As packaging plants grow increasingly connected, companies are leveraging advanced technologies like machine learning, digital twins, and predictive maintenance to optimize operations and increase throughput. According to a recent feature in Food Engineering, predictive maintenance was voted the top ROI-driving investment at the 2025 Connected Workforce Conference, with 55% of respondents ranking it highest.

Jorge Izquierdo, VP of Market Development at PMMI, confirms this trend, citing that 35% of end users plan to boost spending on predictive maintenance. Companies like Hershey and Heinz, along with smaller food brands, are integrating smart data tools, including digital twin platforms, to simulate and test packaging lines virtually without disrupting production.

Kalypso, a Rockwell Automation company, shared how its Emulate3D digital twin software helped a client solve a six-month packaging bottleneck without halting physical operations. Similarly, SmartSights’ ABLE platform is helping manufacturers collect and contextualize real-time data from PLCs and HMIs, enabling powerful root cause analysis and improved OEE performance.

In Europe, OEMs like GREIF-VELOX are embedding condition monitoring and predictive analytics directly into packaging machines, with retrofit-ready solutions designed for older food plants. As connectivity improves, industrial protocols like OPC and MQTT are dismantling data silos, allowing platforms like Ignition SCADA—used by Chobani—to centralize and analyze performance data across entire production lines.

Machine learning is also playing a pivotal role in creating new KPIs. Mark Bertrand of SmartSights explains how custom KPIs like the 'effective rate' (availability × average rate) reveal a packaging machine’s true capacity. In a recent case, ML modeling identified the actual source of bottlenecks on a packaging line, contradicting traditional root cause analysis. Adjustments to machine speed and accumulation rates led to substantial throughput gains.

As manufacturers adopt Unified Namespace (UNS) strategies for data contextualization, connected packaging lines are becoming central to digital transformation. With predictive models, flexible analytics, and better visibility, even complex lines can be continuously optimized, making packaging operations faster, smarter, and more resilient.