Ergonomic risk assessment through group decision-making approach for cashew processing under uncertainty

Area of Science:

• Occupational Health
• Ergonomics
• Industrial Safety

Background:

• Labor-intensive industries like cashew processing present significant risks of musculoskeletal disorders (MSDs).
• Women constitute the majority of the workforce and are disproportionately affected by ergonomic hazards.
• Conventional Ergonomic Risk Assessment (ERA) methods struggle to account for subjective worker discomfort and risk perception, leading to potential underestimation of risks.

Purpose of the Study:

• To develop and present a novel fuzzy logic-based methodology for enhancing Ergonomic Risk Assessment (ERA).
• To provide a more precise framework for predicting and managing ergonomic risks specifically within cashew processing units.
• To validate the effectiveness of fuzzy logic in addressing uncertainties in risk assessment.

Main Methods:

• A two-phase study was conducted, beginning with a structured questionnaire to gauge worker discomfort over an eight-hour shift.
• Ergonomic hazards were systematically identified in the second phase.
• A fuzzy uncertainty model was employed to analyze exposure to risk factors and evaluate the level of ergonomic risk.

Main Results:

• Cashew shelling was identified as a high-risk activity, primarily affecting women workers.
• Prolonged trunk flexion and highly repetitive motions (over 20 repetitions/minute for >6 hours daily) were key contributing factors to high risk.
• Fuzzy computation confirmed the elevated risk levels in cashew shelling, underscoring the need for immediate ergonomic interventions.

Conclusions:

• Integrating fuzzy logic into ERA significantly enhances its accuracy in evaluating ergonomic risks.
• This approach facilitates the early detection of potential ergonomic hazards in industrial settings.
• Proactive implementation of ergonomic interventions, informed by fuzzy logic-based risk assessment, can substantially reduce work-related injuries and improve overall worker well-being.