Researcher ORCID Identifier
0009-0003-5769-5448
Graduation Year
2025
Date of Submission
5-2025
Document Type
Campus Only Senior Thesis
Degree Name
Bachelor of Arts
Department
Science and Management
Reader 1
Nazia Rashid
Reader 2
Anna Wenzel
Terms of Use & License Information
Rights Information
© 2025 Alvin D. Villarosa
Abstract
In the wake of corporate restructuring, Mozarc Medical (MM), a leading medical technology company specializing in kidney care undertook a comprehensive initiative to modernize its Quality Management System (QMS). A critical first step involved optimizing its inherited documentation landscape, consisting of policies, procedures, and work instructions that are not efficient for MM’s current employee management architecture—through artificial intelligence (AI)-driven strategies. Our team found novel ways to incorporate AI into developing MM’s QMS framework and manipulating with quality documentation systems to integrate them into MM’s current architecture. The first two deliverables of a year-long Team Master’s Project involved using AI to consolidate the quality documents inherited: (1) leveraging Microsoft CoPilot to conduct document gap analyses and (2) consolidating overlapping documentation into concise, standardized work instructions. Microsoft CoPilot, was employed to identify redundancies, inconsistencies, and obsolescence within QMS documents. A step-by-step methodology was developed to guide users through document upload, AI-assisted comparison, and synthesis. CoPilot’s AI capabilities reduced manual comparison time from over six hours to approximately 13 minutes per document pair. Based on CoPilot outputs, the team successfully merged a policy and procedure into a streamlined 20-page work instruction using a standardized template.
This foundational work established a scalable workflow for future documentation reform and demonstrated how AI can effectively reduce labor, improve clarity, and support regulatory compliance. The resulting process documentation—including CoPilot work instructions and formatting guides—will serve as key resources for ongoing internal transformation. Future phases of the project will involve completing additional document consolidations, evaluating alternative AI platforms with broader capacity, and integrating finalized documentation into enterprise systems such as Jama and Windchill. This work represents an important step in aligning operational efficiency with the company’s broader digital transformation strategy, ultimately enabling faster innovation, reduced risk, and improved usability of quality systems across the organization.
Recommended Citation
Villarosa, Alvin, "Optimization and Simplification of Mozarc Medical Design Control QMS" (2025). CMC Senior Theses. 3998.
https://scholarship.claremont.edu/cmc_theses/3998
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.
