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The largest technology companies in the world are investing billions of dollars in the race to build the first practical quantum computer to be used outside of laboratory settings. The focus is on finding the best materials to build the computers from, managing to control more and more qubits in one machine, and developing better ways of giving the qubit state.
When quantum supremacy – the period in the near future when a quantum computer will be able to perform any task faster and more accurately than a classical computer could – is reached, many industries will benefit from the almost infinite number of applications that better processing power promises to bring. Not the least of these is industrial automation.
Industrial automation has been a key driver of our modern way of life since General Electric began to automate parts of their factory processes in the middle of the twentieth century. Initially, automation – machines carrying out tasks instead of humans, like the home thermostat – was achieved with mechanical systems comprised of relays, cam timers, drum sequencers, and dedicated closed-loop controllers. These had to be controlled by a trained operative.
The birth of information technology meant that programmable logic controllers (PLCs) could be introduced to manufacturing processes containing thousands of inputs and outputs (I/Os), and these could be controlled by non-specialist operatives. Other developments like distributed control systems (DCSs) and Supervisory Control and Acquisition Data (SCADA) brought more and more computing power into industrial automation, with computers taking over more of the monitoring and programming tasks that humans would otherwise need to complete.
The Limits of Classical Computing in Industrial Automation
Developments in information technology applied to industrial automation have led to the modern factory – and even networks of multiple factories and the freight, rail and air traffic that links them – requiring less and less human input. However, with limited processing power, computer-controlled technologies in complex factories or large networks must decide between a reduction in accuracy and level of detail or a reduction in complexity or size.
Reducing accuracy would mean more human involvement is required, or numerous, relatively inefficient quality control processes would need to be put in place. Reducing the level of detail would result in less accuracy, and would lead to more errors in the factory processes.
Larger factories or networks of factories are needed to bring more economies of scale to industrial processes and to supply the demands of ever-growing populations with more and more complex processes like semiconductor manufacture, air traffic control with thousands of unmanned aircraft (drones) in the sky, or road management with millions of self-driving cars are becoming needed in modern society.
Quantum Computing and the Future of Industrial Automation
Quantum computing would remove the limitations of classical computing and enable industrial automation to reach new levels of size and complexity. It would be applicable to industry in many, almost infinite ways.
Quantum computers will be able to manage extremely large or complex factories which are required to produce, for example, semiconductor materials or new drugs at precise levels of detail and accuracy. The quantum computer could take in inputs from sensors at every stage of the manufacturing process and monitor quality and precision. It could also manage the factory’s output according to demand and logistics considerations, greatly reducing wastage.
Quantum computers would also be able to manage large networks of factories connected by the Internet of Things (IoT) with a level of detail not capable of even classical supercomputers. This would mean that logistics of delivery of materials, production, and distribution of products could be optimized for efficiency, saving on costs as well as helping to reduce the environmental impact of production.
Quantum computers will also be able to drive progress in machine learning and artificial intelligence (AI), again due to their superior processing power. These fields already have numerous applications in industrial automation, with machines being able to learn from their experience and optimize their own processes for speed, accuracy, and efficiency.
With quantum computing-powered AI, the future of industrial automation could see factories taking over their own processes (with human supervision) and even designing new products, new ways of producing them, and new machines to do the labor.