how artificial intelligence and machine learning will change product design and manufacturing. After all, many of the ways we use our smartphones were completely unforeseeable a decade ago. But by learning how to use these technologies in their operations, business and IT leaders can put themselves at the forefront of their industry and ensure they are prepared for whatever the coming years may bring.