DOE design of experiments plays a very important role in the entire quality control process. It is an important guarantee for product quality improvement and process improvement. By studying this course, you will, through quantitative analysis of product quality and process parameters, understand how to find key factors and control related factors. According to actual needs, learn to distinguish and select different types of experimental designs, design your experimental steps, discover how to control various influencing factors, and obtain greater benefits with less investment, thereby improving product quality and production efficiency.

• Master the methods, principles and applications of experimental design
• Learn to use response surface design to determine the optimal parameter range
• Initially master the application of Minitab in DOE

• Personnel who need to understand and apply experimental design, metrology management personnel, engineering technical personnel, product design engineers, process design engineers, quality engineers, reliability engineers, etc.

• Introduction to experimental design
• Purpose and types of experimental design
• Introduction to basic terminology of experimental design
• Statistical knowledge preparation
• Basic statistics
• Basic concepts of deviation
• Hypothesis testing
• Analysis of variance
• Correlation analysis
• Regression analysis
• Single-factor experiment
• Single-factor analysis of variance
• Polynomial regression
• Full factorial experiment
• Composition of full factorial experiments
• Characteristics of full factorial experiments
• Minitab generating full factorial experiments
• Experimental design process: seven-step process of defining the project, identifying responses, establishing baseline levels, determining experimental constraints, identifying factors and determining factor levels, selecting experimental design type, randomizing runs, collecting data, and analyzing data
• Fractional factorial experiment
• Generation of fractional factorial experiments
• Confounding in fractional factorial experiments
• Analysis of fractional factorial experiments
• Case analysis
• Factorial experiments with center points
• Response surface
• Composition of central composite experiments
• Analysis of central composite experiments
• Case analysis