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Experienced users of the software can start by building a New Design or loading an existing design with the Open Design button. Searchable, context-sensitive help can be called by clicking the question mark icon or F1 on the keyboard.

It provides assistance on what to do next. Click on a number in a cell of the report and right-click in the cell to request help to learn more about its contents.

Screen tips provide instructions for what to do or what to look for on the current screen. Stat-Ease Tutorials are available online and included in the installer. Use the tutorials to get more familiar with design of experiments DOE. In our example, we chose to use the full quadratic model. Therefore, some less significant terms shown in black are retained, even though they are not significant at the 0. Right click any cell to export this report to PowerPoint or Word for your presentation or report.

Check it out: This is very handy! Under the Optimization branch to the left of the screen, click the Numerical node to start. We will detail POE later.

The program restricts factor ranges to factorial levels plus one to minus one in coded values — the region for which this experimental design provides the most precise predictions. Response limits default to observed extremes.

In this case, you should leave the settings for time, temperature, and catalyst factors alone, but you will need to make some changes to the response criteria. Desirabilities range from zero to one for any given response. The program combines individual desirabilities into a single number and then searches for the greatest overall desirability. A value of one represents the ideal case. A zero indicates that one or more responses fall outside desirable limits. For this tutorial case study, assume you need to increase conversion.

Click Conversion and set its Goal to maximize. As shown below, set Lower Limit to 80 the lowest acceptable value, and Upper Limit to , the theoretical high. Conversion criteria settings You must provide both these thresholds so the desirability equation works properly.

By default, thresholds will be set at the observed response range, in this case 51 to Otherwise we may come up short of the potential optimum. Now click the second response, Activity. Enter Lower Limits and Upper Limits of 60 and 66, respectively. Values outside that range are not acceptable. Activity criteria settings The above settings create the following desirability functions: 1.

Close out Screen Tips by pressing X at the upper-right corner of its screen. Weights give added emphasis to upper or lower bounds or emphasize target values. With a weight of 1, di varies from 0 to 1 in linear fashion. Weights greater than 1 maximum weight is 10 give more emphasis to goals. Weights less than 1 minimum weight is 0. Try pulling the square on the left down and the square on the right up as shown below.

Before moving on from here, re- enter the Lower and Upper Weights at their default values of 1 and 1; respectively. If you want to emphasize one over the rest, set its importance higher. By leaving all importance criteria at their defaults, no goals are favored over others. Then click Contents.

From here you can open various topics and look for any details you need. Now click the Options button to see what you can control for the numerical optimization. After doing your first search for the optimum, go back to this Option and slide it one way and the other. Observe what happens to the solutions presented by Design-Expert. If you move the Filter bar to the right, you decrease the number.

Conversely, moving the bar to the left increases the solutions. Click OK to close Optimization Options. Running the optimization Start the optimization by clicking the Solutions tab. It defaults to the Ramps view so you get a good visual on the best factor settings and the desirability of the predicted responses. Numerical Optimization Ramps view for Solutions Your results may differ The program randomly picks a set of conditions from which to start its search for desirable results — your results may differ.

Multiple cycles improve the odds of finding multiple local optimums, some of which are higher in desirability than others. Due to random starting conditions, your results are likely to be slightly different from those in the report above. The colored dot on each ramp reflects the factor setting or response prediction for that solution.

The height of the dot shows how desirable it is. Press the different solution buttons 1, 2, 3,… and watch the dots. They may move only very slightly from one solution to the next. However, if you look closely at temperature, you should find two distinct optimums, the first few near 90 degrees; further down the solution list, others near 80 degrees.

You may see slight differences in results due to variations in approach from different random starting points. For example, click the last solution on your screen. Does it look something like the one below? Second optimum at lower temperature, but conversion drops, so it is inferior If your search also uncovered this local optimum, note that conversion falls off, thus making it less desirable than the higher-temperature option.

The Solutions Tool provides three views of the same optimization. Drag the tool to a convenient location on the screen. Click the Solutions Tool view option Report. Desirability A:time 1 B:temperature 1 C:catalyst 1 Conversion 0. Optimization Graphs Press Graphs near the top of your screen to view a contour graph of overall desirability.

On the Factors Tool palette, right-click C:Catalyst. Make it the X2 axis. Temperature then becomes a constant factor at 90 degrees. Design-Expert software sets a flag at the optimal point. To view the responses associated with the desirability, select the desired Response from its droplist. Take a look at the Conversion plot. Then go to Surface Graphs and click Show contour grid lines. Show contour grid lines option Grid lines help locate the optimum, but for a more precise locator right-click the flag and Toggle Size to see the coordinates plus many more predicted outcome details.

To get just what you want on the flag, right-click it again and select Edit Info. Flag size toggled to see select detail By returning to Toggle size, you can change back to the smaller flag. If you like, view optimal activity response as well. To look at the desirability surface in three dimensions, again click Response and choose Desirability.

Then, on the floating Graphs Tool, press 3D Surface. Next select View, Show Rotation and change horizontal control h to Press your Tab key or click the graph. What a spectacular view! In other words, the solution is relatively robust to factor C. Do this by pressing the Default button Surface Graphs and any other Graph Preference screens you experimented on. Design-Expert offers a very high Graph resolution option. Try this if you like, but you may find that the processing time taken to render this, particularly while rotating the 3D graph, can be a bit bothersome.

This, of course, depends on the speed of your computer and the graphics-card capability. To see a broader operating window, click the Graphical node. You need not enter a high limit for graphical optimization to function properly. Graphical optimization: Conversion criteria Click Activity response.

If not already entered, type in 60 for the Lower Limit and 66 for the Upper Limit. Notice that regions not meeting your specifications are shaded out, leaving hopefully! Temperature then becomes a constant factor at 90 degrees as before for Solution 1. This Design-Expert display may not look as fancy as 3D desirability but it can be very useful to show windows of operability where requirements simultaneously meet critical properties.

Shaded areas on the graphical optimization plot do not meet the selection criteria. This provides a measure of uncertainty on the boundaries predicted by the models — a buffer of sorts.

Confidence intervals CI superimposed on operating window After looking at this, go back and turn off the intervals to re-set the graph to the default settings. If you are subject to FDA regulation and participate in their quality by design QBD initiative, the CI-bounded window can be considered to be a functional design space, that is, a safe operating region for any particular unit operations. However, to establish a manufacturing design space on must impose tolerance intervals.

This tutorial experiment provided too few runs to support imposition of TIs. What will this do to the operation window? Find out by dragging the 80 conversion contour until it reaches a value near Then right-click it and Set contour value to 90 on the nose. Changing the conversion specification to 90 minimum It appears that the more ambitious goal of 90 percent conversion is feasible.

This requirement change would make the lower activity specification superfluous as evidenced by it no longer being a limiting level, that is, not a boundary condition on the operating window.

Graphical optimization works great for two factors, but as factors increase, optimization becomes more and more tedious.

You will find solutions much more quickly by using the numerical optimization feature. Then return to the graphical optimization and produce outputs for presentation purposes. Response Prediction and Confirmation This feature in Design-Expert software allows you to generate predicted response s for any set of factors. To see how this works, click on the Point Prediction node lower left on your screen. Click the Point Prediction node left on your screen. Notice it now defaults to the first solution.

Be thankful Design-Expert programmers thought of this, because it saves you the trouble of dialing it up on the Factors Tool. Go ahead and play with them now if you like. You can either move the slider controls, or switch to the Sheet view and enter values. Take a moment now to study the screen tips on all the statistical intervals that come up when you press the light- bulb icon.

Confirmation After finding the optimum settings based on your RSM models, the next step is to confirm that they actually work. To do this, click the Confirmation node left side of your screen. You might be surprised at the level of variability, but it will help you manage expectations. Note: block effects, in this case day-by-day, cannot be accounted for in the prediction. Of course you would not convince many people by doing only one confirmations run. Doing several would be better.

Go to the Confirmation Tool and enter for n the number 3. Click the Enter Data option and type for Activity 62, 63 and Entering confirmation run results Notice that the prediction interval PI narrows as n increases. Does the Data Mean displayed in red fall within this range?

If so, the model is confirmed. Observe the diminishing returns in terms of the precision, that is, the PI approaches a limit — the confidence interval CI that you saw in Point Prediction. The CI is a function of the number of experimental runs from which the model is derived. That is done is this stage, so one can only go so far with the number of confirmation runs. Perhaps half a dozen of these may suffice. If you are not worn out yet, you will need this file in Part 3 of this series of tutorials.

Summary Numerical optimization becomes essential when you investigate many factors with many responses. It provides powerful insights when combined with graphical analysis. However, subject-matter knowledge is essential to success. For example, a naive user may define impossible optimization criteria that results in zero desirability everywhere!

To avoid this, try setting broad acceptable ranges. Narrow them down as you gain knowledge about how changing factor levels affect the responses.

Move on to the next tutorial on advanced topics for more detailing of what the software can do. If you want to learn more about response surface methods not the software per se , attend our Stat-Ease workshop Response Surface Methods for Process Optimization.

We appreciate your questions and comments on Design-Expert software. E-mail these to stathelp statease. Then under the Analysis branch click the R1:Conversion node and go to Model Graphs to bring up the contour plot.

In the vacant region of the AB contour plot right click and select Add contour. Then drag the contour around it will become highlighted.

You may get two contours from one click like those with the same response value shown below. This pattern indicates a shallow valley, which becomes apparent when we get to the 3D view later.

Adding a contour Click the new contour line to highlight it. Then drag it place the mouse cursor on the contour and hold down the left button while moving the mouse to as near to 81 as you can. Now to obtain the precise contour level, right-click the contour you just dragged, choose Set contour value and enter Then choose Contours. Now select the Incremental option and fill in Start at 66, Step at 3, and Levels at 8. That gives you a clue on where to start and how big to step on the contour values.

Zooming in on a region of interest by roping off a box Notice how the graph coordinates change. Obviously you would now want to add more contours using the tools you learned earlier in this tutorial. However, do not spend time on this now: Right-click over the graph and select Default View Window. On the Graphs Tool go to 3D Surface view. Change the Low to 80 and the High to Notice how this makes the graph far more colorful and thus informative on the relative heights.

Edit Legend dialog box to change the color gradient Now click the design point sticking up in the middle. See how this is identified in the legend at the left by run number and conditions. On the Factors Tool select off the Run down-list number 1. However the colors are not ideal now.

So right-click over the gradient and in the Edit Legend dialog box press the Defaults button. Your graph should now match the one shown below. This can be very useful to document unusual happenings during any given run. Much more can be done for your show-and-tell. Spend time beforehand to try different things that Design-Expert can do.

Take advantage of default buttons to put things back the way they were. Then you can generate propagation of error POE plots showing how that error is transmitted to the response. To be sure we start from the same stage of analysis, re-open the file named RSM-a. Then click the Design node on the left side of the screen to get back to the design layout.

Next select View , Column Info Sheet. Enter the following information into the Std. Option to enter a different standard deviation for response Otherwise the field will be protected, that is, you cannot alter it. Under the Analysis branch click the Conversion node.

Then jump past the intermediate buttons for analysis and click the Model Graphs tab. Select View , Propagation of Error. This option was previously grayed out — unavailable — because the standard deviations for the factors had not yet been entered. See this for yourself by trying it. Under the Optimization branch click the Numerical node. On the floating Solutions Tool click Ramps. Note: Due to random starting points for the searches, you may see slight differences on your screen versus the shot below.

Ramps view for optimization with POE Your results may differ The above optimal solution represents the formulation that best maximizes conversion and achieves a target value of 63 for activity, while at the same time finds the spot with the minimum error transmitted to the responses.

So, this should represent process conditions that are robust to slight variations in factor settings. In this case it does not make much of a difference whether POE is accounted for or not go back and check this out for yourself. However, in some situations it may matter, so do not overlook the angle of POE. Design evaluation ought to be accomplished prior to collecting response data, but it can be done after the fact. For example, you may find it necessary to change some factor levels to reflect significant deviations from the planned set point.

Or you may miss runs entirely — at least for some responses. Then it would be well worthwhile to re-evaluate your design to see the damage. Design summary The summary reports that the experimenter planned a central composite design CCD in two blocks, which was geared to fit a quadratic model.

Click the Evaluation node and notice Design-Expert assumes you want details on this designed-for order of model. Press ahead to the Graphs button atop the screen. It defaults to the FDS Graph that depicts standard error versus the fraction of design space.

Click the curve you see depicted. Design-Expert now provides coordinate lines for easy reading. Due to the random sampling algorithm, your FDS may vary a bit. When you evaluate alternative designs, favor those with lower and flatter FDS curves. Stat-Ease teaches how to do this in its workshop on RSM. The FDS provides insights on prediction capabilities.

Design-Expert then displays the standard error plot, which shows how variance associated with prediction changes over your design space. Also, notice the circular contours. This indicates the desirable property of rotatability — equally precise predictive power at equal distances from the center point of this RSM design. For standard error plots, Design-Expert defaults to black and white shading. The graduated shading that makes normal response contour plots so colorful will not work when displaying standard error.

Look closely at the corners of this graph and notice they are gray, thus indicating regions where the response cannot be predicted as precisely. Then right- click over the graph and select Graph Preferences.



Design-Expert Reference Manual –

The manual and tutorials are included on the CD in Adobe’s portable document format (pdf). They can be installed on your system using the “. DeskArtes Design Expert Tutorial Other icons set Design Expert to operate in a particular A new curve can be created using Curve:Create:Free. Lecture6-Design Expert Software – Tutorial – Free download as Powerpoint Presentation .ppt), PDF File .pdf), Text File .txt) or view presentation slides.


Design expert manual pdf free.

The manual and tutorials are included on the CD in Adobe’s portable document format (pdf). They can be installed on your system using the “. Rev. 2/23/13 Mixture Design Tutorial (Part 1/2 – The Basics) Introduction In this tutorial you are introduced to mixture design.

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