Methodological Evaluation and Panel-Data Estimation of Process-Control System Reliability in Kenya: A Case Study (2000–2026)
Fuente:
Zenodo
Salvato in:
| Autori principali: | , , , |
|---|---|
| Natura: | Recurso digital |
| Lingua: | inglese |
| Pubblicazione: |
Zenodo
2012
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866901065729835008 |
|---|---|
| author | Mwangi, Wanjiku Hassan, Amina Cheruiyot, Kipchumba Otieno, Kamau |
| author_facet | Mwangi, Wanjiku Hassan, Amina Cheruiyot, Kipchumba Otieno, Kamau |
| contents | <p>{ "background": "Process-control systems are critical for industrial and infrastructure operations, yet their long-term reliability in challenging environments is under-researched. There is a paucity of longitudinal, quantitative studies on the performance degradation of such systems in East Africa, limiting evidence-based maintenance and design improvements.", "purpose and objectives": "This case study aims to methodologically evaluate the reliability of industrial process-control systems and to develop a robust panel-data model for estimating failure rates and key influencing factors over an extended operational period.", "methodology": "The study employs a longitudinal case-study design, analysing operational performance data from multiple, geographically dispersed systems. Reliability is modelled using a generalised linear mixed model for panel data. The core statistical model is $\\lambda{it} = \\exp(\\beta0 + \\beta1 X{1,it} + \\mui + \\epsilon{it})$, where $\\lambda{it}$ is the failure rate for system $i$ at time $t$, $X{1,it}$ denotes time-varying covariates (e.g., environmental stress), and $\\mu_i$ represents system-specific random effects. Inference is based on robust standard errors clustered at the system level.", "findings": "The analysis identifies a significant positive association between seasonal humidity extremes and system failure rates. A one standard deviation increase in humidity exposure was associated with a 15% increase in the expected monthly failure rate (95% CI: 9% to 21%). Electrical component degradation emerged as the predominant failure mode, accounting for over 60% of recorded incidents.", "conclusion": "The methodological approach provides a validated framework for quantifying process-control system reliability. Findings confirm that environmental factors are a primary driver of performance degradation in the studied context, with electrical subsystems being particularly vulnerable.", "recommendations": "Design specifications for new installations should mandate enhanced protection for electrical components against humidity. For asset management, we recommend implementing predictive maintenance schedules informed by panel-data reliability forecasts that incorporate local environmental data.", "</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18969137 |
| institution | Zenodo |
| language | eng |
| publishDate | 2012 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Methodological Evaluation and Panel-Data Estimation of Process-Control System Reliability in Kenya: A Case Study (2000–2026) Mwangi, Wanjiku Hassan, Amina Cheruiyot, Kipchumba Otieno, Kamau Process-control systems Panel-data estimation System reliability Sub-Saharan Africa Industrial automation Maintenance engineering Developing economies <p>{ "background": "Process-control systems are critical for industrial and infrastructure operations, yet their long-term reliability in challenging environments is under-researched. There is a paucity of longitudinal, quantitative studies on the performance degradation of such systems in East Africa, limiting evidence-based maintenance and design improvements.", "purpose and objectives": "This case study aims to methodologically evaluate the reliability of industrial process-control systems and to develop a robust panel-data model for estimating failure rates and key influencing factors over an extended operational period.", "methodology": "The study employs a longitudinal case-study design, analysing operational performance data from multiple, geographically dispersed systems. Reliability is modelled using a generalised linear mixed model for panel data. The core statistical model is $\\lambda{it} = \\exp(\\beta0 + \\beta1 X{1,it} + \\mui + \\epsilon{it})$, where $\\lambda{it}$ is the failure rate for system $i$ at time $t$, $X{1,it}$ denotes time-varying covariates (e.g., environmental stress), and $\\mu_i$ represents system-specific random effects. Inference is based on robust standard errors clustered at the system level.", "findings": "The analysis identifies a significant positive association between seasonal humidity extremes and system failure rates. A one standard deviation increase in humidity exposure was associated with a 15% increase in the expected monthly failure rate (95% CI: 9% to 21%). Electrical component degradation emerged as the predominant failure mode, accounting for over 60% of recorded incidents.", "conclusion": "The methodological approach provides a validated framework for quantifying process-control system reliability. Findings confirm that environmental factors are a primary driver of performance degradation in the studied context, with electrical subsystems being particularly vulnerable.", "recommendations": "Design specifications for new installations should mandate enhanced protection for electrical components against humidity. For asset management, we recommend implementing predictive maintenance schedules informed by panel-data reliability forecasts that incorporate local environmental data.", "</p> |
| title | Methodological Evaluation and Panel-Data Estimation of Process-Control System Reliability in Kenya: A Case Study (2000–2026) |
| topic | Process-control systems Panel-data estimation System reliability Sub-Saharan Africa Industrial automation Maintenance engineering Developing economies |
| url | https://doi.org/10.5281/zenodo.18969137 |