Experiment Protocol Process

        Administrative
            Protocal Name
            Protocol ID Number
            Version History
			
        Background
            Description of the Process
            Motivations
                Instructions from Management
                Voice of the Customer (VOC)
            References to Process Information
                Calibration to establish accuracy
                GR&R study to demonstrate measurement reliability
                First Principles
                Process documentation, SOPs
                DFMEA & PFMEA
                SPC records
                Process capability studies
                Corrective Actions
            Problem to be Solved
            Review of Previous Investigations
			
        Experiment Design
            Input-Process-Output (IPO) Diagram
                Response(s)
                    CTQs
                    KPOVs
                    Ordinary POVs
                Factors
                    Controlled
                    Uncontrolled
                        Can't be measured
                        Can be measured
                    Type
                    Qualitative
                        Fixed Levels
                        Random Levels
                    Quantitative
					
            Chosen Design
                Design Family
                    Low resolution designs, e.g. screening experiments for many PIVs
                    Intermediate resolution designs, e.g. two-level factorials and fractional factorials
                    High resolution designs, e.g. response surface designs
                Variables Matrix
                Design Matrix
                Alternative Designs Considered
                Sample Size Calculation
                    Using the intended analysis/model
                    Standard deviation estimate
                    Effect size estimate and power
                Randomization Plan
                    Validate by analyzing the run order as the response
                Blocking Plan
                Create the data collection worksheets
                    Run number
                    KPIVs
                    CTQs
                    Covariates
                    Notes/comments
                Validate the design by analyzing a fictional response
				
        Experiment Procedure
            Personel required
            Equipment and hardware required
            Material required
            Safety plan
            Plan for managing interruption to production process
            Experimental procedure
            Data recording process
            Contingency Plan
            Review
                Management Review
                Technical Review
                Customer/Process Owner Review
                Institutional Review Board (IRB)
                Animal Review Board (ARB)
				
        Statistical Analysis
            Software to be used and version number
            Analysis Method
                ANOVA/Regression
                Regression
                Binary Logistic Regression
                Poisson Regression
                Regression with Life Data
                Other
            Models
                Full Model
                Post-Occam Model
                Alternative Models
                Tests of Assumptions
                    Requirements of Residuals
                        Homoscedasticity
                        Normality
                        Freedom from Outliers
                    Goodness of Fit
                    Contingencies
                Model Acceptance Criteria
                Contingency Model
            Model Confirmation Study
                Design of
                Analysis of
                Acceptance Criteria
            Model Application
                Maximize
                Minimize
                Hit target value
                Simultaneous requirements on CTQs
                Reduce process variation
                Robust design
				
        Cost Analysis
            Cost of the experiment
                Adminstrative cost
                Cost per cell of the experiment design matrix
                Cost per replicate observation
                Cost of analysis and interpretation
                Cost to implement the recommended actions
            Risks of not doing the experiment
			
        Experiment Report Format
            Administrative Information
            Findings (abstract or executive summary)
            Introduction
                Background information
                Goal
            Experiment Design
                Variables matrix
                Design Matrix
                Sample size, randomization, and blocking plan
                Alternative designs considered
            Experiment Administration
                Experiment Procedure
                Experimental Data
                Deviations from Protocol
            Analysis
                Software and Version Number
                Graphical analysis
                Statistical analysis
                    Full Model
                    Post-Occam Model
                    Assumption Checks
                        Normality
                        Homoscedasticity
                        Goodness of Fit
                    Contingency analysis
                Interpretation  of the model
                Evaluation against decision criteria
            Discussion
                Success or failure of the experiment
                Consequences of deviations from protocol
                Recommendations for future experiments