Control of Manufacturing Processes (SMA 6303) Overview and Key Techniques

Overview of Process Control Fundamentals Course

This course covers the essential concepts behind manufacturing process variation and strategies for maintaining control over production quality. It emphasizes the importance of identifying sources of variation and applying statistical techniques to analyze and reduce these inconsistencies.

Key topics include probability models that represent manufacturing processes, methods for sampling and parameter estimation, and various approaches to statistical process control (SPC). These approaches range from foundational Shewhart control charts to more advanced multivariate SPC techniques.

Yield optimization and process capability analysis are integral parts of the material. The course also delves into experimental design, featuring full factorial and fractional factorial methods, response surface modeling, and sequential experimentation to enhance process robustness.

Practical applications are highlighted through multiple case studies, such as chemical vapor deposition process design and control of cycle-to-cycle variations. These examples demonstrate how modeling and real-time adjustments can improve manufacturing outcomes.

A structured sequence of 22 lecture videos breaks down these topics systematically, offering in-depth coverage that supports both theoretical understanding and practical application. The lectures serve as a valuable resource for professionals engaged in manufacturing automation, including those working with legacy or advanced control systems.

The principles taught remain relevant despite advancements in automation technology. Consistent production depends on stable systems, accurate measurements, and reliable feedback mechanisms. As such, these fundamentals assist engineers and technicians in making informed decisions for process optimization.

Those interested can access comprehensive lecture materials and videos on the control of manufacturing processes to deepen their knowledge of process variation and improvement techniques.

Their Free Course below:

https://ocw.mit.edu/courses/2-830j-control-of-manufacturing-processes-sma-6303-spring-2008/video_galleries/lecture-videos/

The full course includes 22 lecture videos, each focusing on a key area of process control:

• Introduction — Processes and Variation Framework

• Semiconductor Process Variation

• Mechanical Process Variation

• Probability Models of Manufacturing Processes

• Probability Models, Parameter Estimation, and Sampling

• Sampling Distributions and Statistical Hypotheses

• Shewhart SPC and Process Capability

• Process Capability and Alternative SPC Methods

• Advanced and Multivariate SPC

• Yield Modeling

• Introduction to Analysis of Variance

• Full Factorial Models

• Modeling Testing and Fractional Factorial Models

• Aliasing and Higher Order Models

• Response Surface Modeling and Process Optimization

• Process Robustness

• Nested Variance Components

• Sequential Experimentation

• Case Study 1: Tungsten CVD DOE/RSM

• Case Study 2: Cycle-to-Cycle Control

• Case Study 3: Spatial Modeling

• Case Study 4: Modeling the Embossing/Imprinting of Thermoplastic Layers