Agenda

Monday, 6 March

13:00 - 17:15 CET

Level–1

Workshops Welcome Desk

14:00 - 17:00 CET

Xaloc 1, Xaloc 2 and Xaloc 3

Hands-on Workshops

Led by JMP Education these 75-minute workshops are a rare opportunity for you to go in-depth on specific topics with the experts themselves. You’ll learn about some of the core tenets of JMP and see the software in action.

This content is offered in three themed tracks (Tips and Tricks, Using the JMP Scripting Language, and Case Studies in Data Analysis), but they are independent sessions and do not build on each other. Switch between tracks to customize your learning journey to the topics of interest to you.

Bring a laptop with JMP (or JMP Pro) 16 or 17 installed to get the most benefit from these hands-on sessions.

*Click on each title below to see the schedule. You can sign up for the workshops when you register for the conference. All sessions are complimentary.

Xaloc 2

Tips and Tricks

Facilitator: JMP Education

If you are new(ish) to JMP, come to our Getting Started session to catch the vision of JMP as a dynamic, progressive interface to help you solve all kinds of business problems. This first session will cover the basics of navigating JMP and includes a lot of tips and tricks to help you get deeper insight from your data.

The second session in this track is all about how to decide which statistical method is most effective in solving your specific problem. Are you trying to combine similar batches? Identify causes of poor quality in production? Predict the impact a change will have on a process? Learn about choosing Which Model When in this session.
Xaloc 3

Using the JMP Scripting Language

Facilitator: JMP Education

The JMP Scripting Language (JSL) is a powerful tool for automating repetitive tasks, standardizing analyses across multiple people or departments, and extending the capabilities of JMP. The first session explores adapting scripts to incorporate user selections and input using dialogs. The second session covers the basics of JSL and taking advantage of automatic script generation for the novice scripter. (*The first session in this track is geared toward a scripter with some experience. The second session is developed for a very new JMP scripter.)
Case Studies in Data Analysis

Xaloc 1

Facilitator: JMP Education

These sessions will cover case studies about improving quality, optimizing process settings, reducing costs, and avoiding failures using both JMP and JMP Pro. (Each session will include content for both Pro and non-Pro JMP users.) You’ll learn about the statistical models needed to solve these problems and how to implement them in JMP.

15:00 - 18:00 CET

Meliá Atrium

Early Registration

18:00 - 21:00 CET

Meliá Garden

Food Truck & Market Dinner in the Garden

Immerse yourself in a wonderful gastronomic world where the warm climate of Sitges is mixed with a dinner under the light of the moon.

Mediterranean cuisine with seasonal products, as well as a wide variety of hot and cold snacks and tapas. It includes a variety offer from the cheeses of the Pyrenees mountains to the seafood offered by the Mediterranean Sea.

Attentive and personalized service in an informal and relaxed atmosphere.

Tuesday, 7 March

8:00 - 9:30 CET

Expo Hall

Registration

8:00 - 9:30 CET

Noray Restaurant

Breakfast

8:30 - 9:30 CET

Mestral 2

JMP® Lab

9:00 - 9:30 CET

Expo Hall

Discovery Expo

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement and more.

9:30 - 10:45 CET

Tramuntana

Plenary Session

The Flow of Discovery: Automating the standard paths and enabling the non-standard paths

John Sall, Founder and Chairman, JMP
Mandy Chambers, Principal Test Engineer, JMP
Ryan Lekivetz, Manager, Advanced Analytics R&D, JMP
Rebecca Lyzinski, Clinical Research Developer, JMP
Aurora Tiffany-Davis, Principal Software Developer, JMP

JMP is built for discovery, but discovery is not just happening to see something in a graph; it usually involves a lot of work and many process steps. The problem is that the steps are not always the same in each situation or in each set of data – the analysis has to be interactive. You must be able to pursue clues, identify things, drill down to details, and adapt to new conditions.

The analytic process is fundamentally interactive, and JMP supports interactivity. But there can be “easy buttons” along the way, and you can create your own “easy buttons” for the steps that you plan to take again.

Whether your work can be planned or is a wild path of exploration and serendipity, JMP has the modes to make your work speedy, efficient and productive, while keeping you in an environment of discovery.

11:00 - 11:45 CET

Expo Hall and Mestral 2

Discovery Expo and JMP® Lab

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement, JMP® Lab and more.

11:45 - 12:30 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1335

Llevant 1

A Cross-step Insight With Paired Upstream and Downstream DOE

Tannaz Tajosleiman, Data Scientist, NNE

Topic: Design of Experiments
Level: III

During a process development phase, the process operating conditions must be characterized and optimized at upstream and downstream levels. However, despite the well-known effect of the upstream outcome properties on the performance of the downstream, these two levels are often studied and tested separately, and the interlinked correlations are ignored. As a result, it’s not uncommon to see cases where a significant improvement in the upstream is not retained downstream and, even in some extreme cases, causes additional downstream challenges and a lower overall process yield. Hence, it is important to have a comprehensive cross-step view in the design of the experiments during the process characterization. In this regard, the JMP DOE toolbox is ideal for addressing such cases. In this work, a case study will be presented that demonstrates a systematic two-step method to use the JMP custom design DoE toolbox and the covariate factors option for a cross-step experimental design. The design focuses on pairing the upstream and downstream experimental conditions in an efficient manner. Moreover, operational practicalities such as batch parallelization are included in the final design.
Session ID: 2023-EU-30MP-1276

Garbi 2

JMP Into Retirement Using the Reliability Platform in JMP®

Don Lifke, Development Engineer / Statistician, Sandia National Lab

Topic: Data Exploration
Level: II

The powerful Reliability Platform in JMP® is often overlooked and underutilized. This talk demonstrates some of the basics of the Reliability Platform in JMP by answering the seemingly simple question, "How long will my retirement endure?" Why guess at this extremely important figure when planning for retirement? Use JMP to explore this question! This was accomplished using Reliability and Survival Fit Life by X and historical data from retirees. Uncertainties of this prediction were also quantified. The optimum retirement age was addressed, considering that retiring earlier draws less income for a longer period. In addition, JMP was used to visualize the employer's retirement tool to optimize the most financially desirable retirement age and explore the most enjoyable chapter of life — retirement!
Session ID: 2023-EU-30MP-1262

Garbi 1

Navigating Your Data Workflow: Workflow Builder Grants Your Wishes for Data Cleanup

Mandy Chambers, JMP Principal Test Engineer, JMP

Topic: Data Access and Manipulation
Level: I

What if you could save time in your process of collecting data, cleaning it, and readying it to begin your analysis? Accessing data and preparing it for review is often the most time-consuming part of creating a new data analysis or project. With that in mind, we would like to introduce the Workflow Builder in JMP® 17. With this exciting new feature, JMP users can now record their entire process from beginning to end, starting with accessing data from multiple sources. Working with the action recorder (added in JMP® 16 to track steps and provide scripts that can be saved and reused), Workflow Builder tracks all your changes in data prep and cleanup, data analysis, and reporting. In this presentation, we will show how to operate the Workflow Builder, save each action, and then replay and share them in a polished report. This is sure to become your new favorite feature in JMP 17. No manual cleanup means extra time in your day!
Session ID: 2023-EU-30MP-1266

Llevant 4

Preparing Batch Process Data for Modeling With JMP Pro and Gain Insights Using a Team Approach

Georg Raming,Senior Manager, Siltronic AG

Topic: Data Exploration
Level: II

Siltronic AG is a global technology leader in the semiconductor wafer industry. This presentation will introduce the Siltronic AG approach to preparing batch process data for modeling with JMP Pro. It will demonstrate some interactive steps to clean and rearrange the dataset before modeling using an anonymized dataset containing both historical and experimental batch data. Once the best model algorithm is found, the boosted tree model will be tuned.  The Siltronic AG team found that a technically sound model may be physically worthless, meaning it had been overfitted. Therefore, the team started with a small set of factors, gradually expanding the factor list and testing the model's behavior to find the most effective factors (step forward strategy for a boosted tree in a small JSL routine). The last step provided the best insight into which levers are the strongest to optimize the process.

12:30 - 14:00 CET

Noray Restaurant

Lunch

14:00 - 14:45 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1335

Llevant 1

Mixing Plan for Wine Blending and Tasting of the Modalities To Validate the Recipe of a Wine

Margaux Renaud, R&D Engineer, Chêne & cie

Topic: Data Visualization
Level: I

A client working on blending his wine wanted to get as close as possible to a known wine with different ingredients. To help the client do this, we created a mixture design with four ingredients for 16 samples to compare with the known blend. The samples were tasted randomly, and the panel was asked to create groups of similar samples and describe the group. The result was a distance matrix developed with the help of a JMP script. This matrix was processed by a multidimensional scaling to obtain a map that was easy to describe to the panel. A K-means classification was used to find the samples close to the target. Finally, the distance between the target and the other sample was calculated and represented by a contour plot to show the best part of the mixture design. The terms used by the taster to describe the groups were processed by JMP Text Explorer and then by AFCM to show a map with samples and terms to better describe each sample's position using sensory properties.
Session ID: 2023-EU-30MP-1218

Garbi 1

Regex: A Powerful Text Analysis Tool

Hadley Myers, Senior Systems Engineer, JMP
Peter Hersh, Senior Systems Engineer, JMP

Topic: JSL Application Development
Level: III

Extracting pertinent information from unstructured text data can pose a daunting challenge. Someone may wish to mine blocks of text for websites, telephone numbers, emails, or physical addresses. It could be that units of measurement between documents need standardizing. The Regex function, quietly incorporated into JMP a few releases ago, is an extremely powerful tool to quickly and easily perform these and other tasks. It is also a tool that, for many, is shrouded in mystery. This presentation seeks to highlight this often overlooked and underrated function and decode its inner workings to allow anyone and everyone to tap into its full potential.
Session ID: 2023-EU-30MP-1346

Garbi 2

Scaling up the Use of Machine Learning in Chemical Process Industries

David Peig, Digital Champion, GBU Soda Ash & Derivatives, Solvay SA, BE.
Carlos Perez-Galvan, Industrial Data Scientist, Solvay
Francisco Navarro, Industrial Data Scientist, Solvay

Topic: Data Exploration
Level: II

Solvay was the first company to succeed in industrializing the production of soda ash in 1863, a product that only requires salt and limestone as raw materials. However, behind this simple idea is an intricate continuous process able to handle reactant solids, liquids, and gases. Similarly, using data to bring value needs a deep understanding of any manufacturing process behind it. This presentation will showcase how Soda Ash at Solvay is scaling up the use of data-driven techniques in the chemical industry. To succeed, we trained our subject domain experts (process engineers) to use JMP and its predictive analytics capabilities to accelerate daily tasks such as monitoring and root-cause analysis. We will discuss our open-source JMP add-in to connect to industrial historians (Aspentech IP.21 and OSIsoft PI), the current training program, and the lessons learned in this digital transformation journey.
Session ID: 2023-EU-30MP-1308

Llevant 4

Using Generalized Regression To Analyze Designed Experiments With Detection Limited Responses

Fangyi Luo, Group Scientist, Procter & Gamble
Chris Gotwalt, Chief Data Scientist, JMP
Beatrice Blum, Senior Scientist, Procter & Gamble

Topic: Design of Experiments
Level: III

Most measurement systems have detection limits above or below which one cannot accurately measure the quantity of interest. Although detection-limited responses are common in many application areas, such as the pharma, chemical, and consumer products industries, they are often ignored in the analysis. Ignoring detection limits biases in the results and even drastically lowers the power to detect active effects. Fortunately, the Custom Designer and Generalized Regression in JMP® make incorporating detection limits easy and automatic. In this presentation, we will use simulated versions of real designed experiments to show how to get the analysis right in JMP® Pro 17 and the pitfalls that will occur if detection limits are ignored in the analysis. We will also show how simple graphical tools can identify parts of the design region that could be problematic or even make it impossible to estimate certain model terms or interactions. Our examples will include an experiment designed to maximize the yield of a chemical product where the response is a reduction in the number of microorganisms in microbial susceptibility testing of consumer cleaning products.

15:00 - 15:45 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1316

Garbi 1

Measurement Systems Analysis for Curve Data Using Functional Random Effects Models

Colleen Mckendry, Senior Statistical Writer, JMP

Topic: Quality and Reliability
Level: III

This presentation is an extension of a case study presented at a Discovery conference a few years ago, where a client’s protocols required a Gauge R&R study to be performed before running a functional response designed experiment. As in a standard Gauge R&R study, there were several Parts, several Operators, and several replicates per combination of Part and Operator. However, in this case, the test equipment returned a set of curves as the response instead of a single point. A functional random effects model is appropriate for this type of data. In this application, the functional model is expanded using basis splines and then expressed as a mixed model, where variance components can be estimated using standard methods. This is done using the Functional Data Explorer and Fit Mixed platforms. Due to the functional model expansion, multiple variance components may be associated with each of the Part, Operator, and Part*Operator terms. It is shown that these variance components can be summed and written in the form of a standard Gauge R&R computation, therefore providing a Functional Gauge R&R analysis.
Session ID: 2023-EU-30MP-1261

Garbi 2

Multivariate Analysis of Infrared Spectra Using Wavelet Model in FDE

Giuseppe De Martino, Scientist, Topsoe
Chris Gotwalt, Chief Data Scientist, JMP

Topic: Data Exploration
Level: II

In catalyst development, tests to measure performances can be extremely time-consuming and expensive. In this study, we have explored the possibility of using faster and less expensive characterization data to validate mathematical models linking production parameters and performances. Specifically, we first modeled the production parameters to the performance data available in our dataset, using generalized regression, and from this model, we predicted a set of optimal production parameters. We then analyzed the Infrared Spectroscopy (IR) data using the Wavelet model in Functional Data Explorer plugging the production parameters as additional parameters. Thanks to this addition we were finally able to generate a synthetic spectrum for an optimal catalyst. The generated spectra combined with the predicted production parameters can be used by the scientist to more quickly understand the underlying mechanisms driving performances. Finally, a new catalyst material developed using the predicted parameters can be analyzed using IR and the synthetic spectra can be used to validate the model.
Session ID: 2023-EU-30MP-1203

Llevant 4

Sowing the Seeds of Love for DOE

Phil Kay, Senior Systems Engineer, JMP
Weronika Wrazen, Ph. D. Student, Hasso Plattner Institute

Topic: Design of Experiments
Level: I

There is a big problem with how we are educating our future scientists: we tell them that you are only allowed to change one thing in an experiment and you have to keep everything else the same. When trying to learn about the effect of many factors on a process or system, it is much more effective to change all your factors simultaneously. But people rarely learn about this method, "Design of Experiments" or "DOE." Or they only hear about it later in their careers when they are resistant to new ideas. The result is a huge waste of time and resources due to inefficient experimentation. In the summer of 2022, JMP® launched a competition with an engaging and simple experiment to demonstrate the power of DOE. In this presentation, you will hear from the contest winner and the designer of the experiment. You will hear how experimenters of all ages can get their hands dirty growing garden cress under different conditions according to a statistically designed experiment. And you will see how the results can be easily analyzed with compelling visuals, as well as using sophisticated Functional DOE analysis in JMP® Pro.

16:00 - 17:00 CET

Expo Hall and Mestral 2

Discovery Expo and JMP® Lab

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement, JMP® Lab and more.

18:30 - 21:30 CET

Finca Mas Solers

Dinner Adventure

A short ride from the hotel. Plan on fresh air, great food and warm hospitality in a casual outdoor setting.

Wednesday, 8 March

8:00 - 9:30 CET

Noray Restaurant

Breakfast

8:30 - 9:30 CET

Mestral 2

JMP® Lab

9:00 - 9:30 CET

Expo Hall

Discovery Expo

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement and more.

9:30 - 10:45 CET

Tramuntana

Plenary

Analytics Advocate Spotlight

Building a coalition: Lessons from W. L. Gore ’s culture of statistical enablement

Maria Lanzerath, Global Statisticians Team Leader, W. L. Gore & Associates
Mirco Lang, Quality Engineer, W. L. Gore & Associates
Valérie Nedbal, Global Technical Enablement Engineer, JMP
Meg Hermes, Moderator, JMP

Industrial statistics has transformative power. It makes science more reproducible. It increases yield and reduces scrap. It accelerates innovation and frees scientists and engineers to focus on delivering value through ideas, not just execution. But the potential for positive impact is limited when statistical practitioners operate in a vacuum. To amplify the impact of statistics, advocates often find themselves needing to identify a community of likeminded colleagues willing to help drive change.

In this session, Maria Lanzerath and Mirco Lang of W. L. Gore & Associates will share insights into how they have nurtured an interdisciplinary coalition working to optimize the impact of analytics. From where they sit in two very different parts of the organization, Lanzerath and Lang will compare and contrast their experiences with drivers of culture change. And they will leave the audience with 5 key lessons that can be applied to any organization, regardless of whether change is being driven from the top down or from the grassroots up.

11:00 - 11:45 CET

Expo Hall and Mestral 2

Discovery Expo and JMP® Lab

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement, JMP® Lab and more.

11:45 - 12:30 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1330

Garbi 2

How To Use JMP in Pharma Process Validation and Continuous Process Verification

Per Vase, Managing Consultant, NNE
Louis Meyer, IT Consultant, NNE

Topic: Quality and Reliability
Level: II

The three PQ batch concept in the pharmaceutical industry is being replaced by continued process verification. However, there is still a validation event (stage 2) before going into commercial manufacturing (stage 3). In stage 2, you are supposed to prove future batches will be good, and in stage 3, you are to prove that the validated state is maintained. If this can be done, there is no need for end-product testing any longer leading to large QC cost reductions. JMP has the ideal toolbox for both stages. If the process can be described with a model, prediction intervals with batch as a random factor can be used to predict the performance of future batches. To live up to the assumptions behind the model, JMP has an excellent toolbox to do the sanity check. Even cases with variance heterogeneity can be handled through weighted regression. A JMP script that combines the necessary tools described above to calculate control limits, prediction limits, and process capability in stages 2 & 3 will be demonstrated. The script has been heavily used by many of our customers. It only requires that data can be described with a model in JMP.
Session ID: 2023-EU-30MP-1295

Llevant 4

Innovative Approaches Using JMP: Two Case Studies on Predictive Modeling and Simulations

Damien Perret, R&D Scientist, CEA
François Bergeret, Senior Statistician, Ippon Innovation
Carole Soual, Chief Statistician, Ippon Innovation
Isabelle Giboire, CEA

Topic: Design of Experiments
Level: II

JMP software was initially implemented at CEA in 2010 by R&D teams who develop nuclear glass formulation. Over the years, JMP has been used for multiple purposes, such as data visualization of highly complex composition domains, optimal mixture designs, and machine learning techniques to create property-to-composition predictive models. More recently, JMP enabled us to develop very innovative methodologies. Two case studies will be presented. First, we will show an original approach based on an automatic and intelligent subsampling of the data, combining techniques of optimal designs and several predictive methods in JMP and JMP Pro to create very robust and accurate predictive models. Second, we will present an amazing benefit of using the Simulation platform where a response is below the limit of detection in the most part of the design space.
Session ID: 2023-EU-30MP-1329

Llevant 1

Using Graph Builder’s Splines To Align Measurement Curves

Bernd Heinen, Owner, Stabero

Topic: Data Access & Manipulation
Level: II

A frequent task in data analysis is aligning curves before a descriptive or root cause analysis. Often an additional complication occurs when the measurement intervals are not equidistant in the series to be compared. There is not one single value that quantifies the shift for a whole curve. Interpolation is the solution in cases like this. Simple linear interpolation may lead to numerous random errors; a spline interpolation is more robust. Since the Graph Builder exports the formula for the spline in its current shape, it became an easy, accessible tool for the alignment of curves. And as all steps can be programmed in JSL, it provides a framework for automating curve alignment. This presentation will describe the background, concept, and case study application for the alignment of curves.
Session ID: 2023-EU-30MP-1265

Garbi 1

Pythonless Python Integration for JMP®

Jarmo Hirvonen, Data Integration and Data Science Specialist, Murata Finland
Philip O'Leary, Data Integration Manager, Murata Finland

Topic: JSL Application Development
Level: III

Challenges with a JMP® and Python integration resulted in a search for an alternative solution that would allow for the evaluation and testing of the various Python libraries and powerful algorithms with JMP. This would enable JMP users to work with Python from a familiar JMP environment. After a few different iterations, a RestAPI service was developed, and when JMP calls this service, it dynamically creates a user interface based on the options the service currently provides. The JMP user can then utilize this user interface to employ different algorithms such as HDBSCAN, OPTICS, and UMAP by sending data directly from JMP in one click. After the algorithm has finished its operations on the server side, it will return data to JMP for further analysis and visualization.

12:30 - 14:00 CET

Noray Restaurant

Lunch

14:00 - 15:30 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2, and Mestral 4

Discussion Forums

New to Discovery Summit Europe this year, we’re introducing Discussion Forums to our in-person special segment to give JMP users unprecedented access to the people behind the software. Attendees will meet with members of JMP product management and development teams and other experts to talk about industry-related challenges and top initiatives for JMP 18 and beyond.

Pick which industry-oriented Discussion Forum you’d like to participate in:

Chemical
Pharmaceutical
Semiconductor
Consumer Products

Or, discuss what it takes to drive analytic excellence within your organization in the Analytics Advocate Discussion Forum:

How to be an Analytics Advocate

15:30 - 17:00 CET

Expo Hall and Mestral 2

Discovery Expo and JMP® Lab

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement, JMP® Lab and more.

19:00 - 21:30 CET

La Taberna del Puerto

Dinner by the Sea

Enjoy fresh and local, Catalan and Mediterranean cuisine in its purest state and delighting in the exceptional views of the Sitges fishermen’s wharves and marinas, all within walking distance of the Meliá hotel.

Thursday, 9 March

8:00 - 9:30 CET

Noray Restaurant

Breakfast

8:30 - 9:30 CET

Mestral 2

JMP® Lab

9:00 - 9:30 CET

Expo Hall

Discovery Expo

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement and more.

9:30 - 10:45 CET

Tramuntana

Plenary Session

Lessons from Brain Soup

Suzana Herculano-Houzel, Vanderbilt University

Brains are complex structures whose precise organization and connectivity makes us who we are. Who would have thought, then, that so much could be learned about human cognition, longevity, energetic cost and even evolution by turning brains into soup? In this talk, Suzana Herculano-Houzel tells the story of how she suspected that a number of "facts" about the human brain were really just intuitions, and set out to collect actual data on how many neurons different brains are made of, and why that matters.

11:00 - 11:45 CET

Expo Hall and Mestral 2

Discovery Expo and JMP® Lab

Come to the Discovery Expo for Meet-the-Experts opportunities, talk to User Enablement, JMP® Lab and more.

11:45 - 12:30 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1238

Llevant 1

A Method To Strategically Pre-process Data From Industrial Processes Before Storage and Analysis

Günes Pekmezci, Senior Expert for Industrial Internet of Things, Bundesdruckerei
Luís Fernando Ferreira Furtado, Senior Expert in Industrial Controllers and Robotics, Bundesdruckerei
Michael List, Manufacturing Engineer, Bundesdruckerei

Topic: Data Access and Manipulation
Level: II

Despite the development of new network and media technologies, the intense use of bandwidth and data storage could be a limiting factor in industrial applications. When recording sensor signals from multiple machines, a question must always be asked: which meaningful information could be extracted from the data and what should be saved for later analysis? The answer to this question is a method proposed and implemented by the Production Data Engineering Team at Bundesdruckerei GmbH in Berlin, a wholly-owned subsidiary of the German federal government that produces security documents and digital solutions. This method focuses on pre-processing data directly in the machine controller, strategically reducing the amount of data to send only the meaningful information to the network over OPC/UA, stored in the database, and further analyzed using JMP. A case study is presented, describing the implementation of this method in torque and position data from a servomotor used in a cutting process. The JMP Scripting Language is used to automatically generate reports of the cutting tool wearing, which is also analyzed in combination with the quality data of the product. Those reports allow the Production Engineers to understand the machines better and strategically plan tool changes.
Session ID: 2023-EU-30MP-1319

Garbi 2

Revisiting Pearl’s Influenza Studies Using JMP®

Roselinde Kessels, Assistant Professor, Maastricht University
Chris Gotwalt, Chief Data Scientist, JMP
Guido Erreygers, Professor of Economics, University of Antwerp

Topic: Data Exploration
Level: II

In 1919 and 1921, Raymond Pearl published four empirical studies on the Spanish flu epidemic. He explored the factors that might explain the epidemic’s explosiveness and destructiveness in America’s largest cities. Using partial correlation coefficients, he tried to isolate the net effects of the possible explanatory factors, such as general demographic characteristics of the cities and death rates for various diseases, on the variables measuring the severity of the epidemic. In this presentation, we revisit Pearl’s data and apply variable selection with a pseudo-variable in JMP®'s Generalized Regression platform instead of Pearl’s correlation analysis. We use Poisson forward selection on the variables in the platform with AICc validation. We find that our results largely correspond with Pearl’s conclusions but contain some additional nuances that are substantive. This paper contributes to the literature showing that Poisson regression proves useful for historical epidemiology. JMP’s Generalized Regression platform offers researchers much flexibility in choosing the most appropriate model.
Session ID: 2023-EU-30MP-1304

Llevant 4

The DOE Role Playing Game: Interactive Training of Research Chemists at Imperial College London

Benjamin Deadman, Facility Manager, Centre for Rapid Online Analysis of Reactions (ROAR), Imperial College London
Volker Kraft, Senior Academic Ambassador, JMP Academic Program

Topic: Design of Experiments
Level: I

Since 2018 the Centre for Rapid Online Analysis of Reactions (ROAR), in partnership with JMP, has trained more than 200 chemists and engineers in using Design of Experiments (DOE) for research. During this time, annual workshops have evolved to give new users an accessible, educational, and exciting introduction to DOE. This presentation will discuss the evolution of ROAR training workshops, some lessons learned along the way, and ways role-playing activities allow small groups to experiment with different DOE strategies in the classroom. Our role-playing activity places students in a small contract research organization. It tasks them with improving the outcome of a key reaction step in their client’s production of a target molecule. The activity allows them to apply their DOE knowledge and skills throughout the process, from problem definition and evaluation of different design strategies to proposing an optimized solution. Synthetic generation of data allows the students to get immediate feedback on their experiment designs. Random noise and blocking elements are included to give them an experience resembling the challenges of real physical experimentation with DOE.
Session ID: 2023-EU-30MP-1204

Garbi 1

Want To Know What Analysis You Need? Just Ask DAD

Peter Hersh, Senior Systems Engineer, JMP
Mia Stephens, Principal Product Manager, JMP

Topic: JSL Application Development
Level: I

When analyzing data, scientists and engineers often know what they want to accomplish but are unsure which statistical test is needed. This talk introduces a new Add-in, the Data Analysis Director (DAD). This Add-in was designed to make it easier to find the proper statistical test in JMP® based on the analysis task, goal, and type of data you have. DAD provides a guided flow to help you find the right analysis and run it in JMP. It includes built-in examples, links to JMP Help, demo videos, and even lets you launch the analysis on your data. As you will see, DAD is a useful tool that can help guide you along your analytic journey.

12:30 - 14:00 CET

Noray Restaurant

Lunch

14:00 - 14:45 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1305

Garbi 1

Disallowed Combinations and Operating Region Optimization for CQAs with the JMP® 17 Profiler

Laura Lancaster,Principal Research Statistician Developer, JMP

Topic: Design of Experiments
Level: II

The prediction profiler in JMP® is a powerful tool for visualizing and optimizing models from designed experiments. This presentation will focus on new features in the prediction profiler for exploring and optimizing models with known constraints and for determining factor ranges that assure quality as defined by the specifications associated with Critical Quality Attributes (CQA), thereby solving a fundamental Quality by Design (QbD) problem. While previous versions of JMP were able to create designs that respected disallowed combination constraints and combinations of factors that are known in advance to be physically impossible or undesirable, the model exploration and optimization in the profiler in the last step were unable to obey these constraints. We will demonstrate how the profiler, since JMP® 16, handles these complex design constraints automatically when exploring the model and performing optimization. We will also demonstrate how the Design Space Profiler, new in JMP® 17, finds subregions of the design space that maximize the probability of maintaining product quality for the CQA specifications while maintaining maximum flexibility. These two capabilities make the prediction profiler indispensable for a high-quality product and process innovation.
Session ID: 2023-EU-30MP-1347

Llevant 1

Don’t Lose Time Anymore: Automated Access, Visualization and Evaluation of Production Environments

Ole Lühn, Quality Assurance Manager, BASF

Topic: Data Exploration
Level: III

This presentation demonstrates how to access different production plant data to look into all corners of a production plant for quality assurance. JMP was used to access production, process, and quality data with one click. The presentation shows how data accessed via REST-API from an existing application was optimized by data import, data cleanup of input tables using JSL, and visualization of automated dashboards. Specification and control limit management for automated reporting was critical. Also, where data import possibilities were limited, a combination of Python and JMP was used to import process factors and responses for each production step of interest in mass production plants. A full range of quality assurance tools will be demonstrated, which could be used to begin helpful discussions with production teams for continuous improvement plans and PDCA Cycles.
Session ID: 2023-EU-30MP-1297

Llevant 4

The Earth, the Climate, and You

David Meintrup, Professor, Ingolstadt University of Applied Sciences

Topic: Data Visualization
Level: I

Climate change is a reality. The Paris climate goal of limiting global warming to 1.5 degrees is barely achievable. The only remaining question is: what can we still do to keep the consequences reasonably limited? How many conferences have you flown to last year? How many times a month do you eat meat? Do you drive to work? All of these questions matter, but how much? In this talk, we will try to find a data-based answer to this question using JMP as enabling software, and we will show how each one of us can contribute to preventing climate catastrophe. I am a mathematician, not a climatologist, but we need to get involved—all of us.
Session ID: 2023-EU-30MP-1309

Garbi 2

Using JMP® Pro Text Explorer To Improve Patent Intelligence

Florent Mathieu, Chemical Process Engineer, R&D, Michelin

Topic: Data Exploration
Level: II

Technology intelligence, especially patent intelligence, is a crucial step in the development of new technologies or new processes. This task is often tedious because it requires reading many patents. JMP Pro's text exploration and predictive modeling tools facilitate patent intelligence. First, patents must be identified as critical for a corpus of patents. The patent title, summary, and claims are analyzed with JMP's Text Explorer to associate each patent with a vector representing its lexical field (the Document Term Matrix). Next, a predictive modeling tool, such as neural networks, is used to predict the probability that a patent is critical. Once the machine learning is complete, it is possible to identify, in a fraction of a second, the relevant patents to be read within an extended patent corpus. Once implemented, this methodology accelerates the patent intelligence process, broadens the search scope and limits the risk of missing critical patents. This presentation demonstrates the process of developing this methodology for patent intelligence.

15:00 - 15:45 CET

Llevant 1, Llevant 4, Garbi 1, Garbi 2

Paper Presentations

Session ID: 2023-EU-30MP-1272

Garbi 1

A Family of Orthogonal Main Effects Screening Designs for Mixed Level Factors

Bradley Jones, JMP Distinguished Research Fellow, JMP

Topic: Design of Experiments
Level: III

There is scant literature on screening when some factors are at three levels and others are at two levels. Two well-known and well-worn examples are Taguchi's L18 and L36 designs. However, these designs are limited in two ways. First, they only allow for either 18 or 36 runs, which is restrictive. Second, they provide no protection against bias of the main effects due to active two-factor interactions (2FIs). In this talk, I will introduce a family of orthogonal, mixed-level screening designs in multiples of eight runs. The 16-run design can accommodate up to four continuous three-level factors and up to eight two-level factors. The two-level factors can be either continuous or categorical. All of the designs supply substantial bias protection of the estimates of the main effects due to active 2FIs. I will show a direct construction of these designs (no optimization algorithm necessary!) using the JSL commands Hadamard product and direct product.
Session ID: 2023-EU-30MP-1293

Garbi 2

Industrial Data Science for Batch Manufacturing Processes

Mattia Vallerio, Advanced Process Control Specialist, Solvay
Francisco Navarro, Industrial Data Scientist, Solvay
Carlos Perez-Galvan, Industrial Data Scientist, Solvay

Topic: Data Exploration
Level: II

Batch processes are subject to high variability: raw material composition, initial condition, unit degradation, and their intrinsic dynamic nature. Additionally, they are characterized by several distinct phases and steps that drastically change the conditions during the manufacturing process. In this presentation, we will illustrate with an industrial example how to use data science and machine learning to convert this high variability and apparent excess of data into valuable information. First, we will show how to summarize batch properties into features and use the open-source Predictor Explainer Add-in to identify the most relevant ones using AutoML and ExplainableAI. Then, we will discuss the need to align the data timewise before performing trajectory analysis, briefly introducing the pros and cons of different methodologies to achieve this result. Finally, we will dive into trajectory analysis. In this last step, we will use the Functional Data Explorer functionality of JMP Pro to monitor and identify deviations. Analyzing these deviations will lead us to identify key process control improvements to optimize production further.
Session ID: 2023-EU-30MP-1278

Llevant 1

Using JMP To Manage a Learning Program To Develop the Next Generation of JMP Data Ninjas

Trish Roth, Principal Scientist, Abbott Laboratories
Jeff Pennoyer, Manager Environmental Monitoring and Microbiology, Abbott Laboratories

Topic: Data Exploration
Level: I

Many know JMP as a powerful tool for analytics and modeling and aspire to leverage JMP’s advanced capabilities to champion improvements and business understanding. It can take time and domain experience to achieve a high level of proficiency. Don’t dismay; we all start somewhere! Even at modest experience levels, value can rapidly be achieved using JMP fundamentals. Fundamentals can be quickly propagated across an organization to seed and inspire a culture of analytics. Hear how our team has integrated offerings from JMP education in a JMP “boot camp” format. The faster an organization can establish basic proficiency in JMP, the sooner it can benefit from that investment. Additionally, having a shared platform for both basic and advanced analytics creates a collaborative community, increases self-sufficiency, and provides a learning path to foster employee development. While sharing our training approach, we will demonstrate foundational JMP features, including data filters, tabulate, summary, recode, column formula, and column properties functions to track student progress. See JMP in action as we highlight methods to construct, customize and journal graph builder visuals in ways that entice spreadsheet users to make the “JMP” to becoming JMP data ninjas.

16:00 - 17:15 CET

Tramuntana

Plenary Session

The Joy of Data

Hannah Fry, Professor in the Mathematics of Cities

I’ve spent the last decade working with data, hunting for mathematical patterns in human behaviour. In that time, I’ve come across some incredible stories - written solely in the numbers - that get right to the heart of who we are as people.

In this optimistic talk, I’ll share some extraordinary tales about what’s happening at the very cutting edge of data science – a host of surprising and delightful stories that demonstrate how far you can go when we look back at ourselves through the eyes of data. And I’ll show you how a mathematical view of what it means to be human can shape the way we design our society, from dating and healthcare to catching serial killers, and everything in between.

17:30 - 19:00 CET

Meliá Atrium

Meet the Author Hannah Fry and Closing Reception

We hate to say goodbye as much as you do. That’s why we always build in last-chance networking opportunities. Finish those conversations, make one more new-feature request, and exchange phone numbers because, really, statistical discovery should never end.