SAS Institute Japan List of News Articles

Although quality data and process data are accumulated, there are challenges such as "missing signs of abnormalities" and "being unable to identify the cause when problems occur." In the seminar, we will cover practical methods for quality management and cause analysis, introducing a data-driven approach to problem-solving. We will explain analytical approaches that can be utilized in manufacturing sites, from quality monitoring to cause exploration when problems arise, including demonstrations. 【Target Audience】 Quality management personnel in manufacturing Production technology and process improvement personnel Those who want to utilize process data and quality data Those who feel challenges in cause analysis when problems occur 【Overview】 1) Taking Quality Management to the Next Step - Utilizing JMP Beyond Control Charts Using quality management tasks as a theme, we will cover the flow from control charts and process capability analysis using JMP to cause exploration, as well as methods for sharing analysis results. 2) Data-Driven Cause Analysis and Quality Improvement An analytical approach to efficiently narrow down the causes of problems using process data and quality data. ▼ Details & Registration https://www.jmp.com/ja/events/seminars/discovery-seminar-series/2026/10-30

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

JMP is software that not only excels in statistical analysis and graph creation but also has robust features for experimental design. By utilizing experimental design, efficient data collection can be achieved while minimizing time and costs. In this seminar, we will focus on the features of experimental design, specifically the sample size explorer and Bayesian optimization, and demonstrate examples of their application in the manufacturing industry. 【Overview】 First half: Utilization of t-tests in the manufacturing industry and simulation of required data numbers We will explain the overview and examples of t-tests, which are used for various purposes in the manufacturing industry, and present analysis examples using JMP. Additionally, we will introduce a method to simulate the relationship between the required data numbers for t-tests and statistical power using the sample size explorer. Second half: How to utilize JMP Pro Bayesian optimization – Application to simulation experimental data The Bayesian optimization platform is originally designed for experimental data that includes measurement errors, but there is also a strong demand to apply it to simulation experimental data that does not contain errors, such as CAE. In this seminar, we will introduce approaches for utilizing Bayesian optimization with simulation experimental data.

To researchers and technology developers in the manufacturing industry, as well as manufacturing and quality managers. If you feel the limitations of Excel, start with this seminar. This is a free seminar on JMP aimed at manufacturing engineers who understand the need for data analysis but lack usable tools, or who want to utilize statistics but cannot write code. It will be conducted online in a format where you can operate JMP on your own while watching the instructor's demonstration, making it easy for first-time participants to join. ▼Details & Registration https://www.jmp.com/ja/events/live-webinars/hands-on-workshops/2026/07-29-getting-started Those who do not have JMP can participate using a 30-day free trial version. Trial: https://www.jmp.com/ja/download-jmp-free-trial Seminar Content - Data visualization - Exploring relationships between data - Comparing means, regression analysis - Data exploration using various graphs (Graph Builder, Bubble Plot) - Creating and comparing predictive models (Stepwise Regression, Decision Trees)

"Data processing takes time," "I keep repeating the same tasks," "Creating graphs is surprisingly difficult." Do you have such concerns? As the importance of data utilization increases, a lot of time is spent on tasks such as data processing and graph creation. Especially when working with spreadsheet software, mistakes due to repetitive manual tasks are often a challenge. JMP not only offers advanced statistical analysis but also has a wealth of features for data preprocessing and visualization. In this seminar, we will introduce methods to streamline data operations from loading and processing to graph creation and automation. 【Target Audience】 Anyone, regardless of industry, who regularly processes data or creates graphs using spreadsheet software. Those who feel burdened by the effort of creating monthly or weekly reports and graphs. Individuals who want to streamline data preparation tasks and spend more time on analysis and reporting. Those who want to learn how to utilize JMP not only for analysis but also for data preprocessing and visualization. ▼Details & Registration https://www.jmp.com/ja/events/live-webinars/non-series/2026/10-08-data-processing

In the manufacturing industry, while a lot of quality and process data has been accumulated, there are still many cases where its value is not fully utilized. In this seminar, two companies will introduce examples of using JMP for data analysis and improvement activities. 【Presentation Overview】 1. "Unraveling the 'Personality' of Batteries!" Utilizing "Raw Data" for "Proactive Quality" Kaoru Hasegawa and Kohei Shimada from Energy With Co., Ltd. 2. Why Can't We Find the Root Cause of Defects? ~Data-Driven Improvement Practiced with JMP~ Ikumi Tsuji from Atfields Technology Co., Ltd. 【Target Audience】 - Individuals involved in quality control, quality assurance, production technology, and manufacturing technology in the manufacturing industry. - Those who want to utilize quality data and process data to work on quality and process improvements. - Individuals interested in data analysis and quality/process improvement using JMP (both JMP users and non-users are welcome). ▼Details & Registration https://www.jmp.com/ja/events/seminars/non-series/2026/09-18-manufacturing

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 you can also create experimental designs with constraints on factors. In this seminar, you will create experimental designs using "Custom Design" while learning about these features and how to utilize them. 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

Starting from November 2025, "JMP 19" has become available. Those who hold a license can upgrade to the latest version. For information on new features, please visit the following site: https://www.jmp.com/ja/software/new-release/new-in-jmp