AI Is Here Podcast Series: How AI is optimizing the supply chain for complex industrial systems and increasing sustainability
This is the seventh in a series of blogs on the “AI is here.” podcasts. Each blog in the series will highlight the insights from a specific industry leader as they describe how their organization is deriving significant value from AI today.
In this edition of the “AI is here.” podcast, Dan Faggella, Founder and CEO, of market research and publishing company Emerj, speaks with Caroline Gorski, CEO – R2 Factory at Rolls Royce. Gorski discusses how Rolls Royce is using AI to strengthen the supply chain and to optimize for cost and quality, while reducing risk and improving sustainability.
The fragility of global supply chains, particularly for complex processes, has had a significant impact on manufacturers. That fragility has increased over the last 2-3 years, but now AI is being used to harden the supply chain and to move from simply optimizing for cost reductions and lowering risk to optimizing for sustainability and reducing carbon emissions.
As an example of this fragility, Gorski cites a Harvard Business Review survey, which looked at 100 OEMs in the high tech, automotive, and consumer goods space with supply chain partners that operate across the US, China, and Taiwan. The goal of the survey was to identify how many of them are at risk of climate driven disruption due to forest fires, flooding, hurricanes, etc., and how many of those have continuity plans in place to mitigate those disruptions. The answer was that only 11% have resiliency plans in place, meaning that 89% are at risk from natural events that are occurring at an increasing rate.
Further compounding the problem is that the costs of shipping have gone up an average of 25% in the past year. This has largely been due to a combination of fuel price increases, local lockdowns, and spikes in demand.
Finally, in 2020 the demand for goods in the US grew 17% while demand for services dropped by 2%. This marks the first time since 1929 that the demand for goods went up while demand for services shrank. The pressure on supply chains to continue delivering materials is only going to increase.
AI and large language models can help manufacturers better manage their supply chains to reduce costs, manage risk, and improve sustainability.
Rolls Royce is an example of an organization that has been successfully using AI to manage supply chain challenges. As a manufacturer of large, complex systems, Rolls Royce has significant supply chain challenges. According to Gorski, building airplane engines for their civil aerospace division requires sourcing:
- Almost £3.3 B of materials per year (£13 Million per day)
- Utilizing more than 5,000 vendors
- Sourcing over 50,000 parts
One of their biggest challenges was using data that is not easily machine readable. Ingesting engineering drawings, mathematical notations, and other unstructured data was an extremely difficult, but necessary step for them to be able to unify their analysis of sourceable materials. Once the data was in the system they were able to analyze it and use the results to augment human decision makers. Those humans then took updated data, such as negotiated prices, and put that new information back into the system for further analysis.
Ultimately this allowed Rolls Royce to harden their supply chain and to see significant cost savings. According to Gorski, their use of AI enabled them to save £180 million on a single family of sourced products. Overall they reduced their spending by 15%.
Beyond just cost savings, they were able to significantly enhance their sustainability practices. Their use of AI resulted in the reduction of the carbon footprint of sourced materials by 40%, which is equivalent to saving 100,000 trees.
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