Utilization of Experimental Design with JMP, a Statistical Analysis Software for the Chemical Industry

Analyze visually and interactively.

JMP, developed by SAS, has been used as a tool for statistical discovery by scientists, engineers, and people in various industries and government sectors engaged in data exploration. JMP is a desktop software that combines dynamic data visualization with powerful statistical capabilities, processing data in-memory. With interactive and visual JMP, it is possible to gain insights that cannot be obtained from mere tables of numbers or static graphs. In JMP, graphs, statistics, and data are all linked. This allows for deeper exploration of thoughts and leads to groundbreaking discoveries. JMP enables users to perform analyses in succession while staying in the flow of analysis. You can explore while maintaining the flow of the analysis, and there is no need to re-execute commands when new questions arise. Using JMP significantly improves the efficiency of data analysis, making it easy to handle everyday tasks and complex statistical problems, while also effectively communicating the results of the analysis.

• Construction and process management software
• Scientific Calculation and Simulation Software
• Big Data

For researchers and technology developers in the manufacturing industry! Start with no-code experimental design (DOE).

This is an introductory seminar to learn the basic operations of JMP's "Design of Experiments (DOE)." Anyone can participate, regardless of industry, job type, or experience with design of experiments. You will be able to experience the basic operations and functions of design of experiments while actually operating JMP on your own device, following the instructor's explanations and the provided text (PDF version). [Content] The seminar will focus on explaining the procedures for creating experimental designs, entering experimental data, fitting models, and visualizing results (such as contour plots and response surfaces) using JMP. JMP's "Custom Design" is a flexible experimental design creation feature that supports screening experiments and optimization experiments. It allows for the combination of various types of factors, such as continuous factors, categorical factors, and mixture factors, and can also create experimental designs with constraints on factors. In this seminar, we will introduce these features and how to utilize them while actually creating experimental designs using "Custom Design." If you do not have JMP, you can participate using a 30-day free trial version. Trial: https://www.jmp.com/ja/download-jmp-free-trial

• Other Software

Nitto Kohki will exhibit at "BATTERY JAPAN - Secondary Battery Exhibition," which will be held at Makuhari Messe Hall 7 from September 9 (Wednesday) to September 11 (Friday), 2026. [Booth Number: E22-6] ■ Introduction of Exhibited Products At this exhibition, we will showcase rapid fluid connectors that can quickly connect and disconnect piping for various fluids such as air, water, oil, and chemical solutions. Highlighted products include the "Zero Spill Coupler," which significantly reduces liquid dripping during disconnection and contributes to improving the working environment, as well as the new "Large Diameter Zero Spill Coupler." Additionally, we will present the "High Coupler" series, which features over 100 types categorized by body material and mounting size.

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In the chemical industry, research and development face complex challenges where many factors, such as the optimization of formulation ratios and the examination of process conditions, influence 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. This seminar 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 introduce 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 ▼Details & Registration https://info.jmp.com/register?formId=d79d4aa3-0ca5-4858-80f4-fdc32193a6b9&campaignId=701WP00001PHptfYAD

In recent years, innovative technologies such as generative AI like ChatGPT, Gemini, and Claude have become more accessible, leading to a transformation in users' "norms." This seminar will explain how those involved in planning and improving websites and apps can grasp these changes in "norms" and the perspectives and efforts necessary to enhance user experience. ■ Recommended for: - Those responsible for service conception and planning for corporate websites and apps. * Please refrain from applying if you are from a competing company or an individual. ■ Agenda: 1. Changes in "norms" in the AI era 2. The future of UX design 3. Q&A * The content of the above agenda may change without notice. Thank you for your understanding.

The quality demands surrounding the manufacturing industry are increasing year by year, and the quality assurance and quality control departments are required to make swift and reliable judgments more than ever before. On the other hand, many companies face challenges such as: - Past cases and procedures being scattered, making it difficult to quickly access necessary knowledge - The perspectives and grounds for judgment relying on the experience of the person in charge - Inquiries being concentrated on experienced personnel - Investigating similar cases from scratch each time - Results and reasons for judgments not being utilized for future improvements In this seminar, we will introduce the "Quality Knowledge Utilization AI" service, which leverages accumulated quality knowledge within the organization, such as quality regulations, procedures, past defect cases, audit records, and reports, to enhance on-site decision-making and establish a continuous system for quality improvement. This is not just a simple document search; AI will present decision-making materials and verification perspectives in line with quality business processes such as abnormal response, recurrence prevention, design quality enhancement, and audit response, supporting everything from reporting to sharing and improvement. This content is recommended for those considering the elimination of dependency in quality operations, standardization of quality judgments, and advancement of knowledge utilization.