Live In-Person Event

A JMP Discovery Seminar with NNE

Date: 15 April 2026
Time: 13:00 - 16:00
Location: NNE - Novo Nordisk Engineering, Bredevej 2, 2830 Virum, Denmark
Registration: Free, but registration is required.

Process capability remains one of the most widely used – and often misunderstood – tools for assessing how well a process can meet specifications. While classical Cp/Cpk calculations assume stable, normal, single‑mode data, real‑world manufacturing and analytical processes rarely behave so neatly. Multiple machines, raw‑material sources, tools, operators, and batch effects can create complex distributions, often producing misleading capability results if analyzed with standard methods.

In this in-person session, we explore a modern and more robust approach to capability analysis using JMP. Learn how to detect when normality assumptions fail, how to visualize and understand complex distributions, and how to apply the right statistical tools to obtain meaningful, reliable capability metrics. Whether you work in manufacturing, medical devices, pharma, bioprocessing, or other high‑precision industries, this session provides the necessary foundation to evaluate performance with confidence and clarity.

Reserve your spot now! Limited seats are available.

Guest contributions: Industry perspectives and practical methods

Novo Nordisk: Process Capability on Injection Moulding with Cavity Differences

Novo Nordisk shares how it calculates capability for injection‑moulding processes, where differences between cavities naturally produce multimodal data sets. This demonstration shows how JMP helps separate cavity effects, visualize the true process behavior, and derive capability metrics that reflect real manufacturing performance – essential for high-volume, high‑precision medical device production.

Coloplast: Capability Beyond Normality – Comparing Best Fit, Smoothed, and Model Based Approaches

Coloplast presents practical examples of capability evaluation when data violates normality. the presenters compare best‑fit distributions, smoothed distributions, and model‑based approaches in JMP to show how each method influences capability outcomes. This session provides valuable insights into selecting the right modelling approach to support quality decisions and regulatory expectations.

Any quality engineers, process scientists, analytical development teams, and manufacturing professionals who want to deepen their understanding of capability analysis and ensure their decisions are based on accurate, realistic performance indicators should attend.

NNE: Using Normal Mixture Quantiles and Distributions in JMP

NNE demonstrates how normal mixture quantiles and mixture distributions in JMP can be used to calculate capability both with and without confidence intervals. This approach is especially powerful when the data is multimodal or influenced by multiple underlying sources, providing a far more realistic view of process performance than standard normal-based indices.

Don't miss this opportunity to expand your data analysis skills and unlock the full potential of JMP!

Questions? Marija Lind from JMP is here to answer them marija.lind@jmp.com