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Sensitivity Analysis of Subjective Ergonomic Assessment Tools: Impact of Input Information Accuracy on Output (Final Scores) Generation


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dc.contributor.advisorDavis, Jerry
dc.contributor.advisorThomas, Roberten_US
dc.contributor.advisorMaghsoodloo, Saeeden_US
dc.contributor.advisorDorris, Nathanen_US
dc.contributor.authorEscobar, Claudiaen_US
dc.date.accessioned2008-09-09T21:17:16Z
dc.date.available2008-09-09T21:17:16Z
dc.date.issued2006-05-15en_US
dc.identifier.urihttp://hdl.handle.net/10415/386
dc.description.abstractSubjective ergonomic assessment tools are widely used by practitioners to detect existing or potentially hazardous conditions. Their output scores are used to design, implement, and evaluate measurements and controls in work environments. The objective of this study was to examine three ergonomic assessment tools and determine which input variables are critical for the outcome generation (final score calculation for hazard level classification). Fifteen tools were initially analyzed according to four criteria: (1) type of input and output data (mainly quantitative); (2) type of assessment yielded (mainly subjective); (3) data collection method/self reporting potential; and (4) the focus of their variables (mainly posture based). RULA, REBA, and JSI were the tools ultimately selected for the study. A data set for each tool was created, iterating its input variables within their range of values originating all possible combinations and their corresponding final hazard scores. Pearson’s correlation tests were run on the data sets and the sensitive variables were identified. The sensitive variables were used to perform a sensitivity analysis, following the principles of the brute force method and simple linear regression model. The brute force method was applied on RULA and REBA. Using this method, individual variables were manipulated while the rest remained constant, being set to their expected values. The disturbance was compared to the base case, comprised of all input variables’ expected values and their associated final hazard score. A simple linear regression model was created for JSI. The critical variables for each tool were selected according to their level of impact on final hazard level classification. For RULA and REBA, the modified correlations were used to rank the critical variables from most to least critical. RULA’s ordered list of critical variables was: (1) upper arm, (2) neck, (3) trunk, and (4) legs. REBA’s ordered list of critical variables was: (1) trunk, (2) upper arm, (3) legs, (4) neck, and (5) wrist. For JSI, modified coefficients of regression were obtained to rank critical variables from most to least critical: (1) intensity of exertion, (2) hand/wrist posture, (3) speed of work, (4) duration of exertion and efforts/minute, and (5) duration per day. A discussion of research opportunities, limitations of the study, and the self-reporting applicability to the tools studied were also included.en_US
dc.language.isoen_USen_US
dc.subjectIndustrial and Systems Engineeringen_US
dc.titleSensitivity Analysis of Subjective Ergonomic Assessment Tools: Impact of Input Information Accuracy on Output (Final Scores) Generationen_US
dc.typeThesisen_US
dc.embargo.lengthNO_RESTRICTIONen_US
dc.embargo.statusNOT_EMBARGOEDen_US

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