Publication Date
2016
Document Type
Dissertation
Committee Members
Adedeji Badiru (Committee Member), Frank Ciarallo (Committee Member), Mark Derriso (Committee Member), Mary Fendley (Advisor), Chandler Phillips (Committee Member)
Degree Name
Doctor of Philosophy (PhD)
Abstract
Manufacturing is a human-driven process that applies energy and manpower to produce consumer goods. In repetitive task processes like manufacturing systems, optimal performance is extremely important for the production employee and the company. In the general fast pace of manufacturing operations, there is the potential for operator errors, which correlates to possible safety issues and loss of revenue. This research explores the influence of cognitive resources on operator performance in manufacturing operations using the Multiple Resource Theory (MRT) and mental workload measures. Computer simulation models and mathematical modeling with Improved Performance Research Integration Tool (IMPRINT) were used to assess mental workload resources to improve human system design for performance of the shop floor employee. This research presents the design, analysis and experimental implementation of a theoretical framework that provides a systematic approach for measuring mental workload using a combination of analytical and empirical techniques. Two experiments are presented to show the effectiveness of the proposed framework. As manufacturing operations become more complex, models can be used to provide recommendations for operator mental workload capacity planning. Therefore, this work is important to industry as manufacturing operations are changing by requiring more complex procedures, which increases the cognitive demand of the operator.
Page Count
151
Department or Program
Ph.D. in Engineering
Year Degree Awarded
2016
Copyright
Copyright 2016, some rights reserved. My ETD may be copied and distributed only for non-commercial purposes and may not be modified. All use must give me credit as the original author.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
