Nestle, the world’s largest food and beverage company, is undergoing a significant transformation driven by Artificial Intelligence (AI). This technology is revolutionising Nestle’s operations, enhancing efficiency, and paving the way for a more sustainable future.

One of the most impactful applications of AI at Nestle is predictive maintenance. By leveraging machine learning and sensor data, Nestle can anticipate equipment failures before they happen. This proactive approach minimises downtime, reduces maintenance costs, and enhances production efficiency.

Predictive maintenance works by using AI to optimise maintenance schedules and identify small issues before they escalate into major failures. McKinsey reports that AI-driven predictive maintenance can decrease equipment stoppages by 30-50% and increase their lifespan by 20-40%, improving Health, Safety, and Environment (HSE) standards and overall equipment uptime.

Imagine a factory filled with intelligent machines. Sensors constantly monitor their health, feeding data into AI algorithms. These algorithms analyse the data and predict potential issues, alerting maintenance crews to address them before they disrupt production.

AI-powered predictive maintenance analyses historical performance data to forecast when a machine is likely to fail, limiting its downtime and identifying the root cause of the problem. It uses data contextualization to build a 3D representation of operations, with Reality Capture attaching field images for Computer Vision to autonomously identify anomalies such as pitting, welding, discontinuities, and corrosion using Deep Neural Networks. Machine Learning then builds a picture of the current and future state of operations.

Unlike human planners, this approach accounts for thousands of variables and constraints, improving uptime, reducing costs, and increasing safety. Deloitte reported in 2022 that predictive maintenance can reduce facility downtime by 5-15% and increase labour productivity by 5-20%. This enables operators to make better decisions, compare the real impact of parameters on business outcomes, and consider counterintuitive actions to improve productivity or profitability.

Nestle’s AI-powered maintenance not only saves money but also contributes to its goal of achieving net zero carbon emissions by 2050. By minimising downtime and optimising energy usage, Nestle reduces its environmental footprint.

Nestle’s embrace of AI is comprehensive, with a global program to ensure responsible and strategic implementation. This program focuses on identifying real-world use cases, building a robust data infrastructure, and developing internal talent.

A prime example of Nestle’s success with AI is the Al Maha factory in Dubai, which uses Schneider Electric’s EcoStruxure technology. EcoStruxure monitors the factory’s electrical systems in real-time, leveraging AI to predict potential faults and optimise energy usage.

This state-of-the-art factory benefits from an innovative approach to maintaining its Low Voltage electrical machinery. The solution helps monitor power management, electrical loads, and temperature settings from all connected assets, allowing proactive issue resolution, minimising downtime, and mitigating safety risks.

Opened in 2017, the Al Maha factory produces NESCAFÉ and MAGGI products, runs on 100% LED lighting, recycles 100% of its waste, and has installed the country’s largest ground-mounted private solar plant, generating 9GWh annually, eliminating nearly 6 million kilograms of CO2 per year. This highlights the potential of AI to create a win-win situation, boosting efficiency and environmental responsibility.

Nestle’s journey with AI is ongoing, with the company continuously seeking new ways to leverage this technology across its global operations. As it refines its AI strategy and expands use cases, we can expect even more impressive results in the future.

Works Cited

• Evans, Scarlett. “Feeding The Cognitive Enterprise: Nestle Pushes AI, Predictive Maintenance, Robotics.” IoT World Today, 27 September 2021, https://www.iotworldtoday.com/robotics/feeding-the-cognitive-enterprise-nestl-pushes-ai-predictive-maintenance-and-robotics. Accessed 30 April 2024.
• Kunie, Jorge. “How to leverage the full potential of AI Predictive Maintenance – Vidya.” Vidya Technology, 10 April 2024, https://vidyatec.com/blog/why-is-ai-so-crucial-for-predictive-maintenance/. Accessed 30 April 2024.
• Malmaison, Rueil. “Schneider Electric implements predictive maintenance for Nestlé’s Dubai South factory.” Schneider Electric, 19 July 2021, https://www.se.com/ww/en/about-us/newsroom/news/press-releases/schneider-electric-implements-predictive-maintenance-for-nestl%C3%A9%E2%80%99s-dubai-south-factory-60ec1e5d9da4a27b50547304. Accessed 30 April 2024.
• “Nestle moving towards AI-driven Business | MirrorReview.” Mirror Review, https://www.mirrorreview.com/nestle-usa-moving-towards-ai-driven-business/. Accessed 30 April 2024.
• sitiatarfa8. “AI and Technology in Food Manufacturing: How Nestle and Others Stay on Top.” Kitameraki, 30 March 2023, https://www.kitameraki.com/post/staying-ahead-of-the-game-how-food-manufacturers-are-utilizing-technology-to-stay-on-top. Accessed 30 April 2024.