# Production System Monitoring Based on Petri Nets Enhanced with Multi-Source Information

## TL;DR

This paper introduces a new system for monitoring production lines using wearable sensors and enhanced Petri nets to improve real-time decision-making and system responsiveness.

## Contribution

The novel contribution is a multi-source information-enhanced Petri nets model combined with wearable sensing for dynamic and accurate production system monitoring.

## Key findings

- Wearable sensing enriches state perception in industrial scenarios.
- The Petri nets model provides real-time visual representation of production line operations.
- The approach was successfully implemented in a real-world production system for civil defense doors.

## Abstract

As the manufacturing industry continues to advance its digital transformation, intelligent sensing technology has become a key support for achieving precise, efficient and automated quality control. However, current production line monitoring systems predominantly rely on fixed and costly monitoring equipment and sensors, lacking flexible and interactive first-person perspective perception approaches centered on on-site operators. Meanwhile, factory process monitoring often depends solely on visual expression rather than balancing the capabilities of the simulation model and visual state detection, leading to delayed responses to abnormal systems and hindering the adjustment strategy feedback. To address these limitations, this study provides wearable sensing for key workers, enriching the state perception capabilities in industrial scenarios. Furthermore, to achieve dynamic model and real-time visual representation of production line operations, a multi-source information-enhanced Petri nets model is proposed in terms of engineering and user-friendliness. With the solid mathematical basics of the Petri nets and the enriched human–machine data from the product line, this method provides an intuitive, dynamic and accurate reflection of the production system’s real-time operational status, offering a scientific and reliable basis for operational decision-making. The proposed approach has been implemented in a real-world production system for reinforced concrete civil defense doors, and this engineering application can also be extended to many other scenarios.