Rodríguez-Vélez, Ambar G.

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    Evaluation of force requirements and posture in manual coffee harvesting
    (2018) Rodríguez-Vélez, Ambar G.; Pomales-García, Cristina; College of Engineering; Irizarry, Maria de los A.; Monroig Saltar, Francisco M.; Department of Industrial Engineering; Zapata-Medina, Rocío
    Manual coffee harvesting is a common agricultural task, used around the world, with the potential risk for the development of Musculoskeletal Disorder (MSD). This research evaluates the hand and wrist biomechanical risks that workers undergo while harvesting coffee using two manual methods: selective picking and scraping. To evaluate the biomechanical risks associated with the possibility of developing MSDs, the research employed qualitative and quantitative methods such as an adapted Nordic Questionnaire, Rapid Upper Limb Assessment (RULA), Hand Activity Level (HAL) and Regression Analysis. The qualitative assessment results showed that 43% of the sample reported experiencing pain in the hands and wrists in the previous year. This result was related to the findings from the RULA postural analysis, where 60% of the cases, out of 21 evaluations, reflected that the task should be evaluated more thoroughly and changed soon or immediately. In addition, the RULA evaluation evidenced the need to include: tree height, use of a harvesting basket and harvesting method as relevant variables in the postural analysis. The quantitative analysis demonstrated empirical evidence of finger grip and pinch forces between 0.006 N and 21 N in both harvesting methods studied. Also, HAL results suggest that the task has a risk potential for developing MSDs, as exertion forces and frequency of movements showed that 82% of the sensors with highest force activity resulted in hand activity levels above the desired Action Limit for the selective method in comparison to 38% of sensors during the scraping method. Finally, the regression analysis used to predict hand forces, using the qualitative factors and Principal Component Analysis to reduce model complexity, was not appropriate to model the hand forces data obtained from the field study.