This paper presents a real-world application of an automated Business Process Mapping (BPM) approach using the NFC-Tracer toolkit in an Italian SME operating in the industrial valve maintenance sector. The proposed method enables an effective data-driven reconstruction of production workflows through passive NFC event logging, without requiring prior knowledge of internal processes or personnel involvement. Over a two-week period, real-time data collection enabled the reconstruction of process sequences, the measurement of crossing times, and the identification of critical performance indicators. Statistical analysis was conducted to determine the best-fit cumulative distribution functions (CDFs) for each processing phase, offering insights into service levels and process variability—especially in relation to valve size. The results demonstrate the feasibility and value of autonomous Business Process Mapping (BPM) for SMEs, providing a lightweight and scalable solution to support digital transformation initiatives. Future developments will focus on extending the system’s capabilities with predictive analytics and real-time monitoring features.
Castracani et al. (2026) studied this question.