Synergy in Industry 4.0: Adopting a common language for asset management and scheduling

The DIGEST project is pleased to announce a strategic alignment with the DeepScheduling initiative to adopt a Common Modeling Language (CML) for hybrid temporal scheduling. This collaboration marks a significant step toward a holistic view of industrial operations, where production goals and asset management are no longer treated as separate silos.

By leveraging the layered modeling framework developed within DeepScheduling, DIGEST aims to describe asset management operations using the same generic, solver-agnostic language (BPMN/XPDL transforming into ANML/PDDL+) used for production recipes.

Why is this critical for Asset Management? Traditionally, maintenance schedules are often rigid or reactive. By adopting this shared semantic layer, DIGEST can formally model «foreseen activities», such as predictive maintenance interventions, calibration, or tooling replacements, as standard constraints within the global schedule.

This integration enables:

• Unified Visibility: Asset health requirements are translated into executable constraints alongside production workflows.
• Proactive Scheduling: The AI solver can negotiate the best time for maintenance activities based on real-time asset data, minimizing downtime without disrupting critical production targets.
• Digital Twin Interoperability: A seamless flow of data between the asset’s digital twin and the scheduling engine, ensuring that the «capacity» of a machine in the schedule reflects its actual health status.

This approach ensures that the «health» of the factory is prioritized exactly where it belongs: at the heart of the operational schedule.