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dc.contributor.advisorJimenez, Jesus
dc.contributor.authorSudarsan, Madhusudan ( Orcid Icon 0000-0003-0144-8563 )
dc.date.accessioned2020-07-31T15:58:48Z
dc.date.available2020-07-31T15:58:48Z
dc.date.issued2020-08
dc.identifier.citationSudarsan, M. (2020). Using wearable sensors to evaluate material handling operator’s fatigue in repetitive activities: A design of experiments approach (Unpublished thesis). Texas State University, San Marcos, Texas.
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/12265
dc.description.abstractManual Material Handling is one the major causes which contributes to a large percentage of musculoskeletal disorders. In a manufacturing environment, associates lift loads repeatedly which leads to physical fatigue. Human fatigue not only leads to critical injuries, but also lowers productivity in a work environment which has an impact on the entire supply chain process. Hence, physical fatigue is a challenging safety issue in a manufacturing environment. In this research, a Lifting fundamental skill move mimicking a manufacturing environment is physically simulated with the use of Hexoskin sensors and a motion capture framework. The motion capture framework consists of multiple high version cameras, a workstation to perform the experiment, Hexoskin sensors, and a processor that collects a catalog of Bio-MoCap data on a time-series. The main goals of the study are to 1) determine the correlation of the physiological variables with the subjects RPE level of the Lifting skill move on the Borg’s scale, and 2) predict the level with respect to the task. In this study, we use statistical analysis and regression techniques to determine the relationship of the bio-factors with fatigue. A separate regression model is built to predict fatigue with respect to heart rate and time function. Results show the statistical significance of the bio-factors in the process of getting fatigued. A multiobjective optimization method is used for posture prediction and analysis with consideration of fatigue effect and its application case. This research has potential to contribute in the field of manual material handling and can help in efficiently planning workforce with the available resource.
dc.formatText
dc.format.extent82 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectManual material handling
dc.subjectFatigue
dc.titleUsing Wearable Sensors to Evaluate Material Handling Operator’s Fatigue in Repetitive Activities: A Design of Experiments Approach
txstate.documenttypeThesis
dc.contributor.committeeMemberMéndez Mediavilla, Francis A.
dc.contributor.committeeMemberPérez, Eduardo
thesis.degree.departmentEngineering
thesis.degree.disciplineEngineering
thesis.degree.grantorTexas State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
txstate.departmentIngram School of Engineering


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