Micron Folsom · Singapore
Hardware & Electrical
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Project Title
Intelligent Equipment Health Monitoring and Reliability Analytics Using Artificial Intelligence
Project Description
This project provides the intern with practical exposure to manufacturing equipment reliability, data analytics, machine learning, Artificial Intelligence, and engineering visualization.
The intern will develop a prototype that analyzes equipment alarms, downtime, maintenance, and performance data to identify equipment health trends and emerging reliability concerns. The intern will also explore AI-Enabled and natural language capabilities for communicating analytical insights to engineering stakeholders.
Objective of the Project
The objective is to develop an AI-Enabled equipment health analytics framework that:
Monitors equipment health and reliability trends.
Detects abnormal equipment behavior and emerging concerns.
Identifies when performance degradation began.
Highlights the main factors associated with degradation.
Communicates findings through dashboards and analytical summaries
Opportunities for Full Time Employment
Consideration for future internship or full-time employment opportunities will be subject to business needs, position availability, and the applicable selection process.
Project Scope
The intern will be given the opportunity to:
Analyze equipment alarm history, downtime records, maintenance activities, and operational performance data.
Develop equipment health indicators and monitoring methodologies to evaluate reliability trends.
Apply statistical and machine learning techniques to identify abnormal equipment behavior and emerging reliability concerns.
Develop an Intelligent Equipment Health Monitoring Agent and interactive dashboard to communicate trends and key contributors.
Document and present the methodology, findings, limitations, and recommendations to engineering stakeholders.
Learning Opportunities
The intern will have the opportunity to:
Gain practical experience in manufacturing data analytics and equipment reliability engineering.
Apply data preparation, trend analysis, anomaly detection, and machine learning techniques.
Learn to develop equipment health indicators and evaluate their effectiveness.
Explore AI-Enabled Agents and natural language capabilities for engineering analytics.
Strengthen technical documentation, visualization, problem-solving, and presentation skills.
Deliverables
The intern is expected to deliver:
A prototype of an Intelligent Equipment Health Monitoring Agent.
A documented equipment health scoring methodology and set of reliability indicators.
Automated models for detecting alarm spikes, downtime excursions, and equipment health degradation.
An interactive dashboard showing equipment health trends, abnormal trend start points, and key contributors.
A final technical report and presentation covering findings, limitations, recommendations, and future opportunities.
Impact of the Project
The project is intended to:
Improve visibility into equipment health and reliability trends.
Enable faster identification of potential contributors to downtime and alarm excursions.
Improve early detection of emerging equipment reliability concerns.
Provide data-driven insights for proactive reliability improvement.
Establish a scalable AI-Enabled analytics framework for future development.
Skillsets Required
The ideal candidate should possess:
Programming knowledge in Python, Structured Query Language, or equivalent analytical tools.
Understanding of data analytics, statistics, trend analysis, and data visualization.
Familiarity with machine learning, Artificial Intelligence, anomaly detection, or data science concepts.
Familiarity with AI tools, AI-Enabled workflows, Generative AI, or Agent-based analytics.
Strong analytical, problem-solving, technical communication, and documentation skills.
Course of Interest
The ideal candidate should be pursuing a degree in Data Analytics, Data Science, Computer Science, Mechanical Engineering, Electrical Engineering, Industrial Engineering, or a related field.
Duration of Period
The ideal candidate should be able to commit to a full time internship period of at least 5 months.
About Micron Technology, Inc.
We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.
To learn more, please visit micron.com/careers
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
To request assistance with the application process and/or for reasonable accommodations, please contact hrsupport_sg@micron.com
Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.
Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.
AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.
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