PHA Recommendation Prioritization Using Weighted Safety Risk
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Solution Overview
Problem
Chemical plants face challenges in efficiently prioritizing and optimizing the implementation of process hazard analysis (PHA) recommendations due to limited time and resources, leading to incomplete risk reduction.
Innovation Solution
A computer-implemented method using a weighted safety risk (WISER) approach that assigns severity and frequency values to risk scenarios, calculates a risk score, applies credits to recommendations, and iteratively prioritizes them based on their risk reduction potential, allowing for optimized risk mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all PHA recommendations are implemented, then safety risk reduction is maximized, but time and resources are exceeded
Solution Approach 1:
The patent segments the large set of PHA recommendations into prioritized groups based on their risk reduction potential. By calculating a weighted safety risk score for each recommendation and sorting them in descending order, the system divides recommendations into high-priority (top 20-30%) and lower-priority groups, allowing organizations to implement the most critical recommendations first within available time and resource constraints.
Solution Approach 2:
The patent introduces a quantitative parameter system (weighted safety risk score) that transforms qualitative safety assessments into measurable values. By assigning numerical scores to severity, frequency, and risk reduction potential, and calculating composite weighted scores, the system enables objective comparison and prioritization of recommendations, changing the parameter space from subjective judgment to quantifiable metrics.
2Productivity
If PHA recommendations are prioritized by risk reduction potential, then resource efficiency is improved, but calculation complexity increases
Solution Approach 1:
The patent implements a self-service computational system where the prioritization framework automatically calculates weighted safety risk scores, ranks recommendations, and generates prioritized implementation lists without requiring complex manual analysis. The system performs the computationally intensive tasks of data integration, score calculation, and ranking automatically, reducing the burden on users despite the underlying complexity.
Solution Approach 2:
The patent replaces manual, mechanical prioritization processes with an automated computational system. Instead of relying on expert judgment and manual sorting of recommendations, the system uses algorithmic calculations to compute weighted scores and generate prioritized lists, substituting human cognitive effort with automated computational mechanisms.
3Measurement precision
If a detailed risk assessment is performed for each recommendation, then prioritization accuracy is improved, but time consumption increases
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing baseline risk scores, severity weights, and frequency weights before the actual prioritization process. By preparing the computational framework and pre-processing the data structures in advance, the system reduces the time required during actual recommendation prioritization while maintaining detailed assessment accuracy through the pre-established quantitative models.
Data Source
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AI summary
The present invention relates to a computer-implemented method for making predictions for a process hazard analysis (PHA) recommendation, a computer-program product or a computer-readable medium comprising instructions which, when the program is executed by a computer, cause the computer to carry out said method, a system for making predictions for a process hazard analysis (PHA) recommendation comprising an operating unit adapted to carry out said method and having access to a database of said method, and a method of training an artificial intelligence to make predictions for a process hazard analysis (PHA) recommendation.