HAZOP Using Multi-criteria Decision Making (MCDM) and Fuzzy Logic
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Date
2024-09-03
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The University of Sheffield
Abstract
Conclusions and recommendations
The working of paint mixers in the chemical manufacturing sector involves inherent safety
and operational hazards - equipments malfunction, human errors in mixing and some
variance in the process parameters. To advance safety management and operation
effectiveness in such high-risk environments, this research project sought to design the
integrated risk assessment model by integrating HAZOP analysis with MCDM tools that
include AHP, TOPSIS and Fuzzy Logic.
The first aim was to produce a shift towards a more systematic, objective and ‘unguardable’
framework to guide the identification of hazards and their risk evaluation. This was in the
context of a project conducted within the Al Basma Paints & Chemicals Factory: The first
part of the project was focused on a vigorous HAZOP analysis of the paint mixing process as
well as risk analysis and risk assessment carried out based on a number of risk factors
utilizing AHP. Then, a ranking of the safety measures based on the effectiveness was
computed using TOPSIS, while, Fuzzy Logic was used to incorporate the uncertainties of the
expert judgment.
Description
The integrated application of AHP (Analytic Hierarchy Process), TOPSIS (Technique
for Order Preference by Similarity to Ideal Solution), and Fuzzy Logic in the risk assessment
framework provided a comprehensive and effective approach for prioritizing safety measures
in the paint mixing process at Al Basma Paints & Chemicals Factory. The combined
methodologies allowed for a detailed evaluation of the relative importance of various
parameters, including Pigment, Safety, Temperature, Impeller, Position, Mixing Time, and
Agitation, in maintaining operational safety and product quality.
6.1 Key Findings:
1. High-Priority Parameters:
a) Pigment Handling: The results consistently identified Pigment handling as
the highest priority parameter across all methods. Training for operators and
implementing control systems were found to be the most effective safety
measures. This aligns with general theories on risk management, where
human error in handling critical materials often leads to significant safety
issues.
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