Dynamic Failure-Probability Updating from Quality-System Signals: A Monotone Transfer Model for Risk and Reliability Monitoring

This record contains version v1.4 of the preprint and supplementary materials for: Dynamic Failure-Probability Updating from Quality-System Signals: A Monotone Transfer Model for Risk and Reliability Monitoring This version is aligned with the journal-submitted manuscript submitted in June 2026 to Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. The manuscript presents a methodological risk and reliability monitoring model for updating failure-probability estimates from controlled quality-system signals. The model uses a monotone logit-scale transfer equation, sign-constrained coefficient governance, uncertainty propagation, hysteresis-based alert states, and auditable calculation records. The work is not presented as a validated predictive model, regulatory compliance evidence, conformity evidence, certification evidence, safety proof, or authority-accepted tool. The demonstration uses synthetic variable-regime data. Empirical coefficient calibration, sensitivity analysis, and field validation against independent outcomes are required before operational deployment. Files included in this version: Main manuscript PDF Main manuscript DOCX Supplementary File 1: Public-data validation protocol PDF Supplementary File 1: Public-data validation protocol DOCX Supplementary File 2: Synthetic demonstration dataset CSVC SHA-256 checksum manifest Version DOI:https://doi.org/10.5281/zenodo.20766638

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-19
DOI
https://doi.org/10.5281/zenodo.18097045
Primary Topic
Healthcare Technology and Patient Monitoring
Type
preprint
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preprint

Dynamic Failure-Probability Updating from Quality-System Signals: A Monotone Transfer Model for Risk and Reliability Monitoring

Mehdi Zadehnour
Zenodo (CERN European Organization for Nuclear Research)
Healthcare Technology and Patient Monitoring
preprint

Dynamic Failure-Probability Updating from Quality-System Signals: A Monotone Transfer Model for Risk and Reliability Monitoring

Mehdi Zadehnour
preprint en

Abstract

This record contains version v1.4 of the preprint and supplementary materials for: Dynamic Failure-Probability Updating from Quality-System Signals: A Monotone Transfer Model for Risk and Reliability Monitoring This version is aligned with the journal-submitted manuscript submitted in June 2026 to Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. The manuscript presents a methodological risk and reliability monitoring model for updating failure-probability estimates from controlled quality-system signals. The model uses a monotone logit-scale transfer equation, sign-constrained coefficient governance, uncertainty propagation, hysteresis-based alert states, and auditable calculation records. The work is not presented as a validated predictive model, regulatory compliance evidence, conformity evidence, certification evidence, safety proof, or authority-accepted tool. The demonstration uses synthetic variable-regime data. Empirical coefficient calibration, sensitivity analysis, and field validation against independent outcomes are required before operational deployment. Files included in this version: Main manuscript PDF Main manuscript DOCX Supplementary File 1: Public-data validation protocol PDF Supplementary File 1: Public-data validation protocol DOCX Supplementary File 2: Synthetic demonstration dataset CSVC SHA-256 checksum manifest Version DOI:https://doi.org/10.5281/zenodo.20766638

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Healthcare Technology and Patient Monitoring
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