Dennis Lendrem explains why design of experiments is essential for discovery
Dennis Lendrem’s LinkedIn newsletter, Apes in Lab Coats, has spawned two books.
Dennis Lendrem’s LinkedIn newsletter, Apes in Lab Coats, has spawned two books.
Since its launch in October 2024, the JMP Marketplace has served as a central hub for secure, quality-controlled JMP extensions. To offer you the best possible experience, we're streamlining our platforms and phasing out the File Exchange.
"I’m not tech savvy. I just don’t get math. It’s like a foreign language. I can’t do this." - Kirsten Boyd, Newburyport High School
Our popular Statistical Thinking for Industrial Problem Solving (STIPS) course, which is hosted by our colleagues in SAS Education, is being transitioned to the new SAS learning platform.
The Monty Hall problem is a fun and seemingly paradoxical thought experiment that has confounded many smart people. It happens to be fairly straightforward to solve using JMP, and it presents an opportunity to learn a little about column formulas at the same time. Read on to learn more.
This post shows how the Definitive Screening Design can be used to assess and improve analytic methods.
A compelling component of presenting research is graphs of data collected and the story those visualizations tell. The Graphs for the Experimenter add-in helps JMP users in the life sciences create visualizations in Graph Builder. The add-in offers templates for commonly used analyses and gives researchers a start with using graphs to explore data and share discoveries. Watch the video below to ...
Specifying constraints in a DOE can seem daunting, but it can be much easier than you imagine if you use some of the other tools in JMP to do the heavy lifting.
在智慧製造與精益轉型的浪潮下,產品與系統的「可靠度」早已不再是傳統的品質管控指標,而是影響客戶滿意度、品牌信任與運營效率的核心競爭力。從消費電子、汽車零部件,到工業設備與半導體產品,可靠度分析正快速成為工程團隊不可或缺的關鍵能力。 可靠度是指產品在特定時間和使用條件下無故障運行的能力。從資料分析的角度出發,我們通常會通過「壽命分佈模型」來描述產品的失效時間分佈,其中最常見的是 Weibull分佈,它可以精準描繪不同時間點的失效率與風險函數。
在半導體產業的工作生態中,常常需要對面對的不良狀況找出問題來源,迅速地導入改善對策,而其中最為困難的階段是如何快速地從動輒上百上千的參數中,尋找出最相關的影響因子。以往,可能只能依靠工程師的過往經驗,慢慢的對懷疑的參數試錯找出關鍵因子,這樣的方式不僅耗時曠日,也可能忽略其中重要的指標。如何快速找到製程可以優化的方向,絕對是每一個工程團隊所面臨的一大挑戰。
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We are thrilled to invite you to take part in the pilot of the JMP Wish List Prioritization Survey, set to launch on July 3! Your feedback is invaluable as it will play a pivotal role in shaping the future of JMP by highlighting the ideas that hold the most significance to you.
Survey overview
Within this survey, you will be provided with 100 "coins" to allocate to your preferred ideas. You have...
Learn about how JMP users from notable organizations explore data and overcome obstacles. See and read presentations from over 55 JMP Discovery Summits.
Data integrity is essential for accurate predictive modeling, regulatory compliance, and business efficiency. I spoke with Chandramouli Ramnarayanan, Global Technical Enablement Engineer at JMP, about the biggest data challenges companies face and the best strategies for improving data quality. From statistical monitoring to design of experiments (DOE) and anomaly detection, Chandra shares expert ...
Is it possible to optimize a plasma-enhanced chemical vapor deposition (PECVD) with just 25 test wafers? Absolutely! In semiconductor manufacturing, constraints such as a 25-wafer run on a tool are common, but they don’t have to limit success. Leveraging process data to inform experiment design is a winning strategy for getting effective results with limited resources.
Procter & Gamble veteran Cy Wegman on the importance of a data-driven culture, key leadership attributes, and more.
對食品研發來說,每一次實驗都可能浪費原料與時間。透過有系統的實驗設計與數據分析,這家公司做到了「用最少的試驗,得到最多的資訊」。
手機螢幕的耐用性對消費者和製造商至關重要。本研究透過跌落測試與統計分析,評估兩種鋁矽酸鹽玻璃螢幕的耐久性,探討是否達到97%成功率標準,並比較其性能差異。
Esta presentación introduce las nuevas funcionalidades de JMP 18 en español, incluso: Detección de picosConectores de datos configurablesMejoras la importación de datos en servidores PIPreajustes de plataformaMejoras en le perfilador de predicción, incluso visualizar los intervalos de predicción, las interacciones superpuestas, y la habilidad de ver las observaciones individuales.Mejoras en la i...
The jackknife technique is very simple, yet very powerful, relying on calculations using the “leave one out” technique.Figure 3: Simple plot of X1 vs X2, including best-fit line (from ordinary least squares)