This study tried to identify the problems associated with the posture to be analyzed and tried to suggest guidelines for MSDs(Musculoskeletal Disorders) evaluation based on working posture. A total of 50 jobs from 3 different types of industries(electronics, hospitals, automobiles) were used for MSDs evaluation study which was done by 6 observers. Two indexes were applied to identify the problem in this study which were percentage of agreement and counter-time-error rate. Specifically, ‘counter-time-error rate’ represented a degree of consistency in terms of selecting the posture to be analyzed time after time. Main results of the study were as follows; 1) The average percentage of agreement for representative posture for whole body was relatively higher than that for representative postures for individual body parts, 2) The counter-time-error rate(%) has been reduced as the evaluation process has repeated for the same job. 3) The counter-time-error rate(%) for electronics, hospitals, and automobiles were 63.4%, 61.2%, and 67.3% respectively. 4) The counter-time-error rate(%) for the job with the work cycle of 0.5 to 2 minutes were lower than that of the jobs with the work cycles less than 0.5 minute or greater than 2 minute. 5) The work cycles and the number of trials had significant effects on counter-time-error rate while the types of industries did not have significant effects on counter-time-error rate. Some guidelines could be prepared from the results of the study. Probably, there should have an extension in terms of form and matter for this study in order to have more practical output.

This study tried to develop a basis for quantitative index of working postures associated with WMSDs (Work-related Musculoskeletal Disorders) that could overcome realistic restriction during application of typical checklists for WMSDs evaluation. The baseline data(for a total of 603 jbs) for this study was obtained from automobile manufacturing company. Specifically, data for back posture was analyzed in this study to have a better and more objective method in terms of job relevance than typical methods such as OWAS, RULA, and REBA. Major statistical tools were clustering, logistic regression and so on. The main results in this study could be summarized as follows; 1) The relationship between working posture and WMSDs symptom at back was statistically significant based on the results from logistic regression, 2) Based on clustering analysis, three levels for WMSDs risk at back were produced for flexion as follows: low risk(< 18.5°), medium risk(18.5°～ 36.0°), high risk(> 36.0°), 3) The sensitivities on risk levels of back flexion was 93.8% while the specificities on risk levels of back flexion was 99.1%. The results showed that the data associated with back postures in this study could provide a good basis for job evaluation of WMSDs at back. Specifically, this evaluation methodology was different from the methods usually used at WMSDs study since it tried to be based on direct job relevance from real working situation. Further evaluation for other body parts as well as back would provide more stability and reliability in WMSDs evaluation study.