GM shares how COVID-related semiconductor shortage revealed AI can help with supply chain gaps

General Motors (GM) has provided a behind-the-scenes glimpse at how it uses AI within its supply chain logistics.

Jeff Morrison, GM global purchasing and supply chain senior vice president, writes that “without the right data and insights, even the best supply chain teams can feel like they’re solving an ever-shifting jigsaw puzzle in the dark.”

And AI is the “expert companion” necessary to find issues humans might miss, according to Morrison.

“[W]hen you’re trying to solve a puzzle before your stop, every second matters,” he wrote. “That’s what several AI-powered tools offer supply chain teams: rapid data analysis, pattern recognition, and smart recommendations.

“It’s easy to chase the hype with AI. But at GM, we view AI as a practical, yet transformative force. It is a competitive advantage to unlock enterprise-wide innovation and efficiencies up and down the value chain, from manufacturing and supply chain to the customer experience.”

Morrison pointed to the semiconductor shortage in the early 2020s as an example of “the undeniable need for deeper insights into our vulnerabilities and a stronger capability to anticipate, mitigate, and respond to disruptions effectively.”

From that, GM created a digital supply chain toolset to anticipate and aid in supplier GM facility disruptions, including:

• • “Risk Intelligence: Using the power of AI and machine learning, this tool classifies, summarizes, and tags thousands of daily public posts to anticipate risk in GM’s supply chain, such as natural disasters or other disruptions.
  • “SupplyHealth: With the cooperation of our supply partners, this tool monitors thousands of sites to detect and flag high-risk situations so the team can take action before an issue escalates.
  • “SupplyMap: Collects data from thousands of suppliers around the world, ranging from our direct suppliers to the many levels that feed into them. It uses this data to compile a detailed, map-based view of the network, increasing visibility and understanding of where risks may occur.
  • “SupplyAlert: A centralized communications platform activated once a risk has been identified. This tool combs through internal data and flags key risks to team members who can take pre-emptive action.”

Morrison added, “Our suppliers play a critical role in the development and effectiveness of our AI supply chain tools. We have deployed comprehensive training and tools to support them as they map the entirety of their value chains. This two-way communication allows us to act quickly in support of our suppliers when issues arise. Because in the end, our supplier partners benefit from these tools as much as we do.”

Earlier this year, GM announced an expanded collaboration with NVIDIA to develop next-generation vehicles, factories, and robotics using AI simulation and accelerated computing.

In June, Audi shared that it has increased its use of AI in vehicle production lines to improve efficiency and quality.

“The aim is to fully exploit the potential of AI and data — both in company processes and in the customer experience with services and products,” Audi said in a press release at the time. “AI is currently making the biggest impact in the areas of production and logistics.”

Audi’s primary focus is on AI-supported quality monitoring and generative AI.

McKinsey and Co. recently noted that when it comes to in-vehicle features, for automakers and their suppliers, “the rush to seize the opportunities presented by advanced AI technologies raises important questions about the selection of appropriate hardware, software, and use-case deployment types.”

“Companies will need to answer these questions in different ways across the vehicle life cycle, from product design and engineering to sales and aftermarket support,” McKinsey wrote.

Another example is Volvo’s use of AI-generated life-like virtual worlds to enhance the development of its safety software. With the data that’s collected, Volvo says it can “probe, reconstruct, and explore” to better understand how incidents can be avoided.

Volvo says the technique exposes its safety software to all types of traffic situations at a speed and scale not possible before.

Images

Featured image: SupplyMap is part of a suite of AI-enhanced tools General Motors says it uses to monitor and strengthen its supply chain. (Provided by GM)