Quantum computing just took on another big challenge, one that could be as tough as steel

Honeywell and CQC have been helping Nippon Steel find quantum algorithms that could boost efficiencies in the steel supply chain.
Written by Daphne Leprince-Ringuet, Contributor

Nippon Steel has concluded that, despite the current hardware limitations of quantum computers, the technology holds a lot of promise when it comes to optimizing complex problems.   

Image: Honeywell Quantum Solutions

From railways and ships all the way to knives and forks: the number of products that are made of steel is too high to list – and to ensure a steady supply of the sought-after material, Japanese steel manufacturer Nippon Steel is now looking at how quantum computing might help. 

The company, which produced a hefty 50 million tons of steel in 2019 (that is, 40% of the total production in Japan) has partnered with Cambridge Quantum Computing (CQC) and Honeywell to find out whether quantum computers have the potential to boost efficiencies in the supply chain.  

And after over a year of testing and trying new algorithms, the company has concluded that, despite the current hardware limitations of quantum computers, the technology holds a lot of promise when it comes to optimizing complex problems

"The results Nippon Steel and Cambridge Quantum Computing were able to achieve indicate that quantum computing will be a powerful tool for companies seeking a competitive advantage," said Tony Uttley, the president of Honeywell Quantum Solutions. 

SEE: Building the bionic brain (free PDF) (TechRepublic)

The steel manufacturing process is a highly elaborate affair, involving many different steps and requiring various raw materials before the final product can be built. 

Plants start by pre-treating and refining iron ore, coal and other minerals to process them into slabs of steel, which are then converted into products like rails, bars, pipes, tubes and wheels. 

In the case of Nippon Steel, where millions of tons of material are at stake, finding the best equation to make sure that the right products are in the right place and at the right time is key to delivering orders as efficiently as possible.  

Toss in strict deadlines, and it is easy to see why industry leaders are looking for the most advanced tools possible to model and optimize the whole system, and at the same time reduce operating costs. 

For this reason, the use of pen and paper has long been replaced by sophisticated software services, and Nippon Steel has been a long-time investor in advanced computing – but even today's most powerful supercomputers can struggle to come up with optimal solutions to such complex problems.  

Classical computers can only offer simplifications and approximations. The Japanese company, therefore, decided to try its hand at quantum technologies, and announced a partnership with quantum software firm CQC last year

"Scheduling at our steel plants is one of the biggest logistical challenges we face, and we are always looking for ways to streamline and improve operations in this area," said Koji Hirano, chief researcher at Nippon Steel.    

Quantum computers rely on qubits – tiny particles that can take on a special, dual quantum state that enables them to carry out multiple calculations at once. This means, in principle, that the most complex problems that cannot be solved by classical computers in any realistic timeframe could one day be run on quantum computers in a matter of minutes.  

The technology is still in its infancy: quantum computers can currently only support very few qubits and are not capable of carrying out computations that are useful at a business's scale. Scientists, rather, are interested in demonstrating the theoretical value of the technology, to be prepared to tap into the potential of quantum computers once their development matures. 

In practice, for Nippon Steel, this meant using CQC's services and expertise to discover which quantum algorithms could most effectively model and optimize the company's supply chain. 

To do so, the two companies' research teams focused on formulating a small-scale problem, which, although it does not bring significant value to Nippon Steel, can be resolved using today's nascent quantum hardware. 

The researchers developed a quantum algorithm for this "representative" problem and ran it on Honeywell's System Model H1 – the latest iteration of the company's trapped-ion quantum computing hardware, which has 10 available qubits and a record-breaking quantum volume of 512. After only a few steps, say the scientists, the System Model H1 was able to find an optimal solution. 

"The results are encouraging for scaling up this problem to larger instances," said Mehdi Bozzo Rey, the head of business development at CQC. "This experiment showcases the capabilities of the System Model H1 paired with modern quantum algorithms and how promising this emerging technology really is." 

What's more: an optimization algorithm such as the one developed by CQC and Nippon Steel can be applied to many other scenarios in manufacturing, transport and distribution. 

Earlier this year, for example, IBM and energy giant ExxonMobil revealed that they had been working together to build quantum algorithms that could one day optimize the routing of tens of thousands of merchant ships crossing the oceans to deliver everyday goods – a $14 trillion industry that could hugely benefit from operational efficiencies. 

The results from Nippon Steel are the first to emerge following the announcement of a partnership between Honeywell and CQC earlier this month. CQC's quantum software capabilities are planned to merge with Honeywell's quantum hardware services in a deal that is expected to make waves in the industry.  

By joining forces, the two companies are effectively set to become leaders in the quantum ecosystem. The early results from the trials with Nippon Steel, therefore, are likely to be only the start of many new projects to come, as the two firms apply their complementary expertise to global issues affecting various different industries. 

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