Intern- PCS Enterprise Metric Hub

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Project Details

Project Title: PCS Enterprise Metrics Hub Intern

Location: Singapore

Department: Process Control Systems Engineering

Project Description

This internship project focuses on developing the foundational elements of a centralized Enterprise Metrics Hub that consolidates process control and operational health metrics into a unified reporting framework. The project provides opportunities to explore enterprise reporting requirements, data modeling concepts, and dashboard development using Power BI.

Objective of the Project

Develop a foundational reporting framework for the Enterprise Metrics Hub by defining key performance indicators, evaluating reporting sources, designing a common data model, and developing an initial dashboard prototype.

Project Scope

• Collaborate with stakeholders across engineering organizations to understand reporting requirements and business objectives related to process control metrics.
• Develop a KPI Dictionary documenting metric definitions, ownership, calculation methodologies, reporting cadence, and business relevance.
• Evaluate reporting assets across approved platforms and establish a structured inventory of available data sources.
• Design a common enterprise data model that enables integration of multiple reporting sources into a unified analytics framework.
• Develop prototype dashboards that visualize Process Control Readiness, Defense Line Effectiveness, and Excursion Health metrics using Power BI.

Learning Opportunities

• Gain exposure to semiconductor process control methodologies and operational performance measurement concepts.
• Learn enterprise data modeling and reporting architecture practices used within manufacturing environments.
• Develop Power BI dashboard design and data visualization skills.
• Learn approaches for stakeholder engagement, requirements gathering, and technical documentation.
• Explore data governance concepts including metric standardization and ownership.
• Apply AI-enabled tools and Generative AI techniques to improve productivity, documentation quality, and analytical workflows.

Deliverables

• KPI Dictionary and Data Source Inventory.
• Enterprise Data Model Design.
• Enterprise Metrics Hub Dashboard Prototype.
• Project Findings and Recommendation Summary.

Impact of Project

This project will improve understanding of how process control metrics can be standardized and visualized within a common reporting framework. The work will provide a foundation for future analytics enhancements and contribute to more consistent reporting practices across engineering organizations.

Skillsets Required

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

Course of Interest

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

Duration of Period

The ideal candidate should be able to commit to an internship period of at least 4 months.