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Artificial intelligence (AI) models such as ChatGPT are designed to rapidly process data. Using the AI ChatGPT-4 platform to ...

In this paper, we consider the Bell distribution to introduce two new exciting, and useful statistical control charts for counting processes, which are capable of monitoring count data with ...

Process control charts are an important application of statistical process control (SPC) that are used in the management of processes in various industries with the aim of maintaining consistency, ...

I'm looking for a Python library that supports non-parametric statistical process control (SPC) charts. Specifically, I need functionality for SPC charts that do not assume a normal distribution of ...

Time-series charts highlight changes but do not clarify whether data lie outside expected variation. Statistical process control (SPC) charts make this distinction and have been demonstrated to be ...

Detecting anomalies in the injection molding process remains a challenging task, demanding significant resources, data, and expertise due to their impact on cost and time reduction. While traditional ...

Hybrid Approach Integrating Deep Learning-Autoencoder With Statistical Process Control Chart for Anomaly Detection: Case Study in Injection Molding Process Abstract: Detecting anomalies in the ...

The use of statistical process control (SPC) charts in healthcare is increasing. The primary purpose of SPC is to distinguish between common-cause variation which is attributable to the underlying ...

PCB chemical manufacturing processes can violate data independence and normality. The most critical assumption made concerning statistical process control (SPC) charts is that of data independence ...