Occupational Risks in a Brazilian Aluminum Forming Industry: Risk Analysis and Work Environment
Data on work accidents reflect the incidence of harm to workers’ health and occupational diseases, supported by studies that indicate the influence of length of service on service, age, and dominant skills as contributing factors to occupational accidents. This study aimed to assess whether the work...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Safety |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-576X/11/2/30 |
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| Summary: | Data on work accidents reflect the incidence of harm to workers’ health and occupational diseases, supported by studies that indicate the influence of length of service on service, age, and dominant skills as contributing factors to occupational accidents. This study aimed to assess whether the working environment conditions were favorable to workers and to determine whether gender, age, and length of service influenced the occurrence of work-related accidents. The goal was to identify and mitigate risk factors to improve worker health. Descriptive statistics techniques, including Pearson correlation, Analysis of Variance, the Tukey’s test, and Cluster Analysis were applied. Additionally, a categorical variable analysis (survey) was conducted to assess the work environment, alongside postural analysis using the OWAS (Ovako Working Posture Analyzing System) method. The results revealed noise levels exceeding recommended limits in almost all investigated sectors, as well as inadequate illuminance and temperature conditions on the production line. The clustering analysis identified three distinct groups. Group 1: Individuals aged 18 to 27 with little experience in the activity, of whom 42% reported pain or discomfort. Group 2: Older operators with 62% experiencing pain or discomfort. Group 3: Young male workers with experience in the role, a higher incident of work accidents, and alcohol consumption up to three times a week, of whom 50% reported pain or discomfort. Statistical inference allowed the identification of process deficiencies and a detailed analysis of work-related pain through self-perceived diagnosis, enabling corrective actions to similar processes and contributing to existing research. |
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| ISSN: | 2313-576X |