Food producers are now modeling traditional maintenance data, such as vibration and frequency, and executing machine learning in the cloud with digital twin simulations. Anomalies are being modeled while also providing advanced analytics, reducing downtime and repurposing staff.
Blake Moret, CEO, Rockwell Automation, opened the 2025 Automation Fair by stressing that manufacturers are using automation to move toward autonomy, machine learning and AI strategies. In essence, doing more with less.
Food manufacturers are also embracing doing more with less when it comes to predictive maintenance. Companies are investing in digital twin and cloud monitoring platforms to scale predictive maintenance across plants, reduce preventive workloads, deliver advanced visibility and repurpose workers. This article will examine case studies, technologies and approaches for launching these predictive maintenance programs.