Venue:
SR1
Lecturer:
Valentina Golendukhina - researcher@QE
Abstract:
Data has become a key enabler of innovation in smart manufacturing systems, yet the quality of this data remains a persistent challenge. This talk explores data quality challenges in smart manufacturing and their impact on reliable automation and AI systems. Based on three studies, it highlights common issues in publicly available datasets, introduces best practices for documenting sensor-rich manufacturing data, and presents findings from an industrial case study on data quality at the software-sensor interface (IEC 61131/61499). Emphasis is placed on improving data quality across the entire lifecycle from collection to reuse to enable trustworthy data-driven innovation in Industry 4.0.