Desarrollo de un sistema para la prevención de posturas inadecuadas fundamentado en el método OWAS utilizando técnicas de inteligencia artificial para el procesamiento de imágenes en la Empresa ARBORIENTE S.A.

Abstract

The objective of this study was to develop a system for the prevention of inadequate postures based on OWAS method using artificial intelligence techniques for image processing in the company Arboriente S.A. located in the Puyo city, Pastaza province. The production area of the company was visited to determine the different areas that include the entire manufacturing process and, in this way, to identify the workstations where workers could be exposed to musculoskeletal risks. Once the workstation was identified and met the necessary conditions to perform the analysis both manually and through video images, the appropriate ergonomic method was selected, OWAS, due to the weight to be handled and the amount of repetitive movements that workers must perform to accomplish a specific task. The data collection was carried out by observation technique where it was possible to identify the different phases and movements performed by the workers in suggested time intervals of 20 minutes. The ergoAnalyzer software was developed and then compared with the data collected and processed in Ergonautas' Ergoniza software to verify its accuracy. With the results obtained it was possible to verify that there is a not very significant difference in the different risk levels, taking into account the operating orientation of both programs and thus achieve the required confidence criteria. With the results obtained in the different system tests, it was possible to conclude that the ergoAnalyzer software is reliable for the detection and analysis of musculoskeletal risks in work areas. To achieve reliable and accurate results it was recommended to have appropriate visibility and distances between the system and the work area to be analyzed.