RUTF食品研發案例:使用混料設計實驗精準改善配方
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」。
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」。
Adoption of analytics across teams is key to organizational growth. Evaluating progress toward this objective is critical to organizational alignment and efficiency. The free Analytics Maturity Assessment (AMA) helps organizations evaluate their progress by identifying: Analytic successes.Training opportunities.Potential gains in efficiency.New ways to standardize and automate processes.Analytic g...
The JMP S3 Data Connector in the JMP® Marketplace uses JMP's powerful Python integration to provide seamless access to Amazon Web Services (AWS) S3. You can configure your AWS credentials within the data connector editor and quickly import files that are compatible with JMP and are hosted on Amazon S3 remote connections. This integration streamlines data retrieval processes, enhancing your workflo...
Using the scripting environment and a python package called SASPy, JMP 18 can interface with SAS instances, import data sets, export data sets, and run SAS code.
在化工或材料企業工作的你,如何有效提升新材料研發效率、降低實驗成本?透過QSAR方法,化工工程師可將多水準類別因子轉換為連續因子,並利用主成分分析減少變因數量,降低實驗次數與成本。結合JMP的Custom Design與PLS建模,可快速建立高效預測模型,優化材料選擇與製程設計。了解如何運用數據分析提升研發效率,探索更多實驗設計與建模技巧!
Descubre cómo JMP y JMP Live pueden transformar la gestión de datos en tu empresa mediante la automatización del SPC y las alertas automáticas en gráficos de control.
El constructor de flujo de trabajo de JMP permite grabar los pasos que se toman haciendo clic en la interfaz de JMP, para que el trabajo sea repetible, para que los pasos se puedan aplicar cuando hay datos nuevos, o el flujo de trabajo entero se puede compartir con otras personas.
JMP Clinical 18.1.2 (released on January. 21) and JMP Clinical 18.2 (which will be released in March) comes with several important features, including data quality reports, a configuration checking tool, autosaving and restoring the review builder templates.
本篇文章深入探討如何運用JMP工具進行FMEA(失效模式與影響分析),有效管理製造業品質問題。了解多重回應、儲存格著色及Dashboard等功能如何助力品質分析與改進,讓失效分析更高效、更直觀。
深入解構製造業品質控制的挑戰與解決方案:從資料分析到製程優化,揭示如何利用數據分析工具解決製造業常遇到的品質管理與品質改善問題,提升產品穩定性與競爭力。
The Torch Deep Learning add-in for JMP® Pro is a no-code interface to the PyTorch library for predictive modeling with deep neural networks. The add-in lets you train and deploy predictive models that use image, text, or tabular features as inputs to predict binary, continuous, or nominal targets. A helpful feature of the add-in is its storybook, which offers example starting points for finding...
Have you ever needed to import the data contained in an image of a graph into JMP? It turns out JMP can do this rather easily. Read on to find out how.
In previous blog posts, we talked about breaking down one aspect of the testing challenge, dealing with multiple inputs as a designed experiment where we can start by focusing on one input at a time. A later blog post revisited the fundamental principles of factorial effects in designed experiments. Now, we’ll combine these ideas and discuss what we might want in designing an experiment to be used...
对于研究人员来说,掌握更高效的数据分析方法、使用数据思维解决难题可以达到事半功倍的效果。JMP 学术团队一直在为此不懈努力。11月19日,JMP 应邀走进华东师范大学,携带丰富的行业应用案例,为华师大的师生们呈现了精彩的DOE案例分享。 JMP 数据分析顾问 Jacky Zhang 老师从理论出发,结合生动的行业应用案例,详细讲解了 DOE在多个领域的广泛应用。通过咖啡店经营管理、芯片制造行业产率分析、教育行业真实实验过程等多个实例,Jacky Zhang 老师从不同角度阐释了该技术在实际操作中的价值与应用。 部分学生表示,这些案例不仅通俗易懂,更让他们深刻认识到所学知识的重要性。 此次活动充分展示了如何将学术知识与实际应用紧密结合,帮助同学们了解日常所学知识如何推动实际业务发展。同时,也为同学们启发了就业方向与个人发展的潜力领域。
JMP is valued in the Six Sigma community because it integrates all the capabilities essential for data-driven decision making and process improvement. JMP integrates tools and interactive reports that support each phase of the Six Sigma's DMAIC (Define, Measure, Analyze, Improve, Control) process. The new, free JMP Modern Six Sigma Add-In, created by JMP SE Kim Hui Lim @lkimhui and Pin Hu @PIN, in...
Novas Funcionalidade no JMP 18 Nesta série de videos você desenvolverá as competencias necessárias para usar as novas funcionalidades do JMP 18. Criamos uma série de vídeos curtos para quem está utlizando a última versão do JMP e quer aprimorar as análises. Aprenda neste vídeo como usar o Python no JMP 18. Você vai aprender a: Como usar o Python no JMP 18Como instalar e desinstalar pacotesComo...
Novas Funcionalidade no JMP 18 Nesta série de videos você desenvolverá as competencias necessárias para usar as novas funcionalidades do JMP 18. Criamos uma série de vídeos curtos para quem está utlizando a última versão do JMP e quer aprimorar as análises. Presets Aprenda neste vídeo como usar as predefinições do JMP 18 de forma que você salve uma análise personalizada de muitas plataformas de...
Use this interactive applet to prove to yourself (and others) that DOE is better than One-Factor-At-a-Time (OFAT) Experimentation.
The Materials Informatics Toolkit is a powerful, user-friendly JMP add-in designed to provide an interface for using the RDKit package to calculate descriptors from Simplified Molecular Input Line Entry System (SMILES). I developed the add-in after numerous conversations with JMP users who were working with molecular structures and using Python for their analyses. They needed to be able to perform...