Intern- F10 Manufacturing Engineer

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. Project Title Diffusion Capacity Optimization Through Constraint Workstation Improvement Project Description This internship provides an opportunity to work on projects focused on improving capacity and operational efficiency within the Diffusion manufacturing area. The intern will analyze manufacturing data, evaluate workstation performance, investigate recurring production constraints, and develop recommendations to improve equipment utilization, manufacturing throughput, and cycle time performance. The project will provide exposure to manufacturing engineering methodologies, capacity management, statistical analysis, and cross-functional collaboration within a semiconductor manufacturing environment. Objective of the Project • Analyze Diffusion manufacturing performance and capacity utilization. • Identify workstation constraints that impact throughput and cycle time performance. • Investigate key sources of capacity loss and evaluate improvement opportunities. • Develop data-driven recommendations to improve operational efficiency and manufacturing performance. Opportunities for Full Time Employment Successful interns who demonstrate strong analytical capability, technical aptitude, and collaboration skills may be considered for future internship extensions, graduate opportunities, or full time employment opportunities, subject to business requirements. Project Scope • Analyze manufacturing, equipment, and capacity performance data within the Diffusion area. • Identify bottlenecks and investigate factors contributing to capacity losses, such as equipment downtime, process holds, maintenance-related events, and product mix constraints. • Apply engineering and analytical methodologies including Pareto analysis, Statistical Process Control (SPC), root cause analysis, and capacity modelling. • Collaborate with Process Engineering, Equipment Engineering, Manufacturing, and Industrial Engineering teams to evaluate improvement opportunities. • Where appropriate, utilize AI-enabled analytics tools to support data analysis and engineering decision-making. Learning Opportunities • Gain exposure to semiconductor Diffusion processes and manufacturing operations. • Learn how manufacturing engineers manage capacity, cycle time, and equipment performance. • Develop practical skills in data analysis, statistical methodologies, and problem solving. • Gain experience working with cross-functional engineering teams to evaluate manufacturing challenges. • Build technical communication and presentation skills through project reviews and stakeholder engagement. Deliverables • Capacity performance assessment of the Diffusion manufacturing area. • Engineering analysis of workstation constraints and capacity losses. • Evaluation of improvement opportunities and recommended actions. • Technical report documenting findings, analyses, and recommendations. • Final project presentation summarizing key learnings and project outcomes. Impact of the Project • Improve understanding of capacity constraints and manufacturing losses within the Diffusion area. • Provide data-driven insights that support capacity and operational improvement initiatives. • Identify opportunities to improve equipment utilization, throughput, and cycle time performance. • Support continuous improvement efforts within manufacturing operations. Skillsets Required • Strong analytical and problem-solving skills. • Fundamental understanding of manufacturing or engineering systems. • Familiarity with statistical analysis and data interpretation. • Familiarity with Excel, JMP, Python, SQL, Power BI, or similar analytical tools is advantageous. • Knowledge of Statistical Process Control (SPC), Lean Manufacturing, Root Cause Analysis, or AI-enabled analytics tools is advantageous. • Strong communication and teamwork skills. Course of Interest The ideal candidate should be pursuing a degree in Chemical Engineering, Mechanical Engineering, Electrical Engineering, Industrial and Systems Engineering, Manufacturing Engineering, Materials Science and Engineering, Semiconductor Engineering, or a related engineering discipline. Duration of Period The ideal candidate should be able to commit to a full time internship period of 5 months from Jan to May 2027. 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 in…