Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 10, 2025Open Access

Statistical Process Control for Real-Time Industrial Data Streams

View Full Paper
Ask AI
Bookmark
Share

Authors

MAMuhammad Waqas AhmadKKKaleem Nawaz KhanRARehan Ahmad

Discussion

Loading...

Member takes

Overview

This analysis compares control charts (Shewhart, CUSUM, EWMA) for detecting shifts in real-time data, highlighting effectiveness and false alarm trade-offs.

Key Points

  • CUSUM chart signaled the earliest shift detection at observation 17, indicating high sensitivity.
  • EWMA chart detected the average shift at observation 156, providing a balance between stability and sensitivity.
  • Shewhart chart detected a significant shift at observation 158 with fewer signals, showcasing robustness for larger changes.
  • The study emphasizes choosing appropriate SPC methods based on specific process characteristics and alarm tolerance.

Cite This Study

Ahmad et al. (2025) studied this question.

synapsesocial.com/papers/68c1d5fe54b1d3bfb60f923fhttps://doi.org/10.63075/zeggnv87
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1The combined Shewhart–EWMA sign charts2024 · 6 citations
  2. 2Navigating Process Drift: The Power of CUSUM in Monitoring Air Quality Processes and Maintenance Operations2024 · 12 citations
  3. 3An adaptive CUSUM chart for robust monitoring of multivariate processes2025 · 4 citations
  4. 4Ameliorating the diagnostic power of combined shewhart-memory-type control chart strategies for mean2024
  5. 5EWMA Control Chart for Monitoring Circular Data2026