Applied Machine Learning in Agro-Manufacturing Occupational Incidents

Kakhki, Fatemeh Davoudi; Freeman, Steven A.; Mosher, Gretchen A.

doi:10.1016/j.promfg.2020.05.016

Cited by 6 publications

(2 citation statements)

References 47 publications

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“…Using this AI method also helps in decision-making concerning the prevention, diagnosis, and treatment of diseases. For example, Kakhki et al [ 8 ] predicted the extent of the body part(s) damaged in accidents occurring at grain handling facilities using decision trees and naïve Bayes algorithms. In this way, the frequency of such incidents can be reduced, and medical indemnity payments are prevented.…”

Section: Related Workmentioning

confidence: 99%

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Human-Centered Explainable Artificial Intelligence: Automotive Occupational Health Protection Profiles in Prevention Musculoskeletal Symptoms

Mollaei

Fujão²,

Silva

et al. 2022

IJERPH

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In automotive and industrial settings, occupational physicians are responsible for monitoring workers’ health protection profiles. Workers’ Functional Work Ability (FWA) status is used to create Occupational Health Protection Profiles (OHPP). This is a novel longitudinal study in comparison with previous research that has predominantly relied on the causality and explainability of human-understandable models for industrial technical teams like ergonomists. The application of artificial intelligence can support the decision-making to go from a worker’s Functional Work Ability to explanations by integrating explainability into medical (restriction) and support in contexts of individual, work-related, and organizational risk conditions. A sample of 7857 for the prognosis part of OHPP based on Functional Work Ability in the Portuguese language in the automotive industry was taken from 2019 to 2021. The most suitable regression models to predict the next medical appointment for the workers’ body parts protection were the models based on CatBoost regression, with an RMSLE of 0.84 and 1.23 weeks (mean error), respectively. CatBoost algorithm is also used to predict the next body part severity of OHPP. This information can help our understanding of potential risk factors for OHPP and identify warning signs of the early stages of musculoskeletal symptoms and work-related absenteeism.

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Section: Related Workmentioning

confidence: 99%

“…Researchers have been involved in the treatment of musculoskeletal symptoms, while others have focused on preventing them (see as an e.g., [ 8 ]). This assessment is a sort of HCXAI that connects humans and Artificial Intelligence (AI) ( Figure 1 ).…”

Section: Introductionmentioning

confidence: 99%

Human-Centered Explainable Artificial Intelligence: Automotive Occupational Health Protection Profiles in Prevention Musculoskeletal Symptoms

Mollaei

Fujão²,

Silva

et al. 2022

IJERPH

View full text Add to dashboard Cite

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Exploring Features to Classify Occupational Accidents in the Retail Sector

Sena,

Braga,

Novais

et al. 2024

Communications in Computer and Information Science

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The Machine Learning approach is used in several application domains, and its exploitation in predicting accidents in occupational safety is relatively recent. The present study aims to apply different Machine Learning algorithms for classifying the occurrence or non-occurrence of accidents at work in the retail sector. The approach consists of obtaining an impact score for each store and work unit, considering two databases of a retail company, the preventive safety actions, and the action plans. Subsequently, each score is associated with the occurrence or non-occurrence of accidents during January and May 2023. Of the five classification algorithms applied, the Support Vector Machine was the one that obtained the best accuracy and precision values for the preventive safety actions. As for the set of actions plan, the Logistic Regression reached the best results in all calculated metrics. With this study, estimating the impact score of the study variables makes it possible to identify the occurrence of accidents at work in the retail sector with high precision and accuracy.

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