Strategy for ergonomic validation of a physical mock-up involving limited user trial
Authors: Amare Wibneh Mengistu, Ashish Kumar Singh, Sougata Karmakar
Abstract: Background and Objective: It is practically impossible to find out an individual with a specific percentile for all the anthropometric dimensions. In traditional anthropometric compatibility evaluation, a large number of participants would be required to represent a specific percentile (say, 5th percentile) of different body dimensions. However, a user trial involving a large number of participants with intended percentile values is a tedious, time-consuming, and costly affair and in many cases not practically feasible. This paper presents a research strategy of how to validate the anthropometric compatibility of a physical mock-up by a small number of participants representing the extreme anthropometric variability of the target populations. Methodology: A case study on the user trial of a physical mock-up of a light armored vehicle (LAV) used by the Ethiopian army was carried out involving a few users from an ergonomic perspective. Following an anthropometric survey (32 variables) of Ethiopian army personnel (n =250 male), 12 key variables (06 dominant variables, 02 variables with less commonality, 03 variables with less correlation coefficient from their respective predictors, and one targeted variable ‘mass’) that account for the variability produced by the 32 original variables were identified using Principal Component Factor Analysis (PCFA) and regression analysis. Following this, Ethiopian army personnel who represent the boundary values (5th or/and 95th p values) of the identified key variables were identified from the targeted population. Thereafter, the compatibility testing (in terms of space occupancy, dimensional clearances, reaching distance, view field, operational activities, etc.) of the physical mock-ups were conducted with the identified subjects. Results: The 12 key variables found from PCFA and regression analysis were stature, sitting height, popliteal height, popliteal length, bideltoid breadth, hip breadth, elbow rest length, arm length, foot length, foot breadth, handbreadth, and mass. Total 07 army personnel were finally identified who represented the extreme measurement values (5th or/and 95th p values) of those key variables and were asked to volunteer for testing. Discussions: As demonstrated in the present study, it is possible to identify less number of key anthropometric variables that are representative of the overall anthropometric variability of the population by using PCFA and regression analysis. A minimal number of volunteers could be identified by using the extreme anthropometric values (5th or/and 95th p values) of the identified key variables. These volunteers could be deployed for user trials to ensure compatibility from an ergonomic perspective. Such an evaluation technique, involving less number of participants would confirm accommodating wide ranges of user populations as well as reduce the cost, time, and resources for physical trial.
Keywords: principal component factor analysis, regression analysis, physical ergonomic analysis, physical mock-up, anthropometric compatibility
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