Intern, PDE PCS

Project Title

PCS Enterprise Metrics Hub Intern

Location

Singapore

Department

Process Control Systems Engineering

Overview

Join an inclusive team passionate about one thing: using 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.

Project Description

The internship project focuses on developing a centralized Power BI-based Enterprise Metrics Hub that serves as a single source of truth for process control health, readiness, effectiveness, productivity, and Artificial Intelligence adoption metrics. The solution will consolidate data and reporting currently distributed across multiple platforms into an integrated analytics portal, improving visibility of key performance indicators and enabling data-driven decision making.

Through this project, the intern will gain hands-on experience in semiconductor manufacturing analytics, enterprise data integration, business intelligence development, and Artificial Intelligence-enabled insights generation. The internship is designed as a structured project with defined deliverables and learning objectives, and is not intended for operational or routine production activities.

Project Scope

• Collaborate with stakeholders from Process Control Systems, Manufacturing Research and Data Analytics, Quality, and Process Engineering to understand reporting requirements and business objectives.
• Develop a KPI Dictionary documenting metric definitions, ownership, calculation methodologies, reporting cadence, and business value.
• Design and implement an enterprise data model integrating information from SharePoint, Excel, Power BI, Spotfire, and other approved reporting platforms.
• Develop interactive Power BI dashboards with automated refresh, drill-down capabilities, and standardized reporting views.
• Create dashboards covering:
  • Process Control Readiness
  • Defense Line Effectiveness
  • Excursion Health and Closure Tracking
  • Productivity and Automation Impact
  • Artificial Intelligence and Copilot Adoption
• Evaluate opportunities to apply analytics and Artificial Intelligence techniques to identify trends, risks, and improvement opportunities.
• Explore methods for generating automated executive summaries and actionable business insights.

Learning Opportunities

• Semiconductor Process Control concepts and methodologies
• Statistical Process Control fundamentals
• Fault Detection and Classification fundamentals
• Enterprise Data Engineering and ETL concepts
• Business Intelligence and Power BI dashboard development
• Data modeling and data visualization best practices
• Artificial Intelligence and analytics applications
• Stakeholder engagement and project management
• Executive reporting and data-driven decision making

Deliverables

• KPI Dictionary documenting key business metrics
• Enterprise Data Model integrating multiple reporting sources
• PCS Enterprise Metrics Hub Power BI Portal
• Executive and operational dashboard suite
• User Guide and Knowledge Transfer Documentation
• Final project presentation summarizing project outcomes, insights, and recommendations

Success Criteria

• Key process control and operational health metrics are consolidated into a centralized reporting platform.
• Multiple enterprise data sources are integrated into a common data model.
• Executive and operational dashboards are deployed and adopted by stakeholders.
• Manual reporting effort is reduced through automation and standardization.
• Business users can access consistent and actionable metrics through a single reporting experience.

Skillsets Required

• Familiarity with Power BI, SQL, Python, or equivalent analytics tools
• Understanding of data analysis, data visualization, and reporting concepts
• Strong analytical and problem-solving skills
• Effective verbal and written communication skills
• Ability to work independently on a structured project with defined milestones
• Proficiency in applying Artificial Intelligence tools and AI-enabled workflows for data analysis and productivity improvement

Course of Interest

The ideal candidate should be pursuing a degree in Computer Science, Data Science, Software Engineering, Artificial Intelligence, Information Systems, Analytics, or a related engineering discipline.

Duration of Period

The ideal candidate should be able to commit to a full-time internship period of at least 4 months.

Impact of Project

This project provides the opportunity to develop a high-visibility enterprise analytics solution used by engineering and leadership teams. The project delivers practical experience in semiconductor manufacturing, business intelligence, enterprise data integration, and Artificial Intelligence applications while creating a sustainable reporting framework for future business use.

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.