| |
(Main - Presenter Information) Last Name |
(Main - Presenter Information) Organization |
(Main - Abstract Information) Industry |
Abstract Name First Value |
| 1 |
Betteridge |
Accord Healthcare |
Pharmaceutical |
Using JMP Workflow Builder to Automate Analysis of an Annual Verification of a Spectrometric Method. |
| 2 |
Steele |
AkzoNobel |
Consumer Products |
Use of JMP for restructuring and analysis of DoE data for pigment stability optimisation |
| 3 |
Fetaiha |
Al Quds university |
Medical Statistics (CRO, Providers, Medical Research) |
Oral Health Status of Diabetes Mellitus Patients Attending Primary Health Centers at Palestine |
| 4 |
Nagy |
Alvotech Germany |
Biotech |
Accelerated at-line amino acid analysis by using JMP add-in feature from 908 Devices |
| 5 |
Yu |
Applied Materials |
Industrial Manufacturing |
Case Study for Approaches to Enhance Robustness of SPC Control Limits |
| 6 |
Shen |
Applied Materials |
Semiconductor |
GRR Analysis of Effects from Measurement Queue Time on SiO2 Thin Film Thickness |
| 7 |
Gupta |
Applied Materials |
Semiconductor |
Review the process parameters data to identify the correct hardware design |
| 8 |
Kaushal |
Applied Materials India |
Semiconductor |
Dynamic JMP Dashboard for optimizing tool maintenance in Semiconductor Processes |
| 9 |
Bertelsen |
Arla Foods amba |
Consumer Products |
Unlocking Dairy Excellence: A Journey trough Robust Processes using JMP |
| 10 |
Stuyck |
BASF Antwerpen |
Chemical |
Joining forces in higher education: A role-model from BASF and KU Leuven |
| 11 |
Heinen |
Bernd Heinen |
Cross Industry |
Cause and Effect Diagram, the Hidden Champion - Visualize Complex Structures |
| 12 |
Kühlborn |
Boehringer Ingelheim |
Pharmaceutical |
Dynamic DoE: A Novel Methodology for Time-Dependent Design of Experiments in Chemical Development |
| 13 |
Kühlborn |
Boehringer Ingelheim |
Pharmaceutical |
Dynamic DoE: A Novel Methodology for Time-Dependent Design of Experiments in Chemical Development |
| 14 |
Kunzelmann |
Boehringer Ingelheim Pharma GmbH & Co KG Biberach |
Pharmaceutical |
FUNCTIONAL DESIGN OF EXPERIMENT FOR POTENCY ASSAY OPTIMIZATION AND IN-SILICO SIMULATION |
| 15 |
Kienzle |
Boehringer Ingelheim Pharma GmbH & Co. KG |
Pharmaceutical |
Statistical analysis of memory effects in mammalian cells during intensified Design of Experiment |
| 16 |
Pekmezci |
Bundesdruckerei |
Industrial Manufacturing |
A case study of JMP Live integration with Python for production systems |
| 17 |
Schafheutle |
Business Consulting |
Cross Industry |
Data analytics of sports data collected by a smart watch |
| 18 |
GERUS-DURAND |
Cerba Research |
Biotech |
Cutting Costs, Elevating Quality: DOE's Impact on Immunohistochemistry Clinical Protocol |
| 19 |
Gouttebroze |
Clecim |
Industrial Manufacturing |
ZINC COATING EXCELLENCE: LEVERAGING JMP FOR ACCURATE PRESSURE CONTROL AND THERMODYNAMIC MODELING |
| 20 |
Helm |
Croda Europe Ltd |
Consumer Products |
Advancing Formulation Science in Personal Care |
| 21 |
Kopac |
Culmium |
Industrial Manufacturing |
Predicting Effluents from Glass Melting Process for Sustainable Zero-Waste |
| 22 |
Liscio |
Element |
Other |
The many faces of Design of Experiments: stories from an Analytical Chemist |
| 23 |
Appleyard |
Fujifilm Diosynth Biotechnologies |
Biotech |
What is the real impact of your DoE factors: Automating Impact Ratio calculations with JSL |
| 24 |
Taylor |
GSK |
Pharmaceutical |
A medley of examples how JMP has made my job easier in the Biopharmaceutical Industry |
| 25 |
Paduan |
H. Lundbeck A/S |
Pharmaceutical |
In-process optimization of a drying procedure using Functional Data Explorer |
| 26 |
Paduan |
H. Lundbeck A/S |
Pharmaceutical |
Development of new in-process control method |
| 27 |
Miletic |
Hemofarm STADA |
Pharmaceutical |
Definitive screening design & advanced predictive modeling as useful tools in product development |
| 28 |
Cuvillier |
Ippon Innovation |
Other |
Machine Learning Methods on Industrial Data |
| 29 |
Wise |
JMP Statistical Discovery LLC |
Cross Industry |
Pictures from the Gallery 9: Innovative Graph Builder Views |
| 30 |
Barker |
JMP Statistical Discovery LLC |
Cross Industry |
Catching the wave: A closer look at Wavelets in the Functional Data Explorer |
| 31 |
Goff |
JMP Statistical Discovery LLC |
Cross Industry |
Administrating JMP Live in 18.0 – Spaces, Permissions, and Active Directory |
| 32 |
Chilton |
JMP Statistical Discovery LLC |
Cross Industry |
Leveraging Control Charts for Enhanced Process Monitoring in JMP® Live |
| 33 |
Dudley |
JMP Statistical Discovery LLC |
Cross Industry |
Can Short Run Control Charts Save Your Process? |
| 34 |
Polito |
JMP Statistical Discovery LLC |
Cross Industry |
Every day DOE: How mundane DOE's provide insight into designing more effective industrial DOE's |
| 35 |
King |
JMP Statistical Discovery LLC |
Cross Industry |
CSALT: Adding a Pinch of Flavor to the Accelerated Life Test Planning Experience |
| 36 |
Rhyne |
JMP Statistical Discovery LLC |
Cross Industry |
Assessing Statistical Software using Covering Arrays – A Case Study of Testing Easy DOE |
| 37 |
Corcoran |
JMP Statistical Discovery LLC |
Cross Industry |
Data Connectors - a new JMP initiative to ease data access |
| 38 |
Saanchi |
JMP Statistical Discovery LLC |
Education |
Sample Size Explorers: An Excellent Aid for Teaching Power, Confidence Intervals ... and Beyond |
| 39 |
McCormack |
JMP Statistical Discovery LLC |
Cross Industry |
How to Design and Analyze Experiments with Pass/Fail Responses |
| 40 |
Vogt |
JMP Statistical Discovery LLC |
Cross Industry |
Tolerating Input Variation - Analyses and Predictions in the most variable systems: Hobby Athletes. |
| 41 |
Hersh |
JMP Statistical Discovery LLC |
Cross Industry |
Extending JMP capabilities using Python integration |
| 42 |
Cooper |
JMP Statistical Discovery LLC |
Cross Industry |
Maximizing JMP Data Analysis Workflow Efficiency with Generative AI |
| 43 |
Giuliano |
JMP Statistical Discovery LLC |
Cross Industry |
Revolutionizing Leadership Assessment & Team Building: Building a New Generation of JMP Leaders |
| 44 |
Ding |
JMP Statistical Discovery LLC |
Cross Industry |
Using a JMP App to Show Who is the GOAT of Men’s Tennis? |
| 45 |
Ding |
JMP Statistical Discovery LLC |
Pharmaceutical |
Equivalence Testing Using JMP |
| 46 |
Tiffany-Davis |
JMP Statistical Discovery LLC |
Cross Industry |
JMP Live is for you too - how to use the content that your colleagues publish to JMP Live |
| 47 |
Lancaster |
JMP Statistical Discovery LLC |
Industrial Manufacturing |
Recent Improvements in Large-Scale Process Screening |
| 48 |
Hill |
JMP Statistical Discovery LLC |
Cross Industry |
JMP Live 18.0: Communicating JMP Insights Gets Even Easier |
| 49 |
Demel |
JMP Statistical Discovery LLC |
Cross Industry |
Graph Builder 30-sec-Challenge |
| 50 |
Hecht |
JMP Statistical Discovery LLC |
Chemical |
New Features in JMP's AVEVA / OSIsoft PI Importer |
| 51 |
Kussener |
JMP Statistical Discovery LLC |
Industrial Manufacturing |
Should I bring my umbrella to Manchester? Analogy of an industrial process monitoring |
| 52 |
Nelson |
JMP Statistical Discovery LLC |
Cross Industry |
JMP and Python the Next Step |
| 53 |
Dong |
JMP Statistical Discovery LLC |
Medical Statistics (CRO, Providers, Medical Research) |
Causal Inference for Observational Data in JMP Pro using SEM, Propensity Scoring, & Machine Learning |
| 54 |
Worley |
JMP Statistical Discovery LLC |
Cross Industry |
Building an Analytic Workflow Based on Wavelet Modeling of Chemometric Data |
| 55 |
Wolfinger |
JMP Statistical Discovery LLC |
Cross Industry |
Introducing the Torch Deep Learning Add-In for JMP Pro |
| 56 |
Cobb |
JMP; The University of North Carolina at Chapel Hill |
Cross Industry |
Analytics in the 21st Century: How to Educate a Workforce to be Truly Data Literate |
| 57 |
Fish |
Johnson Matthey |
Chemical |
A Mixture/Process Experimental Design and SVEM Analysis for an Esterification Reaction |
| 58 |
Gomez Jimenez |
Johnson Matthey PLC |
Chemical |
Utilising DoE and the Prediction Profiler for creating Sustainable Formulations |
| 59 |
Berdiuzhenko |
Jotun A/S |
Chemical |
Overcoming limits of scale-down models/experiments with analyzing multidimensional production data |
| 60 |
Berdiuzhenko |
Jotun A/S |
Chemical |
Using FDA to reveal connection between Roughness Profile and Surface Drag for Antifouling Coatings |
| 61 |
GUILLER |
L’Oréal |
Consumer Products |
Synergy between Design of Experiments and Machine Learning for Enhanced Domain Expertise |
| 62 |
Portmann |
Lonza |
Pharmaceutical |
Using microbial metabolic profiles to improve scale up in process characterization studies |
| 63 |
Hirvonen |
Murata Electronics Oy |
Cross Industry |
Mastering the Art of Scripting Seamless JMP-Like User Interfaces with Structured JSL |
| 64 |
Vase |
NNE |
Pharmaceutical |
Cpk, a great concept not always being used properly |
| 65 |
Vase |
NNE |
Pharmaceutical |
Do you have too many Out of Specification Results? |
| 66 |
Vase |
NNE |
Pharmaceutical |
Reduce cost and avoid non-conformities doing smart Shelf-Life calculations in JMP |
| 67 |
Meyer |
NNE |
Pharmaceutical |
Data Driven Specification Limits on Limited Amount of Data |
| 68 |
Korsgaard |
NNE |
Pharmaceutical |
Improving fitting of assay curves using advanced weighted regression |
| 69 |
Bladt |
NNE |
Cross Industry |
The pitfalls of current p-charts (and how to fix it) |
| 70 |
Oxenboell |
Novo Nordisk |
Pharmaceutical |
One size does not fit all – how to customize your JMP Clinical reports |
| 71 |
BOURLON |
NXP |
Semiconductor |
Innovative Methods for Establishing Functional Data Equivalence for Improved RF Comparison Testing |
| 72 |
BOURLON |
NXP |
Semiconductor |
A Novel Way of Using (Functional)-DOE to Reduce a Radar Chip Validation Cycle Time |
| 73 |
BERGES |
NXP Semiconductors |
Semiconductor |
Root cause searching on a yield loss in automotive industry, by multivariate analysis and modeling |
| 74 |
Pehrson |
Orsted |
Clean Energy (Wind, Solar, Battery, Nuclear) & Conservation |
Going quantitative: Text Analysis on Surveys and Voice of the Customer |
| 75 |
Ho |
Pharmaron Biologics UK |
Biotech |
Utilising HTPD and DoE to Optimise the Pharmaron Gene Therapy Platform |
| 76 |
Sorrentino |
Pirelli Tyre SpA |
Industrial Manufacturing |
Consolidation and integration of data workflows to guarantee manufacturing process robustness |
| 77 |
Herud-Sikimic |
Rentschler Biopharma SE |
Pharmaceutical |
Integrating JMP data exploration and python machine learning capabilities |
| 78 |
Silbersack |
Roche Diagnostics International AG |
Pharmaceutical |
Automation Approach Using JMP Scripting Language |
| 79 |
Wells |
Roche Products Ltd |
Pharmaceutical |
QbD in Clinical Trials: Industry Status, Challenges, ICH guidelines and Statistical considerations |
| 80 |
Raming |
Siltronic AG |
Semiconductor |
Data cockpit: Ways to enrich a master table on click with additional data |
| 81 |
Brammer |
Solvay |
Chemical |
Control Charting Dynamic processes |
| 82 |
Perez-Galvan |
Solvay |
Industrial Manufacturing |
Comparison of different data-driven methods for inferential modelling in the process industry |
| 83 |
Campanelli |
Solvay |
Industrial Manufacturing |
Mixture Design in Aerospace |
| 84 |
Porto |
STMicroelectronics |
Semiconductor |
Automated data analysis of a thermal test bench for microelectronic packages |
| 85 |
patelmo |
STMicroelectronics |
Semiconductor |
Exploiting JMP Pro to Model Outlier Distributions in Semiconductor Process Development |
| 86 |
Pearson |
Syngenta |
Chemical |
Using JMP to Build Soft Sensors for Efficient Monitoring of Chemical Production Processes |
| 87 |
Barnett |
Syngenta |
Chemical |
Analysis of Images Using Machine Learning Torch Add-In in JMP 18EA |
| 88 |
Holt |
Syngenta Ag |
Chemical |
Automated binary blend visualisation - from database to data visualisation using Workflow Builder |
| 89 |
Pickburn |
Synthomer |
Chemical |
Using Candidate files to ensure run processability across a design space in Mixture DoE |
| 90 |
Buzoianu |
Tonisity International |
Other |
Tonisity - Our Journey From Excel to JMP Automations |
| 91 |
Cook |
Unilever |
Cross Industry |
Building a global community for digital-first approach to innovation and sustainability at Unilever |
| 92 |
Winnifrith |
University of Oxford |
Pharmaceutical |
DOE, Automation, and Functional Data Modelling rapidly optimise a novel assay of RecBCD |