GOALI: A Symmetry-Based Group Theory Approach to Data Reduction for Micro-Optics Manufacturing

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This Grant Opportunity for Academic Liaison with Industry (GOALI) award provides funding for the development of a symmetry-based data analysis strategy for imaging processing in micro-optics manufacturing. Reducing each image to a small set of numbers based on the symmetry properties of the image will enable a strong correlation between the metrology and both the key manufacturing variables and component performance. The analysis strategy will be based on removing the intended shape of the lens from the measurement, followed by symmetry operations and data reduction methods. Working with industry, the analysis tools will be developed and applied to interferometric measurements of micro-refractive lenses that are photolithographically manufactured to allow correlation between part characterization and performance such as coupling efficiency, in addition to key manufacturing parameters such as photo resist thickness and etch rates. A corresponding measurement and analysis uncertainty will also be a critical component of the research.If successful, the work will allow the physics of the manufacturing process to be correlated to the measurement, leading to optimum process feedback. This will significantly improve the manufacturing of micro-refractive lenses, improving device yield, reducing testing time and cost, and ultimately reducing device cost. Broad dissemination and acceptance by the manufacturing community is ensured by ultimately incorporating the methodology into commercial instrumentation software; demonstrating viability through journal publications, conference presentations, and industry-sponsored technical seminars; developing a continuing education workshop and an advanced laboratory module for undergraduate and graduate education through the Education and Training Facility under the Center for Optoelectronics and Optical Communications at UNC Charlotte; and incorporating the work onto a future micro-optics replication foundry at UNC Charlotte. Material properties and component geometries are strongly influenced by the manufacturing process in replication, and this work will provide an analytical tool to connect part inspection to the physics of the replication process.