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Intern - Mfg Diffusion

3 weeks ago

Singapore Micron Full time

**Our vision is to transform how the world uses information to enrich life for all.**

Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

JR39378 INTERN - MFG DIFFUSION

**About Us**:
Micron Technology's vision is to transform how the world uses information to enrich life. It is our mission to be a global leader in memory and storage solution We have five meaningful values: People, Innovation, Tenacity, Collaboration and Customer Focus. We conduct business with Integrity, accountability and professionalism while supporting our global community. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We recruit, hire, train, promote, discipline and provide other conditions of employment without regard to a person's race, color, religion, sex, age, national origin, disability, sexual orientation, gender identity and expression, pregnancy, veteran's status, or other classifications protected under law. This includes providing reasonable accommodation for team members' disabilities or religious beliefs and practices.

**Location**:
1 North Coast Drive, Singapore

**Department**:
F10N Manufacturing Diffusion

**Project Title**:
Development of Robotic Process Automation (RPA) and machine learning models to identify post processed wafer defects signatures and trigger automated reaction mechanism.

**Description**:
The production of Semiconductor chips is a multi-step process, between several processes, dedicated machines were used scan the wafers to ensure the wafers are clean before moving on to the next process. Although the production of semiconductor wafers takes place in a cleanroom, it is common to find residual particles littered across the wafer surface after being processed. This is likely caused by chemical reactions between different chemicals during processing. These particles could cause potential yield lost or even scaping entire wafer if left unchecked. Through several trails and tests, different cleaning recipes were created and implemented to purge out residual particles in the tool before processing the next batch of wafers. These cleaning recipes are created with different combination of gas flows and temperatures. Different patterns of particle issue may be a result of underlying issues within the tool. For example, streak patterns may signify issues with the specific injectors or gas regulators, randomly scattered particles may signify that the tool is saturated with residual particles. Currently, such defect patterns could only be accurately classified by a pair of trained human eyes and reaction to such defects are also manually triggered.

Through this internship, the project strives to use machine learning model to identify the types of defect pattern expeditiously and also to develop a RPA workflow to automatically trigger appropriate reaction mechanism to rectify the particle issues. This greatly reduces the time and manpower needed thus reducing cost.

**Aim of the project**:
Utilize machine learning models to identify, classify and recognize wafer defect patterns and automate appropriate reaction mechanism process with the aid of Robotic Process Automation (RPA) software

**Scope**:

- Data mining of wafer maps and other relevant information from different data source
- Collaborate with workstation owners to create and optimize reaction mechanism for particle issues
- Using python programming language to perform image classification and recognition of wafer maps
- Using RPA software to automate reaction mechanism
- Using tableau to create a dashboard that includes relevant charts and information vital for decision making

**Learning Opportunities**:

- Good understanding of the overview of semiconductor manufacturing industry
- Understand day to day operations as an equipment shift engineer
- Understand diffusion process in semiconductor manufacturing
- Understand equipment used in manufacturing of semiconductor chips
- Implementation of RPA across different platforms
- Understand how to implement machine learning techniques to classify and recognize wafer images
- Learn how to retrieve data from different databases and perform data mining across various platforms
- Utilize tableau to organize charts and information to aid in decision making
- Collaborate with different departments

**Deliverable**:

- A dashboard that displays all relevant charts and information
- Semi-automate decision making process

**Skillset Require**:

- Python (jup