Introduction:
In our production process, workpieces need to dip into a special solution multiple times to achieve a specific thickness. However, the number of dips is temperature, timing, and humidity dependent, making it difficult to achieve high accuracy measurements manually. We needed a solution that would allow us to make real-time high accuracy measurements to ensure the quality of the final product and adjust the dipping action parameters accordingly.

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Problem:
Manually measuring the thickness of the workpieces after dipping them into the special solution was a challenging task due to the variability of the process. It was difficult to maintain consistent accuracy, leading to issues with quality control and production efficiency.

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Solution:
To overcome these challenges, I implemented a solution using two robots, two Keyence optical micrometers, and a heat tunnel. The robots were able to handle the workpieces with precision, while the optical micrometers provided high accuracy measurements. The heat tunnel ensured consistent temperature and humidity conditions during the process. With real-time measurement data, I was able to adjust the dipping action parameters based on the measurements and achieve the desired thickness more consistently.

Results:
The machine allowed us to make real-time high accuracy thickness measurements and adjust the dipping action parameters accordingly, ensuring the quality of the final product. The use of robotics and optical micrometers also improved production efficiency and eliminated the need for manual measurement methods.

Introduction:

This manufacturing process require to move many workpieces from one solution to the next, with each workpiece staying in different solutions for different periods. The process was originally handled by operators, but it was very slow, ineffective, and easy for them to make mistakes. I was asked to provide a solution that would improve the production rate and reduce the risk of mistakes.

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Problem:

Manually moving the workpieces from one solution to the next was a slow and inefficient process. It was difficult for operators to keep up with the production rate and there was a high risk of mistakes being made.

Solution:

To overcome these challenges, I implemented a solution using a gantry robot. I optimized the sequence to significantly increase the production rate and reduce the risk of mistakes. The gantry robot was able to move the workpieces from one solution to the next with precision and speed, improving the efficiency of the process.

Results:

The solution I implemented was a huge success. The use of the gantry robot significantly increased the production rate and reduced the risk of mistakes. It allowed me to meet my production goals more efficiently and effectively.

Introduction:

The team needed a solution to efficiently schedule the arrangement of thousands of boxes and fixtures daily, while also integrating with a Nikon X-ray machine for 3D scanning of dental impressions. The goal was to minimize downtime for the X-ray machine.

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Problem:

Manually scheduling the arrangement of boxes and fixtures was a time-consuming and error-prone process. It was also difficult to integrate with the Nikon X-ray machine for 3D scanning, leading to frequent downtime for the machine.

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Solution:

To overcome these challenges, I developed a customized machine that uses a conveyor system and robot to streamline the scheduling process. The machine is able to work in conjunction with the Nikon X-ray machine to scan and arrange dental impressions for 3D scanning, minimizing downtime for the machine.

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Results:

The customized machine has been a great success. It has significantly improved the efficiency and accuracy of the scheduling process, while also minimizing downtime for the Nikon X-ray machine.

Introduction:

Ultra-thin wires need to be connected to circuit boards using pins, but the process is challenging because the surface coating needs to be removed during the process. Previously, this was a manual process and the quality of the connection depended on the operator's skill and consistency. This led to issues with quality, speed, and a high rejection rate.

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Problem:

The manual process of connecting ultra-thin wires to circuit boards using pins was prone to errors and inconsistency, resulting in a high rejection rate and reduced efficiency. The quality of the connection depended on the operator's skill and attention to detail, which was difficult to maintain consistently.

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Solution:

To address these issues, I created a machine that used precise pressure to make consistent pressing results. The machine was designed to handle the ultra-thin wires and circuit boards with care, ensuring a high-quality connection every time. The machine was also able to work faster than a manual process, improving efficiency and reducing the rejection rate.

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Results:

The precision pressing machine was a huge success. It improved the quality of the ultra-thin wire connections, increased the speed of the process, and significantly reduced the rejection rate. In addition, it eliminated the need for skilled operators, making the process more reliable and consistent.

Client: Dr. Marlow, Princeton University

Project Objective: Develop an algorithm to calculate the distance between the Earth and the Moon rapidly and accurately.

Role: Algorithm Developer/Python Programmer

I developed an algorithm using Python, a high-level and versatile programming language ideal for such a task due to its extensive scientific libraries and ease of use. The algorithm was designed to rapidly calculate the Earth-Moon distance, utilizing available astronomical data and leveraging the computing power of Python for quick computations.

Outcome:

The developed algorithm significantly expedited the calculation process for the Earth-Moon distance. It not only reduced the time needed for such computations but also improved the accuracy of the results by eliminating manual data processing errors.

The success of this project demonstrated the effective application of Python programming in the field of astronomical computations, providing an excellent example of how modern programming can support advanced scientific research.

Project Objective: Create a SolidWorks macro to replace part information in thousands of assembly files while preserving the linkages between these files.

Role: SolidWorks Macro Developer

Problem:

The client, a large manufacturing company, was facing challenges managing their SolidWorks assembly files. They had thousands of parts within hundreds of assembly files, each needing regular updates. These updates were originally done manually, consuming valuable time and resources, while also introducing potential for human error. A significant challenge in this task was preserving the relationships between parts in the assembly, which were necessary for the correct functioning and representation of the assembly.

Solution:

The solution was to create a SolidWorks macro that would automate the task of replacing parts information across multiple assembly files. This macro would not only speed up the process but also eliminate human errors, thereby enhancing productivity and accuracy. 

Implementation:

I developed a custom macro utilizing SolidWorks API (Application Programming Interface) to automate the process. The macro was designed to parse through the assembly files, identify the part information that needed to be replaced, make the necessary changes, and save the updated assembly file, all while maintaining the links between parts in the assembly.

Outcome:

The implementation of the SolidWorks macro significantly streamlined the client's process of updating part information in assembly files. It resulted in a substantial time saving - a task that used to take several weeks could now be completed in a matter of hours. Additionally, the macro eliminated manual errors, ensuring a high degree of accuracy in the updated assembly files.

Client: Dr. Gayah, Penn State University

Project Objective: To develop a JavaScript program tailored to the client's specific needs.

Role: Programmer

Problem:

Dr. Gayah needed a custom JavaScript program for a particular project at Penn State University. The existing software solutions were either too generic or didn't meet the specific requirements for the task.

Solution:

Drawing on my programming skills, I proposed to develop a tailored JavaScript program that would meet Dr. Gayah's specific needs. JavaScript was chosen due to its versatility, compatibility across different platforms, and widespread usage.

Implementation:

The JavaScript program was designed to be intuitive and user-friendly while accomplishing the desired functions effectively. To ensure optimal performance, the program was written using efficient coding techniques and practices.

Throughout the development process, continuous testing was performed to identify and rectify any bugs or issues promptly. This iterative approach helped to ensure that the final product was reliable and met the specified requirements.

The program was also documented thoroughly, providing Dr. Gayah and his team with a clear understanding of how to use it and how it worked, facilitating easy maintenance and potential future modifications.

Outcome:

The custom JavaScript program was successfully developed and delivered to Dr. Gayah. It met the specific requirements set out at the project's inception, improving the efficiency of Dr. Gayah's work.

The success of this project underscored the power of custom software solutions in meeting specific needs that cannot be adequately addressed by off-the-shelf software. This project demonstrated my ability to effectively use JavaScript to deliver custom solutions tailored to specific needs and contexts.

Client: Anonymous

Project Objective: Develop an algorithm to improve the accuracy and response time of a glucose sensor.

Role: Algorithm Developer

Problem:

The client had a glucose sensor that was not providing readings as accurately and quickly as needed. This posed challenges in real-time glucose monitoring, which was crucial for managing and treating diabetes in patients.

Solution:

I proposed to develop an algorithm that would improve the sensor's data processing, ultimately enhancing its accuracy and response time. This algorithm was to be designed to handle the sensor's data more efficiently and provide precise glucose readings more quickly.

Implementation:

Leveraging my expertise in algorithm development, I created an algorithm tailored to the specific requirements of the glucose sensor. The algorithm was designed to process the sensor data, filter out noise, and deliver accurate glucose readings in real time.