Application of natural language processing and machine learning in prediction of deviations in the HAZOP study worksheet: A comparison of classifiers

Ekramipooya, Ali; Boroushaki, Mehrdad; Rashtchian, Davood

doi:10.1016/j.psep.2023.06.004

Process Safety and Environmental Protection

2023

DOI: 10.1016/j.psep.2023.06.004

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Application of natural language processing and machine learning in prediction of deviations in the HAZOP study worksheet: A comparison of classifiers

Ali Ekramipooya

Mehrdad Boroushaki

Davood Rashtchian

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2024

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Cited by 10 publications

(1 citation statement)

References 52 publications

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“…Recently, the integration of machine learning and natural language processing (NLP) techniques has created new opportunities for automating various aspects of the brainstorming process [11]. These techniques are used to organize and analyze textual documents in various application domains [12].…”

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confidence: 99%

BERTopic for Enhanced Idea Management and Topic Generation in Brainstorming Sessions

Cheddak,

Ait Baha,

Es-Saady

et al. 2024

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Brainstorming is an important part of the design thinking process since it encourages creativity and innovation through bringing together diverse viewpoints. However, traditional brainstorming practices face challenges such as the management of large volumes of ideas. To address this issue, this paper introduces a decision support system that employs the BERTopic model to automate the brainstorming process, which enhances the categorization of ideas and the generation of coherent topics from textual data. The dataset for our study was assembled from a brainstorming session on “scholar dropouts”, where ideas were captured on Post-it notes, digitized through an optical character recognition (OCR) model, and enhanced using data augmentation with a language model, GPT-3.5, to ensure robustness. To assess the performance of our system, we employed both quantitative and qualitative analyses. Quantitative evaluations were conducted independently across various parameters, while qualitative assessments focused on the relevance and alignment of keywords with human-classified topics during brainstorming sessions. Our findings demonstrate that BERTopic outperforms traditional LDA models in generating semantically coherent topics. These results demonstrate the usefulness of our system in managing the complex nature of Arabic language data and improving the efficiency of brainstorming sessions.

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confidence: 99%

BERTopic for Enhanced Idea Management and Topic Generation in Brainstorming Sessions

Cheddak,

Ait Baha,

Es-Saady

et al. 2024

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HAZOP, FMECA, monitoring algorithm, and Bayesian network integrated approach for an exhaustive risk assessment and real‐time safety analysis: Case study

Nehal,

Mekkakia‐Mehdi,

Lounis

et al. 2024

Process Safety Progress

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Hazard studies are essential in the petrochemical industry to ensure safe operations. This article provides an in‐depth analysis of the hazards associated with a vacuum distillation unit furnace. This study aims to identify probable hazard scenarios related to furnace operation, assess the associated risks, and provide prevention and mitigation strategies. A comprehensive strategy was employed to achieve these objectives, combining two analysis methods: HAZard OPerability (HAZOP) and Failure Modes, Effects, and Criticality Analysis (FMECA). This integrated approach enables a comprehensive risk assessment to be carried out and appropriate preventive measures to be taken to maintain safe operations, including renovation work. Then, depending on the results of the two methods, it is essential to constantly evaluate equipment safety, taking into account parameters such as furnace efficiency, tube temperature, and fume temperature. Therefore, a monitoring program has been created in Python, which enables real‐time examination of the furnace's safety with these critical parameters. If safety conditions are compromised, alarms are sent to mitigate risks, particularly in case of a failure. A Bayesian model is also developed to evaluate the algorithm's results and determine renovation and failure case scenarios. This comprehensive approach improves risk assessment's reliability, precision, maintains safe and efficient industrial operations.

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Responsible use of Generative AI in chemical engineering

Daniel,

Xuan

2024

Digital Chemical Engineering

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Application of natural language processing and machine learning in prediction of deviations in the HAZOP study worksheet: A comparison of classifiers

Cited by 10 publications

References 52 publications

BERTopic for Enhanced Idea Management and Topic Generation in Brainstorming Sessions

BERTopic for Enhanced Idea Management and Topic Generation in Brainstorming Sessions

HAZOP, FMECA, monitoring algorithm, and Bayesian network integrated approach for an exhaustive risk assessment and real‐time safety analysis: Case study

Responsible use of Generative AI in chemical engineering

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