A Risk-Ranked Maturity Framework for Pre-Start-Up Safety Review as a Barrier Integrity Indicator in Commissioning Systems
Abstract
Purpose: Pre-Start-Up Safety Review (PSSR) is widely required prior to introducing hazardous energy into process systems, yet it is often implemented as a compliance checklist rather than a performance-oriented barrier assurance mechanism. This study evaluates whether PSSR maturity at the commissioning boundary reflects operational readiness and contributes to loss prevention.,Methods: A structured PSSR Maturity Index (PMI) was developed to quantify readiness across mechanical completion, safeguard validation, documentation closure, and organizational preparedness. Barrier-focused gap analysis identified vulnerability concentrations, followed by risk-based prioritization to distinguish high-impact deficiencies. Supervised machine learning models, including Logistic Regression, Random Forest, and Gradient Boosting, were applied under stratified cross-validation to assess predictive capability for commissioning performance stability.,Results: PSSR dimensions contributed unevenly to operational stability. Safeguard readiness and mechanical integrity showed the strongest associations with performance outcomes, whereas documentation closure alone demonstrated limited protective value. Machine learning analysis confirmed consistent predictive capability, with Logistic Regression achieving the highest discrimination performance (AUC = 0.865). Sensitivity analysis further supported prioritization robustness.,Conclusion: Interpreting PSSR maturity as a measurable proxy for barrier integrity shifts its role from procedural compliance toward performance-based safety assurance. The framework bridges verification practice and operational risk control while offering a practical pathway for strengthening commissioning safety in resource-constrained industrial environments.
Fields of Study & Subjects
Risk and Safety Analysis
Safety Systems Engineering in Autonomy
Occupational Health and Safety Research
Publication details
- Journal / source
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Publication date
- 1 January 2026
- Document type
- Preprint