
Keysight Internship
Overview
This summer, I interned at Keysight's Santa Clara facility, working within the Optics Department. My focus was in the continuous glass polishing area, tackling projects aimed at improving process understanding and operational efficiency.
Categories
Optics
Manufacturing
Date
Jun 2024
-
Sep 2024
Title.

My first project characterized our single-sided Chemical-Mechanical Polishing (CMP) machines. The objective was to understand Material Removal Rates (MRR) and track the evolution of surface wavefront using a 4D interferometer.
We used 100 x 70 mm, ~18mm thick glass test pieces, referred to as "Spam Plates," applying ~0.28 PSI pressure with added weight. I designed an experiment using a series of 6-hour polishing runs using three identical parts on different measurement schedules: one with frequent initial measurements (every 30 mins for 2 hrs) transitioning to 2-hour intervals, one measured solely every 2 hours, and a baseline measured only at 0 and 6 hours. This allowed us to specifically capture initial polishing effects and evaluate the impact of repeatedly removing and re-starting parts on the machine.
Data acquisition involved collecting wavefront properties (Peak-to-Valley, RMS) taken with a 4D interferometer. I also performed physical thickness measurements with a micrometer to calculate MRR. All collected data was processed and analyzed using Python.
My second project stemmed from observations of daily operations in the polishing room. I identified inconsistencies and omissions in recorded polishing surface and slurry parameter data, impacting process traceability. Additionally, the main tracking spreadsheet, with four years of daily entries, was slow and cumbersome.
To address this, I developed a Polishing Machine Data Entry Tool. This tool streamlined data input and improved data quality by ensuring mandatory field completion and incorporating data validation checks. It also featured a search function with an Excel preview window, allowing users to query historical data without risking accidental modification. This solution improved data accuracy and completeness and enhanced the efficiency of accessing polishing records.
Note: Due to the nature of this internship I don’t have too many pictures of my work that I can share, but I am allowed to write about my experience.


Keysight Internship
Overview
This summer, I interned at Keysight's Santa Clara facility, working within the Optics Department. My focus was in the continuous glass polishing area, tackling projects aimed at improving process understanding and operational efficiency.
Categories
Optics
Manufacturing
Date
Jun 2024
-
Sep 2024
Title.

My first project characterized our single-sided Chemical-Mechanical Polishing (CMP) machines. The objective was to understand Material Removal Rates (MRR) and track the evolution of surface wavefront using a 4D interferometer.
We used 100 x 70 mm, ~18mm thick glass test pieces, referred to as "Spam Plates," applying ~0.28 PSI pressure with added weight. I designed an experiment using a series of 6-hour polishing runs using three identical parts on different measurement schedules: one with frequent initial measurements (every 30 mins for 2 hrs) transitioning to 2-hour intervals, one measured solely every 2 hours, and a baseline measured only at 0 and 6 hours. This allowed us to specifically capture initial polishing effects and evaluate the impact of repeatedly removing and re-starting parts on the machine.
Data acquisition involved collecting wavefront properties (Peak-to-Valley, RMS) taken with a 4D interferometer. I also performed physical thickness measurements with a micrometer to calculate MRR. All collected data was processed and analyzed using Python.
My second project stemmed from observations of daily operations in the polishing room. I identified inconsistencies and omissions in recorded polishing surface and slurry parameter data, impacting process traceability. Additionally, the main tracking spreadsheet, with four years of daily entries, was slow and cumbersome.
To address this, I developed a Polishing Machine Data Entry Tool. This tool streamlined data input and improved data quality by ensuring mandatory field completion and incorporating data validation checks. It also featured a search function with an Excel preview window, allowing users to query historical data without risking accidental modification. This solution improved data accuracy and completeness and enhanced the efficiency of accessing polishing records.
Note: Due to the nature of this internship I don’t have too many pictures of my work that I can share, but I am allowed to write about my experience.


Keysight Internship
Overview
This summer, I interned at Keysight's Santa Clara facility, working within the Optics Department. My focus was in the continuous glass polishing area, tackling projects aimed at improving process understanding and operational efficiency.
Categories
Optics
Manufacturing
Date
Jun 2024
-
Sep 2024
Title.

My first project characterized our single-sided Chemical-Mechanical Polishing (CMP) machines. The objective was to understand Material Removal Rates (MRR) and track the evolution of surface wavefront using a 4D interferometer.
We used 100 x 70 mm, ~18mm thick glass test pieces, referred to as "Spam Plates," applying ~0.28 PSI pressure with added weight. I designed an experiment using a series of 6-hour polishing runs using three identical parts on different measurement schedules: one with frequent initial measurements (every 30 mins for 2 hrs) transitioning to 2-hour intervals, one measured solely every 2 hours, and a baseline measured only at 0 and 6 hours. This allowed us to specifically capture initial polishing effects and evaluate the impact of repeatedly removing and re-starting parts on the machine.
Data acquisition involved collecting wavefront properties (Peak-to-Valley, RMS) taken with a 4D interferometer. I also performed physical thickness measurements with a micrometer to calculate MRR. All collected data was processed and analyzed using Python.
My second project stemmed from observations of daily operations in the polishing room. I identified inconsistencies and omissions in recorded polishing surface and slurry parameter data, impacting process traceability. Additionally, the main tracking spreadsheet, with four years of daily entries, was slow and cumbersome.
To address this, I developed a Polishing Machine Data Entry Tool. This tool streamlined data input and improved data quality by ensuring mandatory field completion and incorporating data validation checks. It also featured a search function with an Excel preview window, allowing users to query historical data without risking accidental modification. This solution improved data accuracy and completeness and enhanced the efficiency of accessing polishing records.
Note: Due to the nature of this internship I don’t have too many pictures of my work that I can share, but I am allowed to write about my experience.

