Online Agenda

Tuesday, 10 March

13:00 - 16:30 CET

  • Session ID: 2020-EU-TUT-529

    Introduction to JMP® Live: Use and Administration

    Brian Corcoran, JMP Director of Research and Development, SAS

    Dieter Pisot, JMP Principal System Engineer, SAS

    Eric Hill, JMP Distinguished Software Developer, SAS

    • Topic: Data Visualization and Exploration
    • Level: 1

    You know the value of sharing insights as they emerge. JMP Live — the newest member of the JMP product family — reconceptualizes sharing by taking the robust statistics and visualizations in JMP and extending them to the web, privately and securely. If you'd like a more iterative, dynamic and inclusive path to showing your data and making discoveries, join us. We'll answer the following questions: What is JMP Live? How do I use it? How do I manage it? For background information on the product, see this video from Discovery Summit Tucson 2019 and the JMP Live product page.

Wednesday, 11 March

11:00 - 11:45 CET

  • Session ID: 2020-EU-45MP-427

    Digital Analytics Boosted With JMP® Integration to Google Cloud

    Alfredo López Navarro, Data Lab Manager, Telefónica

    Arne Ruhkamp, Senior Digital Analyst, Telefónica

    • Topic: Data Exploration
    • Level: 1

    Step into the world of digital analytics with a hybrid approach. When it comes to statistical analysis, web analytics tools are limited. JMP boosts insights by bringing a flexible platform. It allows us to aggregate, cleanse, explore and interact with different types of data in an agile way. In this showcase we will 1) share with you how business can benefit from cross-functional teams, 2) give a live demo on how to connect to Google Analytics through JMP, 3) merge the web analytics data with other data sources, and 4) generate and deliver the insights. In the way we managed to break silos, we changed our working culture and improved our performance. There is still a long way to go. Our intention is to share all the materials with the JMP User Community, data sets, journals and a booklet.

11:50 - 12:20 CET

  • Session ID: 2020-EU-30MP-458

    See Fer Yer Sen: The Importance of Data Exploration, a JMP Live Showcase

    Phil Kay, JMP Senior Systems Engineer, SAS

    • Topic: Data Exploration
    • Level: 1

    People and organizations make expensive mistakes when they fail to explore their data. Decision makers cause untold damage through ignorance of statistical effects when they limit their analysis to simple summary tables. In this presentation, you will hear how one charity wasted billions of dollars in this way. You will learn how you to easily avoid these traps by looking at your data from many angles. An example from media reports on "best places to live" will show why you need to look beyond headline results. And how simple visual exploration – interactive maps, trends and bubble plots – gives a richer understanding. All of this will be presented entirely through JMP Public, showcasing the latest capabilities of JMP Live.

12:30 - 13:15 CET

  • Session ID: 2020-EU-45MP-313

    Optimization of a Chemical Looping Process by Optimal DOE and Statistical Modeling

    Frank Deruyck, Lecturer, University College Ghent

    • Topic: Design of Experiments
    • Level: 2

    In this presentation, an optimal DOE and statistical models are created to maximize performance of a chemical looping process with CO2 capture to generate H2 and synthesis gas, potential new recourses for energy and circular economy. The complex fluidized-bed reactor used is subject to several possible interacting and quadratic effects, as well as random noise, so a thoughtful experimental and modelling strategy is necessary. The DOE and analysis platforms in JMP offer a wide variety of DOE preparation and model fitting options. This paper will illustrate how to decide between an orthogonal RSM, custom DOE and a DSD based on R&D criteria and goals, and model objectives and DOE diagnostics such as power, factor correlation and variance profile. Model building occurs by screening out effective factors using stepwise regression (fixed factor forward selection and all possible models) followed by REML analysis eliminating random noise variance. Useful models for methane conversion and synthesis gas yield are obtained and supported by additional validation experiments. The profiler desirability function is used to compute the optimal operation conditions. This work demonstrates the possibility of optimizing a complex technological process with a careful DOE setting and statistical modeling approach.

13:20 - 13:50 CET

  • Session ID: 2020-EU-30MP-471

    Biological Products and Stability: Linear and Nonlinear Modeling

    Thomas Brisset, Stability Platform Manager, Stallergenes Greer

    • Topic: Predictive Modeling
    • Level: 2

    Stability studies are a key part of pharmaceutical product development. They help justify shelf and storage conditions. By using a stability data modeling approach, the laboratory can characterize its product and perform shelf life extrapolation. This approach can help also in the definition of acceptance criteria of quantitative parameters. In the context of biological product development, we studied physico-chemical and immunological parameters using different JMP platforms - Graph Builder, Linear Model, Stability - which integrates regulatory constraints. The objective of the presentation is to explain the approach to study stability data, to highlight the different issues and to exhibit how statistical modeling can represent a decision support process.

14:00 - 14:45 CET

15:00 - 16:00 CET

Plenary

  • JMP 15 and JMP Pro 15 give you more options for exploring and analyzing your data interactively. From enhanced data preparation and modeling to instant graphical gratification, you’ll discover new ways to access and understand your data. You’ll also find a new way to publish, share and communicate those findings.

Thursday, 12 March

11:00 - 11:30 CET

  • Session ID: 2020-EU-30MP-414

    SIFTomics and Data Analytics: The Quickest Way to Unravel the Totality of Your Chemical Space

    Camilla Liscio, Senior Application Chemist, Anatune

    Jamie Minaeian, Application Chemist, Anatune

    • Topic: Data Exploration
    • Level: 2

    In a world of increasing complexity, analytical chemists must unravel the entirety of the chemical space of products and materials. On this never-ending quest from complexity to clarity, data analytics becomes an essential tool. VOCs are known to impart an odor to products. The traditional approach to quantifying odor uses a sensory panel, which is expensive and can be subject to problems brought about by fatigue. Selected ion flow tube mass spectrometry (SIFT-MS), however, can selectively detect and quantify a wide range of odor compounds in real time, more cost-effectively. The challenge is how to make sense of the rich data set generated by fast SIFT-MS analysis.This is where JMP machine learning and multivariate analytics brings clarity by enabling extraction and understanding of the most important chemical insight. This talk will demonstrate the synergistic power of SIFT-MS analysis combined with chemometrics to characterize the chemical space of odor compounds in a real application scenario.

11:35 - 12:05 CET

  • Session ID: 2020-EU-30MP-356

    Using Simulation Methods in JMP® to Prevent Supply Chain Fires

    Stephen Pearson, Specialist Data Scientist, Syngenta

    • Topic: Design of Experiments
    • Level: 2

    Many powdered materials slowly oxidize with time, which generates heat. If in a bulk form (such as during transport or storage) then heat generation can exceed heat loss, leading to ignition. Climate control and limiting packing amounts can reduce the risk, but this increases costs for the consumer through reduced logistical options, larger shipping volumes and disposal of additional packaging. Laboratory tests are well established to determine a safe packing size. However, they are costly, especially for new products where limited amounts of material are available. The physics of the oxidation process can be simulated, provided all the material properties are known. Using JMP, we will demonstrate how to combine these two approaches to reduce the amount of thermal stability testing required: 1) generate a constrained spacing-filling experimental design; 2) control the simulation software (COMSOL Multiphysics) via JSL; 3) build meta-models; 4) simulate the outcome for new materials. By obtaining estimates of different material properties with each test, the prediction uncertainty can be updated to suggest the range of suitable packaging given the available data. This enables a data-driven approach to the selection of laboratory tests.

12:15 - 12:45 CET

  • Session ID: 2020-EU-30MP-371

    Data Exploration and Discovery in Multi-Isotope Imaging Mass Spectrometry (MIMS) in Cancer Research

    Greg McMahon, Principal Research Scientist, National Physical Laboratory (UK)

    • Topic: Data Exploration
    • Level: 2

    Multi-isotope imaging mass spectrometry (MIMS) combines stable isotope labeling of biological samples with high spatial resolution (sub-cellular) mass spectrometry imaging and extensive statistical analysis of the resultant image data. The images are rich in information, and use of JMP allows a quick and easy method of analyzing the data for information that is either just subtly contained within the image, or other information that may be below the first "obvious" layer of information. Combining Graph Builder with simple data distributions and local data filters provides a wealth of information. The approach can be extended by application of cluster analysis and multivariate statistics. In this presentation, we will use an example tracking the metabolic fate of 13 C and 18 O stable isotope labeled glucose in mouse breast cancer tumors engineered to contain cells with either high or low levels of the Myc oncogene, which is a driver for aggressive breast cancer growth. We will finish with a few comments about the significance of the results in terms of cancer research for the non-expert.

12:50 - 13:35 CET

  • Session ID: 2020-EU-45MP-429

    A Practical Road Map for Implementing Industry 4.0 Using Custom SQL Databases and JMP® 15

    Joseph Beauchemin, Jr., Director of Quality (Non-Ferrous), Hitchiner Manufacturing

    Philip Ramsey, Principal Lecturer, University of New Hampshire; and Owner, North Haven Group

    • Topic: Data Access and Manipulation
    • Level: 2

    Industry 4.0 (I4.0) is an initiative to transition organizations to the digital revolution and guide the creation of smart factories. Despite confusion about I4.0, one consequence is the proliferation of large amounts of data within organizations. We present a framework to manage many data streams resulting from I4.0 and propose standardized workflows for analytics to drive process improvements. JMP statistical software is a solution for data analyses and reporting. Standard Work and JMP are used to: Identify data requirements and collection strategies; create custom SQL databases; perform standardized analyses in JMP via custom scripts; and create dashboards with JMP for management reviews. The range of analytical capabilities and scriptability of JMP make it key to Standard Work. The JMP Query Builder is essential in accessing SQL databases that link all of the relevant data sources, while automatically integrating various JMP data analyses. A case study using JMP and Standard Work shows an advanced manufacturing company reduced data correction and formatting time from 90% to less than 10% of project time and increased yields from 10% to over 90%. JMP platforms used are: Query Builder, Process Screening, Predictor Screening, Response Screening, Model Driven Multivariate Control and Functional Data Explorer.

13:45 - 14:15 CET

  • Session ID: 2020-EU-30MP-447

    Measurement Systems Analysis for Curve Data

    Astrid Ruck, Senior Specialist in Statistics, Autoliv

    Christopher Gotwalt, JMP Director of Statistical Research and Development, SAS

    Laura Lancaster, JMP Principal Research Statistician Developer, SAS

    • Topic: Quality and Reliability
    • Level: 2

    Measurement systems analysis is a measurement process consisting not only of the measurement system, equipment and parts , but also the operators, methods and techniques involved in the entire procedure of conducting the measurements. Automotive industry guidelines such as AIAG [1] or VDA [4] investigate a one-dimensional output per test, but they do not describe how to deal with data curves as output. In this presentation, we take a first step by showing how to perform a gauge repeatability and reproducibility (GR&R) study using force vs. distance output curves.  The Functional Data Explorer in JMP Pro is designed to analyze data that are functions such as measurement curves, as those which were used to perform this GR&R study. 

14:20 - 14:50 CET

  • Session ID: 2020-EU-30MP-404

    Simple Process Monitoring of Multiple Parameters Using JMP®

    Torsten Weber, Engineer Process Integration, Heliatek

    • Topic: Data Visualization
    • Level: 2

    The paper will discuss the application of JMP at Heliatek in terms of process monitoring in a pilot production environment. In a running production it is a challenge to keep track of multiple control charts simultaneously. The contribution describes an alarm dashboard compiled in JSL, which monitors multiple process parameters and visualizes critical limit exceedings in a simple way. The application counts the limit violations in a defined time frame of multiple components and depicts the results in a heat map. Database queries continuously update the data. This presentation will explain in detail:  How to run this application in a loop to react as soon as possible to critical process variations.  How to solve issues regarding automatic alarm emails without using the „mail()“ or „alarm script()“ function of JSL  How to share this alarm board in a network via customized HTML report to minimize interrupting „hangover“ while updating the data.  This application helps to enhance the production yield of organic-PV products by a simple visualization of multiple process parameters and therefore shortens the response time.

15:00 - 16:00 CET

Plenary

  • The Art of Statistics

    David Spiegelhalter, University of Cambridge

    The Art of Statistics

    Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way numbers can be used to support sensationalized claims, whether political or scientific. As data becomes more influential in our society, data literacy becomes an increasingly essential skill. This means a new approach to statistics education is necessary, in which real problems provide motivation for ideas, and technicalities are delayed as long as possible.

    In his new book, David Spiegelhalter uses this approach to construct a first course in statistics driven by questions such as:

    • Could Harold Shipman have been caught earlier?
    • Should he take a statin?
    • Who was the luckiest passenger on the Titanic?
    • Why do old men have big ears?  

    Thus is the true power of statistical science revealed.

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