The APBC’ s transition to autonomy saw labour productivity increase by
43 % helped the team save time up front and improve confidence as the facility ramped up.
Q. WHICH DATAPOINTS DO YOU USE THAT STANDARD TELEMETRY MISSES?
» While standard telemetry tracks basic machine uptime or static outputs, the APBC facility uses contextualised data and AI tools to capture real-time energy and compressed air consumption data across multiple lines and assets. This helps detect unseen air leakages and track energy inefficiencies. Additionally, manufacturers feed contextual data collected from the machine, manuals, downtime logs and historical data into AI tools and maintenance copilots for equipment troubleshooting and instant quality root-cause analysis. All this data is born in the automation systems deployed throughout the factory.
Q. WHAT WERE THE BIGGEST CHALLENGES? WHAT DIDN’ T WORK THE FIRST TIME?
» The biggest challenges during the transition were rooted in culture and change management, rather than the technical tools. Employees needed to step out of their comfort zones, and we had to upskill the workforce to implement these technologies and manage the transition from strictly defined traditional operational roles to more dynamic, cross-functional positions. To overcome this, we introduced fusion operating teams that intentionally brought IT, OT and
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