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All Journal Catalyx : Journal of Process Chemistry and Technology
Dwi Nova Wijaya
Universitas Negeri Surabaya
Chemistry

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Dynamic Risk Assessment of Industrial Safety Barriers Using Bayesian Networks: A Predictive Modeling Approach Dwi Nova Wijaya; Zaenal
Catalyx : Journal of Process Chemistry and Technology Vol. 2 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/catalyx.v2i3.1341

Abstract

Traditional risk assessment methods in chemical and process industries frequently fail to capture the dynamic nature of barrier degradation and hazard escalation. This study proposes a Dynamic Bayesian Network (DBN) framework integrating temporal indicators, including SIS unavailability and corrosion rate, to enhance the predictive accuracy of real-time risk management systems. The DBN was structured using nodes and dependencies derived from industrial scenarios and reliability parameters, then validated through two simulation cases — reactor runaway and corrosion-driven leak — utilizing real-time inputs of dT/dt and k_cor to dynamically update failure probabilities via MATLAB. Results demonstrate that barrier degradation significantly impacts risk profiles: escalation probability in the reactor runaway scenario increased from 0.10 to 0.45 as SIS unavailability rose, while leak probability reached severe consequences when barrier failure exceeded 60%. Compared to static models, the DBN approach more accurately captured emergent risks over time. The framework supports predictive maintenance, alarm prioritization, and human reliability modeling, establishing DBNs as valuable tools for transitioning toward intelligent, adaptive safety systems in high-risk industries.
Economic Viability of Decision Support Systems for Emergency Risk Reduction in Chemical Industries Dwi Nova Wijaya
Catalyx : Journal of Process Chemistry and Technology Vol. 2 No. 4 (2025): October 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/catalyx.v2i4.1343

Abstract

This study assesses the economic feasibility of implementing a Decision Support System (DSS) in chemical process industries for emergency management and risk reduction. Recognizing the financial stakes involved in industrial incidents, the research evaluates the costs and returns associated with DSS adoption through a structured cost-benefit analysis. The methodology incorporates capital expenditure (CAPEX), operating expenditure (OPEX), avoided incident losses, and insurance premium reductions. Using data modeling and sensitivity analysis, the study calculates net financial benefits and payback periods under various scenarios, ranging from conservative to optimistic projections. Key findings reveal that the DSS investment of USD 450,000, with an annual OPEX of USD 85,000, yields annual economic benefits of USD 290,000 through incident cost avoidance and insurance savings. This translates to a net benefit of USD 205,000 annually and a payback period of approximately 2.2 years. Even under conservative assumptions, the system demonstrates economic viability, confirming its potential to deliver substantial returns beyond its safety functions. The conclusion affirms that DSS integration not only enhances operational safety but also provides compelling financial justification. It encourages broader adoption in high-risk industrial sectors and advocates for future research that integrates intangible benefits and long-term impacts into economic evaluations.
Co-Authors Zaenal