Semiconductor, Manufacturing, and Industrial (SEMI) Engineering M.Eng. Pathway

As the worldwide need for efficient, resilient manufacturing systems is growing rapidly, so is the demand for skilled engineers to develop these systems. The Cornell Systems Engineering program has developed the Semiconductor, Manufacturing, and Industrial Engineering (SEMI) pathway to meet this need.
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Program Details

The Semiconductor, Manufacturing, and Industrial (SEMI) Engineering pathway is focused on learning for careers in semiconductor, manufacturing, and industrial systems engineering. The SEMI pathway covers the latest approaches in operation, control, planning, and optimization. This pathway prepares students for successful careers in both Industry 4.0 and Industry 5.0 areas with opportunities to explore the modern incorporation of cyber-physical systems IoT, data analytics, AI, robotics, digital twins, as well as sustainability and sociotechnical systems, into semiconductor, manufacturing, and industrial engineering applications.

The pathway provides course options as electives in the Systems Engineering M.Eng. program. Students can choose any combination of pathway courses as long as they meet the Systems Engineering M.Eng. program overall course credit and curriculum requirements.

Curriculum

Systems Engineering Core Courses

  • SYSEN5100 Model Based Systems Engineering (4) or SYSEN 5151 Foundation Systems Engineering (4)
  • SYSEN5200 Systems Analysis Behavior and Optimization (3)
  • SYSEN5930 or CEE6910 Project Management and Leadership for Complex Systems or Principles of Project Leadership (4)
  • SYSEN5900 MEng Project (6-8)

Additional Core Courses for Distance Learning Students

  • SYSEN5920 Systems Engineering Management for Virtual Teams (1)
  • SYSEN5940 Creativity and Innovation within Systems Engineering (1)

Elective Course Focus Areas

  • Manufacturing Focus

    • Systems Integration, Verification, and Validation
    • Systems Engineering and Six Sigma for the Design & Operation of Reliable Systems
    • Theory and Practice of Systems Architecture
    • Design of Manufacturing Systems
    • Energy Efficiency in the Circular Economy
    • Industrial Blockchain Systems and Applications

  • Controls Focus

    • Feedback Control Systems
    • Optimal Control and Decision Theory
    • Multivariable Control Theory
    • Model Based Estimation
    • Adaptive and Learning Systems

  • Big Data/Machine Learning Focus

    • Computational Optimization
    • Industrial Big Data & Machine Learning
    • Data Analytics
    • Deep Learning

  • Manufacturing and Semiconductor Applications Focus

    • Cyber-Physical Systems
    • Creating Solutions with Embedded Systems
    • Internet of Things System Design Fundamentals
    • Introduction to Robotics
    • Digital Twins and Model-Based Systems Engineering

  • Semiconductor Design Focus

    • Nanofabrication and Characterization of Electronics
    • Thin Film Material Science
    • Materials Design and Processing for Industry
    • Analytical Techniques for Material Science

The M.Eng. Programs