The Linde pub crawl
Safety isn’t the only thing on Linde’s AI agenda however. Elsewhere in the UK, Linde is trialling the use of Artificial Intelligence to enhance another aspect of deliveries: meeting customer demand. Every two weeks, Linde delivery trucks head to bars, pubs and restaurants across the country to ensure they have the gas cylinders they need to create the right fizz in drinks. And here is where another business challenge bubbles up.
BOC – a member of the Linde Group in the UK – guarantees that customers will have access to whatever they might need when the trucks pull up. This means that more cylinders than needed are often ferried around the country. 20% more in fact. And should customer requirements not be met, a second delivery is made. It was with these two things in mind that the Digital Base Camp began to investigate how Artificial Intelligence could help order the next round.
Again, data was the name of the game. The software was “trained” using historical ordering information from 25,000 customers. Additional external factors, such as weather, sporting events and bank holidays, were then added as features to the algorithm to identify the extent to which they influenced the orders. “The great thing about the algorithm is that it can deliver tailored insights for different customers,” explains project manager Stefan Lenz.
“After a three-month development phase, the program was implemented by BOC’s digitalisation team in the UK,” he says. Since 2017, the computer has been calculating the daily individual stocking requirement for every truck in the 255-strong fleet. The result? “BOC avoided the unnecessary transport of almost 90,000 gas cylinders over an entire year,” reckons Lenz. Not to mention the need for any follow-up journeys. This has led to reduced fuel consumption and a reduced environmental impact, as well as happy customers!
The next step for both new technologies is to roll them out further. There are already plans to start testing the AI Transport Safety Guardian software in other countries in Europe and Asia. In locations with similar road conditions and equivalent data availability, the algorithm can be applied with very few adjustments. When it comes to the customer-demand technology, Linde is considering introducing it to Canada and Australia, as well as to other sectors, such as medical gas delivery.
For both forms of software, the technology will be developed continually with further testing and further learning. Whether road hazards or optimising stock deliveries, the benefits are clear. None more so than potentially saving lives. “Even if we prevent one terrible accident, it’s worth it,” Luo says.