Utilization of Experimental Design with JMP, a Statistical Analysis Software for the Chemical Industry
Let's efficiently discover hidden optimal conditions, experimental conditions, and formulation conditions within a limited number of experiments!
In the chemical industry’s research and development, there are complex challenges where many factors, such as the optimization of formulation ratios and the examination of process conditions, affect properties. Additionally, due to constraints on raw material costs and evaluation labor, there is a demand to efficiently gain insights with a limited number of experiments. In this seminar, we will introduce practical applications of Design of Experiments (DOE) using JMP. In the first half, we will explain how to create and optimize experimental designs considering formulation factors and constraints. In the second half, we will present Deterministic Screening Designs (DSD) that can efficiently identify important factors with fewer experiments. 14:00 - 14:45 Practical Application of Experimental Design in the Chemical Industry - Experimental Design Considering Constraints and Formulations 14:45 - 15:30 Connecting Screening and Optimization - Practical Use of Deterministic Screening Designs
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basic information
【Date and Time】September 30, 2026, 14:00~15:30 【System Requirements】 This seminar is an online seminar using Zoom. To view the seminar, the following environment is required: - A PC connected to the internet - Speakers (earphones) ▼Details & Registration https://info.jmp.com/register?formId=d79d4aa3-0ca5-4858-80f4-fdc32193a6b9&campaignId=701WP00001PHptfYAD
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Free (Pre-registration is required from the page below)
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Applications/Examples of results
"Democratization of Data" and Sharing the "Wisdom" of Manufacturing Across the Company - TOTO's New Exploration of "Good Products and Uniformity" [Challenge] The manufacturing of sanitary ceramics using natural raw materials involves approximately 13% shrinkage during the drying and firing processes. As products become larger and more complex, the challenge is how to maintain "uniform" high quality and how to convert the "tacit knowledge" of skilled artisans into "explicit knowledge" to pass on to the next generation. For TOTO Ltd., which has a history of over 100 years, this was a crucial issue at the core of its manufacturing. [Solution] Exploratory data analysis using JMP was introduced for the manufacturing data from the advanced Shiga factory. By deepening the high yield achieved through the introduction of the first barcode system in the sanitary ceramics factory, the "good product conditions" were quantified using visual verification with graph builders, as well as partition and cluster analysis, leading to improvements in direct yield and overall yield. Additionally, JMP was adopted for the foundational education of the "in-house study abroad program" over two years, aiming to enhance company-wide data science skills. [Results] Please check the following page for more information! https://www.jmp.com/ja/customer-stories/toto
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Company information
The JMP story goes back to 1989 when John Sall decided to combine statistical analysis capabilities with graphical visualizations to animate and visualize data. For more than 35 years now, John Sall has led JMP R&D, making each version of JMP more visual, more interactive, and more practical to help users understand their data. What started as a passion project has grown by leaps and bounds. It’s now a family of statistical software products designed with scientists and engineers in mind and used worldwide in nearly every industry.
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