DYNA JOURNAL ENGINEERING

Key words:

Ingeniería de procesos, simulación 3D, ergonomía, OCRA Check-List, modelo humano digital (DHM), Process Engineering, 3D simulation, ergonomic, OCRA Check-List, digital human modelling (DHM)

Article type:

ARTICULO DE INVESTIGACION / RESEARCH ARTICLE

Section:

RESEARCH ARTICLES

ABSTRACT:
The use of simulation tools and three dimensional (3D) computer aided design is currently widespread in Process Engineering for machine design, manufacturing tools and dimensional control models, but it is not so common for method and job design. For workplace design it is essential to have all data from product, process, and resources needed to manufacture. Human factor is a key issue among these resources, as it obliges to make a working environment major study, in order to ensure that operators can perform their tasks in safety way and without injury damages. In this way, the use of a Digital Human Model as a first element of the denominated ‘Digital Manufacturing‘, is an excellent opportunity to integrate all the product-process design elements into a real concurrent engineering, which allows to analyze important variables such as ergonomics or time estimation. From ergonomics point of view, all the possible and potential injuries in the musculoskeletal system which could be a result or consequence of job tasks development have generated a great interest at Manufacturing Engineering. This paper presents an addition, extension and annexe of the ergonomic analysis methods for these risks prevention, which currently has one of the most used tools in sectors such as aeronautics and automotive. It has been for the first time satisfactorily implemented the OCRA Check-List method in a 3D design and simulation environment application, evaluating the simulation tool ability and capacity for tasks time prediction. The application, together with the evaluator active participation, permits to make correct risks analysis of musculoskeletal injuries due to repetitive work, as well as tasks time development estimation.