SCOPE

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SQC Horizons 2026 aims to bring together researchers, practitioners, and educators to discuss recent developments in Statistical Quality Control (SQC) within increasingly complex and data-driven environments. As modern systems evolve, the need for rigorous, adaptive, and analytically grounded quality methodologies has become central across scientific research, industrial applications, and digital infrastructures.

The workshop will address advances in statistical process control, data analytics, and modern monitoring methodologies, with applications spanning engineering, life sciences, and digital systems. Particular attention will be given to challenges associated with non-stationary processes, autocorrelated data, and real-time monitoring, which are critical in both traditional and emerging domains.
 

A distinctive component of the workshop is the exploration of SQC methodologies within e-learning systems. The increasing availability of learning data enables the application of statistical tools to monitor student engagement, assess performance, and support the continuous improvement of educational processes. This perspective highlights the relevance of SQC beyond conventional industrial settings, extending its scope to data-driven educational environments.

 

The workshop is particularly oriented toward Master’s, PhD, and postdoctoral researchers, providing a dedicated platform for the dissemination and discussion of emerging research. To promote broad participation and inclusivity, SQC Horizons 2026 will be conducted in a fully hybrid format and will not require a registration fee, thereby facilitating access for early-career researchers worldwide.
 

By fostering interdisciplinary exchange, the workshop seeks to strengthen the connection between theoretical developments and practical applications, contributing to the advancement of statistical methodologies for quality monitoring and improvement across science, industry, and education.