This paper aims to enhance risk assessment during the design phase of petrochemical projects, where ineffective analysis often leads to cost overruns, delays and project failure. It proposes a hybrid gray-FMEA (failure mode and effects analysis) approach to manage uncertainty in expert evaluations and thus improve risk prioritization.
A hybrid approach combining gray theory with the traditional FMEA is proposed to improve the reliability of risk evaluation. The combination addresses uncertainties associated with expert judgments and prioritizes critical failure modes. An intensive literature review and expert input were used to identify key design-stage risks, which were then ranked using the proposed gray-FMEA approach and validated through real-world case studies.
The most identified critical failures include overlooking time and cost constraints, lack of thorough design reviews and inaccurate or missing information. These issues significantly impact project performance and highlight the need for early and structured intervention. The analysis emphasizes the need for a proactive and systematic approach for risk management during the early stages of project development.
The study offers a practical insight for project managers, design engineers and decision-makers in the petrochemical sector. It highlights the importance of conducting structured feasibility analyses, implementing rigorous and regular design reviews and establishing centralized systems for documentation and communication to reduce ambiguity and miscommunication. By adopting the proposed gray-FMEA approach, organizations can strengthen early risk detection, clarify design documentation and implement timely corrective measures before failures escalate, ultimately leading to more successful project outcomes.
This research introduces a novel structured risk assessment framework designed for petrochemical projects. The gray-FMEA approach serves as a practical tool for assisting project managers to proactively identify risks and implement timely corrective actions, thereby enhancing design reliability and overall project performance.
