Quality Control and Precision Measurement Lab

Quality Control and Precision Measurement Lab

Overview:

• This laboratory focuses on the teaching and research of applying quality concepts and techniques. The goal is to use the principles and technologies of quality in industries such as electronics, optoelectronics, semiconductors, automobiles, and service industries to improve and enhance the quality of products and processes. The main techniques used are statistical methods, measurement system analysis, control charts, design of experiments, and machine learning methods.

Research Field

• 1. Application of Machine Learning and Data Mining Techniques in Process Control.
• 2. Intelligent Process Management Systems.
• 3. Development of Real-time Control Systems for Processes.
• 4. Construction and Design of High-Yield Process Control Systems.
• 5. Design of Univariate/Multivariate Control Charts.
• 6. Application of Six Sigma in Enterprise Process Improvement.

Research Accomplishments

• 1.Construction of Quality Anomaly Diagnosis System using Deep Learning Techniques.
• 2. Research on the Application of Machine Learning Techniques in Real-time Monitoring of Processes.
• 3. Research on the Application of Statistical Quality Control Methods in Process Improvement.
• 4. Identification of Multivariate Process Anomaly Sources.

Instructional Software

• > Minitab, SAS, MATLAB, PYTHON, SigmaPlot, Statistica, JMP, SPSS.

Industry Corporation

• 1. Establishing a classification model for textile defects using deep learning algorithms and transfer learning.
• 2. Classifying defects in printed circuit board circuits using deep learning algorithms and transfer learning.
• 3. Improving the yield of printed circuit boards/IC carrier plate processes using statistical quality control methods.
• 4. Improving the performance of injection molding and cleaning processes for hard disk components using Six Sigma quality management.

Professor