JMP Wish List

hogi · ‎10-15-2022

☑ cool new feature ☑ could help many users! ☐ removes a „bug“ ☐ nice to have ☐ nobody needs it #myTop10_2022 If a user changes the name of a column, references to the column in table scrips are (sometimes) automatically corrected, references in user scrips unfortunately not: Column() vs As Column() vs datable:column vs dt:As name("column") So, column name changes are very dangerous: there is always the risk that a jsl code doesn't work anymore after the change - like illustrated in the example below. JMP detects that a noc-existing column is requested and throws an error: My wish: Instead of throwing an error, JMP could open a window and provide a list of column names. Then the user can select a replacement column. There should also be a toggle box, allowing the user to decide if the JSL code should be automatically adjusted wit the new column name. The new behaviour could be enabled/disabled in the preferences menu such that users which got used to error message still have the choice to get it. NamesDefaultToHere(1); dt = Open("$SAMPLE_DATA/Big Class.JMP"); Data Table( "Big Class" ):age << Set Name( "age_" ); s = dt << runScript("Distribution"); // column names automatcally adjusted wait(2); s = dt << runScript("Set Age Value Labels"); // this script throws an error more wishes submitted by

ASTA · ‎10-11-2022

I would like to suggest a feature to be added for validation runs of your DoE model. Usually when I have the data for my DoE model I run an additional 3-5 runs to validate the model and compare the outcome of the runs to what the model predicted. It would be very useful to have this as a feature in JMP to augment the design with additional runs and compare the results to the model predictions by a test of equivalence.

Charlie · ‎10-05-2022

I have a stacked table with a Time Point (X) column, a Cumulative Release (Y) column, and several columns of factors from a DOE. We have different specification limits for release at various time points in the dissolution curve, as required by the FDA. In development, I need to fit curves to the data, use models to determine significant factors, and optimize factors using Desirability Functions. I can fit curves with this table, but I cannot use the Desirability Functions because each column can only have one set of specifications saved with it. I can split the table by Time Point and make a new table, but that creates more documentation and review work, as required by our data integrity rules. It would be nice if there was a way to account for these specifications in Fit Model and FDE. Suggestions Allow specification limits to be set conditionally. This may help resolve the problem for non-FDE models. In FDE, allow more than one target curve. Curves based on upper spec, target, and lower spec would allow explorations of the variable space for each target curve. I use JMP Pro 16.2.0

Victor_G · ‎09-16-2022

Hello dear JMP Team, When searching through the Sample Data Index in the part "Design of Experiments", I see no indications about the type of design used. I find it quite difficult to navigate in this list and find the right design example. Perhaps would it be possible to add next to each file name the type of design used (not necessarily all the details of the design) ? : Custom Design, Augmented Design, Definitive Screening Design, 2-levels Screening/Fractional Factorial/Full Factorial Design, Response Surface Design (CCD, Box-Behnken...), Mixture Design, Taguchi Arrays, Choice Design, MaxDiff design, Space-Filling Design, ... It would help a lot find the right example with the right design, when teaching/explaining/learning a concept about DoE and needing a toy dataset to demonstrate. Thanks for the hard work !

DensityOfMining · ‎06-05-2022

Donald46 · ‎04-20-2022

Idea: Add a comment/label to a constraint to describe it's function Problem: It's common to share DOE's with colleagues, when they look at how the DOE was designed it's often very difficult to know what each constraint is trying to achieve How solution works: Labelling each constraint will indicate the intention of each constraint

Benjamin_Fuerst · ‎02-04-2022

Hello, It would be very helpful after punching in the linear constraints for a DOE, to see a preview of your constrained space before you "Make the Design". Ben

ttallen · ‎12-03-2021

I am a big fan and user of the Custom DOE option in JMP. I recently use the option to plan a pro COVID vaccination advertising campaign that significantly increased rates. At the same time, I wish that the software included expected bias (at least as an option) in the design criterion. Both Doug Mongomery and I have written papers about variance plus expected bias criteria. George Box pointed out the importance of including bias in experimental planning optimization. For related references please consider our old article: Allen, T. T., & Tseng, S. H. (2011). Variance plus bias optimal response surface designs with qualitative factors applied to stem choice modeling. Quality and Reliability Engineering International, 27(8), 1199-1210. Variance plus bias optimal response surface designs with qualitative factors applied to stem choice modeling (researchgate.net) It shows how to make reasonable assumptions in general situations. Contact me at allen.515@osu.edu if you want to discuss this.

rc_hertzy · ‎06-19-2021

While many JMP methods are described or identified in platform output (e.g., Nonlinear saying "Solved by Analytic Gauss-Newton") others are not. When different JMP platforms give different results, understanding and explaining that difference is difficult. My client (US government) uses confidence limits for policy decisions, so I need to know why the methods differ. Example (JMP 16.0.0): Nonlinear vs. Fit Curve, both using Exponential 3P model, even though the corresponding parameter (and Std Err) estimates agree to the number of digits shown. Extremely useful would be JMP having a central Help page where one can easily locate the identification of the statistical method employed. Including a reference and/or summary of the statistical details would also be helpful.

jszarka · ‎05-19-2021

Currently, if a covariate is included in Custom Design, there is no longer an option to have random blocks. This would be a nice feature to add. You can have fixed blocks right now, or you have to do something creative where you add in a fake hard-to-change factor to create a split-plot design, but modify your model. Having the random blocks option would seem most natural for those situations.

Vins · ‎05-01-2021

The covering array DOE platform now supports dissallowed combinations. Based on a talk by @joseph_morgan and @Ryan_Lekivetz a few years back, the availability of options in the covering array platform that allow you to set different factors at different strengths would greatly improve the platforms use and applicability in software testing and laboratory testing. A JMP add in would also be welcomed.

jszarka · ‎04-27-2021

When generating a split-plot or other experiment with random blocks using Custom Design, I really like how the resulting data table has an Evaluate Design script already attached to it. However, if I update the 'Whole Plots' or 'Random Block' to actually reflect what it truly means in practice (e.g. Setup or Batch) then the script doesn't work. I think it's as simple as adding that linkage (as denoted by the ":" that you get with the other factors). If I just have X1-X3, this is what the code looks like for a split-plot, and won't update once the Whole Plots column is renamed. However, if I update the name of X1, it will update appropriately. DOE( Evaluate Design, X( Whole Plots, :X1, :X2, :X3 ) )

shampton82 · ‎01-10-2021

I'd like to see the process screening platform be able to recognize columns assigned as non-normal and be to use these columns in the analysis. Right now only normal data columns can be used.

plebrun · ‎10-09-2020

There is two main schools of how people can build DOE. The one chosen by JMP is to create design matrix using the powerful coordinate exchange algorithm. The second way is to provide a list of candidate data points (that could respects some complex constraints) and then search through it to create the design. (Actually, is JMP creating this list of candidate points in background ? When looking at design, there are some weird non rounded values, some times, which seems to indicate that JMP can take really any point (satisfying constraints if any) from the space of factor.) I discussed yesterday with many DoE users at a conference, and they told me the fact that the second option does not exist in JMP is one of the main reason they don’t want to buy and use JMP. This option is however available in SAS proc Optex, which I am sure share many similarities with the Custom DoE platform of JMP. Would you think such addition may be possible in the future, for Custom Design and Augment Design platforms ?

PaulM · ‎08-19-2020

Expand the capability of the FDE DOE platform to allow optimization of multiple variables at a time vs. the response. Currently you can only see each variable in mini profiler with whatever your chosen output is. It would be nice to view many different curves/variables with the output in the same profiler, so you can view a more complex process easier.

Vball247 · ‎04-10-2020

Just watched the JMP on Air segment on Statistics Index, The Statistics Index. I like to tell new JMP users about it in JMP classes. Would like to suggest adding a filter like in the Scripting Index or Preferences. Right now in the Statistics Index you can start typing in the menu to find something, but it is a first character look-up. I search for Steel-Dwass and find it, but if I only remembered something like "Dwass", then it will not show. Or say you want to find any topic on "design", it is scattered throughout the index like "experimental design", "factorial design", "fractional factorial...", etc.

Amir_H · ‎03-30-2020

Can you please fix the HTML interactivity in DOE model's profilers when one or a few constraints are defined? My DOE model’s profilers in the HTML file became static when I added the constraints. They were interactive when I had no constraints. Unfortunately, including constraints in most DOE models is inevitable.

pauldeen · ‎03-11-2020

I would like to be able to add a factor to a previously ran Custom DOE. So an extension of the augment DOE platform that allows me to add a new factor where I could tell you what that factors was set to for the runs that are already done.

MathStatChem · ‎10-22-2019

I would like the ability to get alias effects matrix using JSL in Custom Design. there is a <<Get X Matrix (X) that returns the design matrix for the specified model and there is a <<Get Alias Matrix message that gets the aliasing correlations (for model x alias interactions, X`*A) but there is not command to get the alias effects matrix for the design (A) In Custom Design, Evaluate Design, and Compare Designs, I would like to be able to use JSL get the full correlation matrix that is used to construct the color map on correlations. So a <<Get Correlations Matrix message would be nice.to add. For Evaluate Design, I would like to be able to see a list of the pairwise correlations of the model x model, model x alias, and alias x alias correlations. Similar to the pairwise correlations table that can be displayed in Multivariate. The reason so so that I can sort and see the pairs of effects with the highest confounding. For Compare Designs, I would like to be able to see the difference in the effects and aliases correlations matrices. So if I compare 2 designs, and each has a color map on correlations (C1 and C2), I want to be able to see (C1-C2) as a "delta color map".

jdv · ‎10-10-2019

It would be very helpful to allow an option for non-linear constraints for mixture DOE.

JMP Wish List

catch "missing column" error and provide a selection menu

DoE model validation /verification feature

Using Multiple Time Point Dissolution Specifications with Models

Sample Data Index (Design of Experiments): Add descriptions about which design is used

visualization Augment for multiple variants correlation based on quality control chart

Add labels to constraints

DOE with constraints: Graphical preview

Custom DOE With an Integrated Variance + Expected Bias Option

Help page for statistical details of all JMP methods

Random Blocks with Covariate Designs

variable strength covering arrays

Labeling Flexibility for Split-Plot and Random Block Experiments for Evaluate Design

Update to Process Screening platform

Custom design from candidate points

Expand FDE DOE

Filter on the Statistics Index

Interactive HTML with constraints

Augment DOE with new factor

DOE platform improvement suggestions

Non-linear constraints in DOE