<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.

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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
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article

StatisticalProcessMonitoring.jl: A General Framework for Statistical Process Monitoring in Julia

Daniele Zago
1 citations
Journal of Statistical Software
Time Series Analysis and Forecasting
1.49
article

StatisticalProcessMonitoring.jl: A General Framework for Statistical Process Monitoring in Julia

Daniele Zago
article en
1 citations

Abstract

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.

Journal of Statistical SoftwareVol. 113(7)
University of Padua (IT)
Openalex Percentile: Top 16%
Time Series Analysis and Forecasting
1.49
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