Discovery Summit

Innovative Thermal Transport Modeling of Fusion Plasma Using JMP^®

Masayuki Yokoyama, Professor, National Institute for Fusion Science

• Industry/Topic: Education/Data Exploration/JSL Application Development
• Level: 2

I have attempted modeling of thermal transport properties in fusion plasmas using a "big data" approach based on the results of several experiments and relevant analyses. This research, which strives to use JMP to view the tens of thousands of plasma experiments that have been conducted as a source of big data, differs in its fundamental idea from conventional modeling of the thermal transport properties based on physics mechanisms. If this research is successful, we will be able to present an effective means of modeling of thermal transport properties across a broad range of plasma parameters without any awareness of types of fluctuations that cause turbulent transport and collisional thermal transport, etc. Moreover, we will be able to predict parameters such as temperatures in fusion reactors rather easily and in a short period of time for the effective reactor operation and control.

Separation Prediction Based on Statistical Retention Modeling
for Simultaneous Optimization of Aqueous Phase pH and Organic Phase Composition

Tsukasa Sasaki, Researcher, Analytical & Quality Evaluation Research Laboratories, Pharmaceutical Technology Division, Daiichi Sankyo

• Industry/Topic: Education/Data Exploration/JSL Application Development
• Level: 2

Reversed-phase liquid chromatography (Rp-HPLC) has been recognized as an extremely important analytical methodology in recent years in the field of quality assessment of low-molecular drugs, since it can be used to isolate components from complicated mixture and quantitate them with favorable reproducibility. Generally, optimization and refinement of analytical condition in Rp-HPLC is performed stepwisely according to the physicochemical properties of the targeted compounds. However, since the final separation condition is decided based on the effects of several factors relate to the mobile phase’s properties, a trial-and-error approach is not practical for searching out the optimal setpoint. In this presentation, we’ll report research about a simultaneous optimization approach by using multiple linear regression analysis and artificial neural network analysis on the composition of the organic portion and the pH value of the aqueous portion of mobile phase.

JMP^® Applications for Utilizing Big Data on Manufacturing

Nobuo Hara, Staff Engineer, Panasonic Corporation

• Industry/Topic: Education/Data Exploration/JSL Application Development
• Level: 2

At Panasonic, we have utilized many resources to make use of data in the semiconductor field for many years, and have been successful at making use of big data in manufacturing. However, manufacturing equipment and product unit values are not nearly as expensive in many other business divisions as they are in the semiconductor field, so the resources that can make use of data have been limited from a cost-effectiveness perspective. In recent years, however, examples of the successful use of big data centered on IT have become widely known, and the utilization of big data in general manufacturing has become desirable. Under such circumstances, my department, which is the companywide production technology support unit, has established three issues for the utilization of big data in manufacturing with limited resources: data acquisition, data extraction, and data analysis. Data analysis involves the development and demonstration of systems that use JSL and OLE in JMP, and this is currently underway. In this presentation, I will explain the issues involved in the use of big data in manufacturing and their resolution, based on the system we have developed.

An Encouragement of Robust Parameter Design (From KKD to Science)

Tadashi Mitsui, Chief Specialist, Storage & Electronic Device Solutions Company Center for Semiconductor Research & Development, Semiconductor Research Planning & Coordination Department, Toshiba Corporation

• Industry/Topic: Education/Data Exploration/JSL Application Development
• Level: 2

In a mass production manufacturing process, robust design is regarded as important, especially for process parameter variation. Nevertheless, it is rarely carried out because of requirements for large experimental resources. Conventional methods allow the use of a noise matrix as an outer array, along with orthogonal arrays. The total number of experiments increases by a lot, except in the case of uniformity optimization where noise factor is a measurement sampling position. In this study, we propose a cost-effective method for robust design with the use of custom design.

A Consideration of Differences in Average Public and Private Saving Rates by Generation and Current Income

Kenichiro Tanaka, Doctoral Student, Graduate School of Applied Informatics, University of Hyogo

• Industry/Topic: General/Data Exploration/Data Visualization
• Level: 1

In order to consider what sorts of differences might occur in the saving rates of individuals working in the public sector (public) and individuals working in the private sector (private), we used pseudo-microdata for educational purposes provided by the National Statistics Center and analyzed it with the JMP statistical analysis software. Although it was clear that the average public saving rate was higher than the private, an assay of differences in saving rates by five-year classes and five classes of current income revealed that neither was necessarily higher. Further, a common point between public and private was that the peak average saving rates of both were in the 35-39 range, began to decline after age 40, then generally recovered before the official retirement age, in the 55-59 bracket. We learned that, in households of two or more individuals believed to be married, it is essential to save for retirement during the periods in which that is possible, regardless of children’s educational expenses.

The Actual State of Family Budgets in Single-Mother Households: A Comparison of Single-Income and Double-Income Households

Keirei Ka, Ji-in Toh and Keijo Lee, Doctoral Student, Graduate School of Applied Informatics, University of Hyogo

• Industry/Topic: General/Data Exploration/Data Visualization
• Level: 1

According to the 2011 Nationwide Survey on Fatherless Families, there are an estimated 1,238,000 single-mother households across Japan. We used pseudo-microdata for educational purposes provided by the National Statistics Center to analyze the economic conditions and lives of these households, with a particular focus on Engel’s coefficient and the ratio of spending on home-cooked meals, home-meal replacements, and eating out. The aim was to analyze the data with a focus on differences in the lives of single-mother households and general population married-couple households (both single-income and double-income households).