Process Engineering Fundamentals – Online Microcredential

Gain in-demand knowledge and advance your career in semiconductors

The semiconductor industry is driving technological innovation across countless applications. Keeping pace with rapidly evolving chips and manufacturing processes requires skilling up alongside advancements in the field.

Meet the growing demand for a workforce skilled in semiconductor process development and evaluation when you earn a microcredential in process engineering fundamentals online from Oregon State University. You'll learn to map out the complex network of processes needed to transform raw materials into functional integrated circuits — preparing you for career advancement in an evolving industry.

This 10-credit microcredential, offered online by Oregon State’s innovative College of Engineering, covers critical engineering principles like mass and energy balances, thermochemistry and statistical analysis of process data. You'll learn how to apply these concepts to optimize inputs, monitor outputs and evaluate the generation or consumption of materials at each step. These quantitative skills will enable you to identify inefficiencies, implement data-driven improvements and ensure manufacturing quality control.

Coursework

Required courses (10 credits)

• CBEE 211 – Material Balances and Stoichiometry (3) and CBEE 212 – Energy Balances (3)
  • or CBEE 280 – Material and Energy Balances (6)*
• CBEE 213 – Process Data Analysis (4)

* In order for CBEE 280 to satisfy these requirements, students must register for this variable-credit course at the full 6 credit hours.

Prerequisite courses

• MTH 252 – Integral Calculus (4)
• MTH 256 – Applied Differential Equations (4)

Skills

The in-demand skills you’ll develop as a student in this microcredential will give you what you need to stand out and level up in your career.

• Material balances set up, performance, and application
• Energy balances set up, performance, and application
• Thermophysical and thermochemical calculations
• Data analysis
• Statistical analysis of process data
• Process engineering