1  Num Factors: You can analyze up to 15 factors in this software.  
2  Design Type:
Specify the type of design you want to create. The following options are available:
 
3  Factors: Specify the details of your design in this frame. The number of factors you selected will display the input rows in this frame.  
4  Variable Name: Specify a name for each of your variables. Make sure the names are unique and don't involve special characters.  
5  Variable Type:
Specify the type of factor. The available options are:
 
6  Levels: Specify the number of levels for each factor. We can only have two levels for 2level factorial designs such as full factorial, fractional factorial, response surface, and PlackettBurman designs. However, for a general factorial, we can have up to 10 levels for each factor.  
7a  Low Level: Specify the low level for each factor. If you specify numeric type, then all levels must be numeric.  
7b  High Level: Specify the high level for each factor. If you specify text type, the levels could be numeric or text. No interpolation is made between these values, even if you specify numeric levels.  
8  Flowchart: Click on this button to view the flowchart for the Design of Experiments.  
9  Help Button: Click on this button to open the help file for this topic.  
10  Cancel Button: Click on this button to cancel all changes to the settings and exit this dialog box.  
11  Create Design: If this is your first time using this template, click this button to format the worksheet template. You can also update the worksheet format any time, but remember that you may lose any data entered on this worksheet. Once you are happy with the worksheet template layout, you must enter any required data on the worksheet. When the data entered into the worksheet is complete, you can click on Analysis Setup and then Compute Outputs to generate analysis results.  
12  Analyze Design: Click on this button to save all changes and compute the outputs for this analysis. Review the results of your analysis and make changes to your inputs if required to update analysis results. 
1  Create Design: Select this radio button to create a design using the settings given below. 
2  Center Points: Specify the number of center points you want to add to your model. If you specify "None," then no center points are added, and only a linear model is developed. For Response surface designs, select the number of center points to "Auto" for the system to automatically determine the required number. However, you can change this number based on your needs. Center points can help you check for model linearity and increase the power of your designed experiments. 
3  Replicates: It is a good idea to replicate the design so that you can estimate the experimental error. Replication helps you improve the power of your experimental design and calculate the P values for each term so that you can determine model significance. Increasing the number of replicates comes with the cost of having to perform a greater number of tests, which can add to the time and cost required for performing the designed experiment. 
4  Randomize Runs: Specify if you want to randomize your runs. The purpose of randomization is to handle unknown noise factors. It is recommended that you always randomize your runs. 
5  Design Generators: For Fractional factorial designs, you can specify a design generator. If you leave this field blank, the software will automatically pick a design generator. However, if you want a specific type of confounding, you can specify your design generator. An example is D = ABC. Here, column D is assigned to the product of A, B, and C factors. 
6  Axial Points: The axial points option can only be specified for the Response Surface Methodology designs. The two options available here are Central Composite Design (CCD) and Face Centered Design (FCD). If you choose the CCD design, the system will automatically calculate your alpha value. However, you can change this value based on your specific needs. If you select the FCD design, the alpha value defaults to 1.0. 
7  Blocks:
Known noise factors should be blocked, and the entire design should be randomized to handle unknown noise factors. If you have specific noise factors that could impact your experimental design, you could block these factors from impacting your experimental results. Note that currently, you can only block the replicates. 
8  Random Seed: If you are randomizing your design and each time you want to generate the same random numbers, you can specify a random seed value here. The random seed value should be a numeric integer. If you leave the seed value blank, a random value will be used each time. 
9  Block Generator: You can assign a fractional column as a block. If you leave this blank, the software will pick a generator; otherwise, you can specify your block generator. Currently, only one block generator can be specified. Additional blocks are based on replication. 
1  Import Design: Select this radio button to create a design by importing the columns from a table. At a minimum you need to specify the factor columns to import but you can specify other supporting columns as described below.  
2  Search: You can enter any search terms here to filter your list of available data if you have many rows of data in your Excel file.  
3  Available Data: The list of available tables is shown in this list box. It lists all the available tables in your current workbook, the names of the columns within each table, the type of data (Numeric or Text), and the number of rows of data.  
4  Factor Columns: Specify the column names that contain the factors to import. For example, if you have three factors in your design as specified in your Design tab, you will need to specify the three factors in this list box. You can drag and drop the column names that contain this information from the list of available data. Note that this is an optional setting, and if you do not specify any columns in this list box, the factors are not imported and updated to the worksheet.  
5  Other Columns:
Specify the column that contains additional information for the design. In this list box, you can specify the standard order, run order, point type, and blocks for the experimental design. Note that this list box is optional. You will need to specify in the checkboxes below which columns you want to specify. Ensure that you enter the columns in the same order as the checkboxes. For example, if you have specified the checkboxes Point Type and Blocks, then the first column that should be specified is for the Point Type and the second column should be for Blocks. If no columns are specified, the default values are assumed for each column. The following table shows the default values that will be set if not specified.
 
6  Checkboxes: Specifies which columns should be imported from tables. By default, it is required that factor columns at a minimum must be imported to create your design and the rest of the columns can assume default values. If you want to specify other column, make sure to select the checkbox and enter that column information in the Other Columns listbox in the same order as the checkboxes. 
1  Search: You can enter any search terms here to filter your list of available data if you have many rows of data in your Excel file.  
2  Available Data: The list of available tables is shown in this list box. It lists all the available tables in your current workbook, the names of the columns within each table, the type of data (Numeric or Text), and the number of rows of data. You will need to look for those columns that contain the Response information for your design.  
3  Response Columns: You can enter the response data directly on the worksheet or import it from a table. If you plan to enter the data directly on the worksheet, you can leave the data tab blank. If you want to import the response data from a table, you can select the columns that contain the response data by dragging and dropping them from the list of available data. Note that if you specify multiple columns of data here, their mean or standard deviation is used to create the DOE model.  
4  Response Type:
If you have multiple columns, specify if you want to use the mean of all the columns as the response variable or the standard deviation of all the values as the response variable. If you specify the mean, the mean values of all the columns you entered in response columns will be used to fit the model. This is the default option. However, if you want to develop a DOE model to predict variation, you can use the standard deviation option to build a model of the data's standard deviation.

1  Model Reduction:
Specify how you want to perform the analysis. You have the following options:
 
2  Select Terms:
Specify which terms you want to include in your analysis. You will need to select the option for the model terms. You have the following options:
 
3  Available Terms: This list box lists all the terms available in your model to pick for analysis. Note that the factor names are represented in short form (A, B, C), etc., to make it easy to understand.  
4a  Select All Terms: Click on this button to move all the available terms to those included for analysis, shown in the list box on the right. This is equivalent to using all terms for your analysis.  
4b  Deselect Term: Click this button to remove the selected term from the Terms Included column. You can use this to drop any terms from your model you are no longer interested in.  
4c  Select Term: Click this button to move the term selected in the list of available terms to the included ones on the right. You can use this to add new terms to your model for analysis.  
4d  Deselect All Terms: Click on this button to remove all terms from the included terms list. You must start from scratch and add terms you are interested in later.  
5  Terms Included: This list box lists all the terms used to build your model.  
6a  Center Points: Click on this checkbox to include center points in your analysis. You need to include center points in your analysis initially, and if it is not statistically significant, you can drop the center point terms.  
6b  Blocks: Click on this checkbox to include blocks in your analysis. You need to include blocks in your analysis initially, and if they are not statistically significant, you can drop the block terms. 
1  Main Effects Plots: Click on this tab to specify the options to create the main effects plots. Note that if there is any item selected to display for the main effects plots, a >> sign is displayed on the page name. 
2  Interaction Effects Plots: Click on this tab to specify the options to create the interaction effects plots. Note that if there is any item selected to display for the interaction effects plots, a >> sign is displayed on the page name. 
3  Contour Plots: Click on this tab to specify the options to create the contour or surface plots. Note that if there is any item selected to display for the contour plots, a >> sign is displayed on the page name. 
4  Other Plots: Click on this tab to specify the options to create the other plots like Pareto plots and residual plots. Note that if there is any item selected to display for the other plots, a >> sign is displayed on the page name. 
1  Checkbox: Click on the checkbox if you would like to plot the main effects plot.  
2  Select Plots:
Select the plots that you are interested in. The following options are available:
 
3  Graph Type:
Under the graph type, specify the type of plots to generate. The available options are:

1  Checkbox: Click on the checkbox if you would like to plot the interaction effects plot.  
2  Select Plots:
Specify which interaction effects you want to plot. The following options are available:
 
3  Graph Type:
Click on the graph type and specify the type of plot to generate. The available options are:
 
4  XAxis Variable:
Click on the dropdown box for the Xaxis variable to specify which variable you want to use for the Xaxis. This option is only available if you plot a single interaction effects plot. The following options are available:

1  Checkbox: Click on the checkbox if you would like to plot the contour or surface plot.  
2  Select Plots:
Specify which interaction effects you want to plot. The following options are available:
 
3  XAxis Variable: Specify the Xaxis variable for the selected contour/surface plot.  
4  Graph Type:
Click the variable graph type to specify the type of plot to generate. The available options are:
 
5  Other Factors & Levels:
Click on the Xaxis factor setting to specify the factor used for the Xaxis. By default, the first variable is chosen for the Xaxis. Next, specify the levels to be used for the other factors. The following options are available:

1  Checkbox: Click on the checkbox if you would like to generate the other plots, such as the Pareto effects plot and the residual plots.  
2  Pareto Plot:
Specify if you would like to show or hide the Pareto plot. The available options are:
 
3  Residual Plots:
Specify if you would like to show or hide the residual plots. The available options are:
 
4  Target: If you want to look for an optimal target value in the results, specify the optional target value in the dialog box. This value will plot a horizontal line on the primary effects plot. The intersection of the horizontal line and the main effects plot will give an idea of the input variables' values that can result in this output value. The target value is also used to fashion the contours so that the target values can easily be found in the contour and surface plots. 
1  Item: The lefthand side shows the major tabs and the items checked within each section 
2  Status: The righthand side shows the status of the checks. 
3  Overall Status: The overall status of all the checks for the given analysis is shown here. The overall status check shows a green thumpsup sign if everything is okay and a red thumpsdown sign if any checks have not passed. Note that you cannot proceed with generating analysis results for some analyses if the overall status is not okay. 
1  Summary: Provides a summary of the design found on the worksheet. If you are using two levels or multiple levels for each factor. It also shows the number of factors and runs found on the worksheet. 
2  Factors & Levels: Provides a summary of the factors used in the design and the levels for each factor. It specifies whether the levels are numeric or text and the number of levels for each factor. If you disagree with this summary, you will need to click on Analysis Setup and modify the design as required. 
3  Notes: Provides a highlevel summary of the design, such as whether it contains center points and blocks, and if it is a fractional factorial, the type of confounding found in the model. 
1  Objective:
Specify the objective for this analysis. There are two options for this selection:
 
2  Initial Design:
Specify how you want to create the initial design. The available options are:
 
3  Improvements:
Specify if you want to make improvements to the initial design. The available options are:
 
4  Random Seed: If you create a design using the Random method, you can specify a seed value for the random number generator. If the seed value is zero, then a new set of random numbers is used each time to create the design. However, suppose you want to have repeatability in your analysis. In that case, you can specify a seed number for the random number generator so that the same set of random numbers is generated each time.  
5  Num Points: Specify how many points you want to retain in your final model. These are the number of runs (N) you can afford for this experimental design. This could be due to cost factors or the fact that we don't have sufficient resources to run all experiments.  
6  Indicator Column:
The indicator column on your worksheet specifies which columns to use for your final optimal design. If you leave this column blank, all rows are equally likely to be selected, and the best set of N rows will be selected for the final design. However, if specific rows are never included or always included, you can specify that in the indicator column. A value of 0 implies that we do not want to include this row in the final design. Possibly, this set of experimental runs is not feasible or practical for our analysis. A value of 1 in the indicator column implies that we always want to include this row in the final design. This could be used for rows where, from experience, we want to ensure that we keep this row in our analysis. If additional rows are to be selected to meet the minimum number of points in our design, they will be chosen from rows that don't have 0 or 1 marked in that row. Use the following syntax for this column.
 
7  Model Terms: Specify the terms that need to be included in the model. These terms will be used to compute the Defficiency scores. For example, if you specify A, B, C, AB, then the terms A, B, C, and the interaction term AB will be used for analysis.  
8  Use Intercept: If you select this checkbox, the constant or the intercept term will also be included in the model for computing the Defficiency scores.  
9  Model Terms:
You can either manually type in the model terms or use one of the standards to define the model terms. The available options are:
 
10  Results: The results of the analysis are displayed in this textbox.  
11  Copy Solution: Click this button to copy the developed solution back to the worksheet. This will place 0's and 1's in the indicator column. A value of 0 implies that that row is not included in the final model, and a value of 1 indicates that that column is included in the final model.  
12  Clear Indicator: Click this button to clear any values entered in the Indicator column. You can manually clear it from the worksheet or use this button to clear the values.  
13  Cancel Button: Click this button to close this dialog box  
14  Optimize Button: Click this button to perform the analysis and report the results in the Results dialog box. 
1  Exclude Row: Since the indicator column in the first row shows 0, we do not include this row in our analysis. 
2  Include Row: Since the indicator column in the remaining rows shows 1, we include these in our analysis. 
1  Model: The model analyzed in the current worksheet is displayed in this section. If no model has been studied yet, you cannot make predictions using this dialog box. You will need first to generate a model using the Analysis Setup and Compute Outputs buttons. You can use a model to make predictions only when a model has been developed and saved to the worksheet. 
2  Date: The date shows the date the model was developed and saved to the worksheet. Note that once a model has been saved, it can be used for predictions. You don't need to use Compute Outputs to update the model. You can share this worksheet with other users, and they can enter their inputs and generate the predicted model outputs using the model equation. 
3  Inputs: Specify the input values you want to use to make the prediction. You will need to specify all the model inputs to make a prediction. A blank value of input will be taken as a value of 0. 
4  Predict Button: Click on the >> button to make the prediction. This will use the model equation and the inputs you have specified to generate the model outputs. 
5  Outputs: The outputs from the model are displayed in this section. Currently, the outputs are only displayed in this dialog box and not on the worksheet. You will need to manually copy the solution to your worksheet if you would like to save this value. 
6  Cancel Button: Click on this button to close this dialog box. 
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