Caterpillar, the world’s largest construction OEM has said that it is “actively pursuing” Artificial Intelligence (AI) to improve business outcomes for itself and its customers.
The OEM said that, like most manufacturers, its advanced computer programs and cloud computing allows its engineers to complete work in a fraction of the time it used to take and that it is incorporating AI into its product development process.
“AI is technology that can learn, adapt, and make decisions by processing and learning from data, simulating human cognitive functions like reasoning and problem-solving,” says chief digital officer and Cat digital senior vice president, Ogi Redzic.
“AI includes several subfields such as machine learning, deep learning, and generative AI (GenAI) – which grabs the most attention.”
Machine learning can be defined as the ability of computers to learn from experience and make decisions or predictions based on the data alone. Caterpillar gives the example of using machine learning in the area of Condition Monitoring – a suite of technologies Cat dealers use to detect and identify issues and recommend service or maintenance based on data from the machine itself.
Generative AI
GenAI is AI capable of creating new content, text, images, or video. It’s a step forward in manufacturing, allowing computers to complete time-consuming and repetitious tasks. For instance, Caterpillar developers use GenAI to query massive amounts of proprietary information and get practical answers without doing a deep search or spending hours reading thousands of pages of material.
Beyond its own operations, Caterpillar uses digital technologies to develop customer solutions. For example, Caterpillar’s Condition Monitoring Advisors (CMAs) monitor the state of Cat-connected assets in the field by analysing incoming data. In the past, CMAs had to extract data from multiple systems, perform an analysis and make a customer recommendation.
Using Gen AI, the CMAs are now presented with a concise report containing data that has been automatically prepared and summariSed with a recommendation already created. The CMA can then review the report and approve or edit the recommendation. This still requires a human, but the time required to prepare data and create a recommendation is significantly reduced.
“AI will revolutionize the way we interact with machines and design interfaces between systems. It’s fascinating and changing at a very rapid rate,” says Caterpillar chief information officer and IT senior vice president, Jamie Engstrom.
“We’ll continue to see the industry mature, and the accuracy of technologies like Large Language Models (LLMs) will improve.”
Engstrom and her team have developed an Intelligent Automation Center of Excellence and a GenAI community of practice where employees participate in AI use cases.
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