JMP

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)

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 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 cause analysis during problem occurrences 【Overview】 1) Taking Quality Management to the Next Step - Utilizing JMP Beyond Control Charts Focusing on quality management tasks, 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/2026/12-09

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

Aren't you just using the data obtained from experiments and prototypes to create figures for your reports? In this seminar, we will confirm the features and basic operations of JMP's Graph Builder, and using data typically obtained in research, development, and design departments, we will create commonly used graphs such as mean values with error bars, box plots, and scatter plots with regression lines. Additionally, we will demonstrate an approach that leads to new discoveries by switching conditions, which is difficult to achieve with spreadsheets like Microsoft Excel. Target Audience: - Engineers who regularly handle experimental or prototype data - Those currently creating graphs in Excel and feeling challenged by the effort required for conditional comparisons and plotting Main Content: - Features and basic operations of Graph Builder - How to create graphs commonly used in research, development, and design departments - Utilizing functions that promote new discoveries, which are difficult with spreadsheets - Customizing graphs and producing high-quality outputs Details & Registration: https://www.jmp.com/ja/events/live-webinars/non-series/2026/10-29-graph-builder