Data analysis and simulation techniques to optimize manufacturing throughput and quality.
Course overview
In this course you will learn how to use data and simulation to improve manufacturing efficiency. You will study techniques for analyzing production data, identifying bottlenecks, and testing changes in a virtual environment before implementing them on the shop floor. The course focuses on practical applications that help increase throughput and maintain quality standards.
Prerequisites for this course include Lean Manufacturing and Robotics Fundamentals. You should be comfortable with basic statistics and have an understanding of automated systems. The course is designed for students who want to deepen their knowledge of production optimization.
Who takes this course
This course is an elective for the Mechanical Engineering Technology program. It is also open to students in Manufacturing Engineering Technician and Bachelor of Applied Technology — Advanced Manufacturing who have completed their prerequisites.
Credits: 3 · Hours: 45
Prerequisites
- MFGT 3260 Lean Manufacturing
- MFGT 2650 Robotics Fundamentals
Learning outcomes
- Apply statistical methods to identify bottlenecks in production lines
- Build and validate discrete-event simulation models for manufacturing systems
- Analyze quality control data to recommend process improvements
- Evaluate the cost-benefit of proposed optimization strategies
- Present technical findings to stakeholders using clear visualizations
Evaluation
| Component | Weight (%) |
| Simulation projects | 40 |
| Midterm examination | 25 |
| Case study analysis | 20 |
| Final examination | 15 |