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

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.


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Engineering Commons

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