An Integrated Grey System Theory Approach for Operational Risk Assessment and Interdependency Analysis in Mineral Processing Plants: A Case of Gohar Zamin Iron Ore Complex (Sirjan, Iran)

Abstract

Operational risk assessment in complex industrial systems like mineral processing plants is hindered by inherent uncertainty and incomplete information. This study presents an integrated grey system theory-based framework to address this challenge. Combining Grey Multi-Criteria Decision-Making (GST-MCDM) and Grey Relational Analysis (GRA), the methodology enables a systemic analysis that prioritizes risks, quantifies interdependencies, and measures cumulative burden across four key objectives: time, cost, quality, and safety. Applied to a case study at the Gohar Zamin iron ore processing plant (Iran), the model analyzed 26 operational risks, classifying them into Critical (8 risks), Significant (9), and Controllable (9) tiers. Electrical power shortage (RPS: 0.19) and raw material supply delay (RPS: 0.21) were identified as the most critical risks. The analysis quantified that the safety objective bears the highest cumulative risk burden at 32%, primarily due to human factor vulnerabilities, while cyber-physical threats ranked among the top 8 critical risks. Strong interdependencies were revealed, notably a quality cascade (relational grade: 0.84) between poor consumable materials and final product failure. Sensitivity analysis confirmed high model robustness (Spearman’s p = 0.91). The framework provides managers with an actionable tool for strategic, cluster-based mitigation and evidence-based resource allocation, emphasizing investment in human capital as a core risk reduction strategy. This research contributes a replicable, quantitative methodology for enhancing operational resilience under uncertainty in capital-intensive industries.