“Artificial Intelligence Model Based on Grey Clustering to Access Quality of Industrial Hygiene: A Case Study in Peru“
Descripción del Articulo
“Industrial hygiene is a preventive technique that tries to avoid professional illnesses and damage to health caused by several possible toxic agents. The purpose of this study is to simultaneously analyze different risk factors (body vibration, lighting, heat stress and noise), to obtain an overall...
Autores: | , , , , |
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Formato: | artículo |
Fecha de Publicación: | 2023 |
Institución: | Universidad Privada Norbert Wiener |
Repositorio: | UWIENER-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.uwiener.edu.pe:20.500.13053/9103 |
Enlace del recurso: | https://hdl.handle.net/20.500.13053/9103 |
Nivel de acceso: | acceso abierto |
Materia: | artificial intelligence; grey clustering; industrial hygiene 1.02.00 -- Informática y Ciencias de la Información |
Sumario: | “Industrial hygiene is a preventive technique that tries to avoid professional illnesses and damage to health caused by several possible toxic agents. The purpose of this study is to simultaneously analyze different risk factors (body vibration, lighting, heat stress and noise), to obtain an overall risk assessment of these factors and to classify them on a scale of levels of Unacceptable, Not recommended or Acceptable. In this work, an artificial intelligence model based on the grey clustering method was applied to evaluate the quality of industrial hygiene. The grey clustering method was selected, as it enables the integration of objective factors related to hazards present in the workplace with subjective employee evaluations. A case study, in the three warehouses of a beer industry in Peru, was developed. The results obtained showed that the warehouses have an acceptable level of quality. These results could help industries to make decisions about conducting evaluations of the different occupational agents and determine whether the quality of hygiene represents a risk, as well as give certain recommendations with respect to the factors presented.“ |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).