<b>StatisticalProcessMonitoring.jl</b>: A General Framework for Statistical Process Monitoring in <i>Julia</i>
Statistical process monitoring (SPM) control charts are widely used for monitoring the stability of sequential processes. Currently, there is no open-source software which provides a general and extensible implementation of control charts. StatisticalProcessMonitoring.jl is a novel Julia package which aims at addressing this gap, offering support for monitoring various type of data, such as univariate and multivariate observations, partially-observed data streams, and profiles. The package introduces an extensible SPM framework, allowing users to seamlessly design control charts for structured data types using the existing implementation. By introducing a flexible implementation of control charts, StatisticalProcessMonitoring.jl provides fully-automated and efficient algorithms for determining control limits and tuning control chart hyperparameters. These algorithms can accommodate various commonly-used performance metrics based on the run length distribution. The package further leverages existing packages in the Julia ecosystem to offer users a range of optimization and plotting functionalities.
Authors
- Daniele Zago (ORCID: https://orcid.org/0000-0003-0778-7099)
Institutions
- University of Padua (IT)
Publication Details
- Journal
- Journal of Statistical Software
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18637/jss.v113.i07
- Citations
- 1
- Primary Topic
- Time Series Analysis and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 1.49