Date of Award

8-16-2024

Document Type

Open Access Thesis

Department

Mechanical Engineering

First Advisor

Ramy Harik

Abstract

Quality Management (QM) is essential in manufacturing to ensure products are consistent and functional every time. Consumers expect high quality products that last, and industries unable to accomplish this are destined to fail. Therefore, product quality has always been at the forefront of manufacturer decision making, though it is normally viewed as a given more than as a goal. This means that businesses want quality because it is needed for their survival, but there has not been consideration for how to incorporate innovation into this essential field. Quality needs to be viewed holistically with regards to all manufacturing factors that affect it. A Holistic Quality Management (HQM) Model was designed through the identification of crucial pillars, themes, and metrics in literature. The relationships between these features and their effect on product quality were utilized and quantified to calculate a Quality Assurance (QA) score. This model represents a generic version that can be used out of the box for a variety of industries for immediate insight into their quality performance. It acts as a starting point for these facilities to cater to their specific needs. A user-friendly interface was developed to give both high-level scoring and allow for deeper dives to determine sources for quality shortcomings. The Future Factories (FF) lab in the McNair Aerospace Center at the University of South Carolina acted as a test bed for this project. To showcase the model’s flexibility multiple versions were created for different industries where metrics would have different impact on product quality or where specific metrics may need to be added or subtracted. This holistic model acts as a guide on what to focus on for QM and planning, improves QA through a straightforward score, and uncovers the metrics at the root of quality issues which leads to better Quality Control (QC). With the inclusion of live data, Closed-Loop Quality (CLQ) can be achieved where overall quality is improving for existing products. The facility can then shift left and improve the implementation of new products faster. This is all packaged into a simple interface that is accessible for the needs of users from the shop level to upper management.

Rights

© 2024, Devon Blakeney Clark

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