Inside Quantum Technology’s “Inside Scoop:” Quantum and the Manufacturing Industry
Manufacturing is part of our everyday lives, from our electronic devices to cars to homes. It is the common denominator for many industries. And with its moving parts, like product development, production lines, and prototype testing, quantum computing offers many benefits for this industry. “Quantum computing can impact the manufacturing industry at many different levels, from robot routing optimizations on the factory floor, to materials development at the atomic level,” explained Tim Costa, Director of HPC and Quantum Computing Products at NVIDIA. While quantum computing is still being developed, many companies are already looking into what use cases this future technology could be applied to.
Starting at the Factory Floor
The factory floor offers unique opportunities for quantum computing. One example is using quantum annealing to optimize production lines for faster and more efficient production. “On the factory floor, hundreds of robots per plant are deployed to assemble products and route new materials,” Costa explained. “Optimally routing and deploying these robots to improve the overall efficiency of a plant is a challenging computational problem, but can yield large increases in productivity. This type of optimization problem and others (like supply chain and resource routing optimization, placement and distribution planning, product configurations) are believed to be within a class of problems well suited to quantum computers, as the technology matures.” Quantum computers can also help to optimize safety on the factory floor, simulating different scenarios to find areas of improvement. This can help make conditions safer and more transparent for employees.
Manufacturing Better Products
Quantum computing is also predicted to improve product design and testing. This technology can look at individual components in a larger product to find weaknesses or suggest methods for improvement, which can save on costs. Quantum computing, along with AI, can also simulate product testing, telling designers and engineers more about their prototypes and making the process more cost-effective. This can be especially helpful for improving the safety of products, such as bridges or cars, where simulations can show areas that may lead to unsafe conditions after years of use. As all companies want to avoid the negative effects and publicity associated with unsafe products, quantum computing can act as an extra safety check in the process of product design and creation.
When will Quantum Computing be Implemented by the Manufacturing Industry?
Because quantum computing is still in its early stages of development, most experts predict it will be years, if not decades, before the technology will be affordable and accessible to the manufacturing industry. As Costa explained: “Currently, quantum computing is a developing technology where the best classical computing solutions still outperform quantum solutions. While we expect in the future that quantum computers will outperform classical supercomputers for certain tasks, quantum computers won’t replace the classical supercomputing infrastructure. Instead, one can imagine quantum computers being integrated into the classical computing infrastructure and workloads as quantum accelerators, much in the way GPUs have been integrated into supercomputers as accelerators.”
That doesn’t mean companies can’t already begin looking into quantum computing as part of their business strategy. “Valuable insights about the technology can still be gained by manufacturing companies today by exploring what use-cases and workflows can benefit from quantum computing once it matures,” Costa added. “In addition, understanding and developing new quantum algorithms is a large and active area of research today, which can yield valuable increases in efficiency in a manufacturing workflow in the future. Simulation tools, like NVIDIA cuQuantum, provide a powerful and efficient way for the end-user to explore and develop these algorithms, and understand what quantum algorithms will provide value for the end-user’s workflow when quantum technologies mature.”
Kenna Hughes-Castleberry is a staff writer at Inside Quantum Technology and the Science Communicator at JILA (a partnership between the University of Colorado Boulder and NIST). Her writing beats include deep tech, the metaverse, and quantum technology.