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 factor 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 during problem occurrences, with demonstrations included. 【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 factor analysis when problems occur 【Overview】 1) Taking Quality Management to the Next Step - Utilizing JMP Beyond Control Charts Using quality management tasks as a subject, 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 Factor 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 examination of process conditions, affect properties. Additionally, due to constraints on raw material costs and evaluation labor, there is a need 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 a 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 keeping time and costs down. In this seminar, we will focus on the features of experimental design, specifically the sample size explorer and Bayesian optimization, and present examples of their application in the manufacturing industry in a demonstration format. [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 introduce analysis examples using JMP. Additionally, we will demonstrate how to simulate the relationship between the required data numbers for t-tests and statistical power using the sample size explorer. Second half: Utilizing JMP Pro Bayesian optimization - Application to simulation experimental data The Bayesian optimization platform is originally designed for experimental data that includes measurement errors; however, there is also a significant demand to apply it to simulation experimental data that does not include errors, such as CAE. In this seminar, we will introduce approaches for utilizing Bayesian optimization with simulation experimental data.

"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 data loading to processing, formatting, graph creation, and automation. 【Target Audience】 Anyone, regardless of industry, who regularly processes data or creates graphs using spreadsheet software Those who find it cumbersome to create reports or graphs on a monthly or weekly basis 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 to engage in data analysis and improvement activities. 【Presentation Overview】 1. "Unraveling the 'Personality' of Batteries!" Utilizing "Raw Data" for "Proactive Quality" Hasegawa Kaoru and Shimada Kohei from Energy With Co., Ltd. 2. Why Can't We Find the Root Cause of Defects? ~Data-Driven Improvement Practiced with JMP~ Tsuji Ikumi 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. - Anyone 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 text (PDF version) and the instructor's explanations. [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 accommodates 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 set on the 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