The course of study for elementary school and junior high school was made public in March 2017, and the course of study for high school in March 2018.It is important to realize the purpose of this course of study.In education of mathematics, it is expected to tackle positively not only the problems of “the world of arithmetic/mathematics”, but also the problems of “the real world”.When considering the above, essential consideration based on the connection with other subjects’ contents is necessary in addition to the utilization of information appliances. Furthermore, from the viewpoint of lifetime study, learning mathematics with a Mathematical viewpoint and ways of thinking through mathematical activities as well as developing power to work on a problem tenaciously should be strengthened.

View full abstract

　The purpose of education is essentially to make it possible for people to live freely. If society changes, its purpose will have to change according to it. The OECD is developing the Education 2030 project to examine the competency required in the near future of 2030 and consider the curriculum, teaching and learning, assessment and evaluation, and others that will lead to the development of such competencies. In this paper, I discussed the need to multilayering mathematics education to foster such competencies, including data science. Also I introduced the case “Let’s save more lives with AEDs” for fostering them at junior high school.

View full abstract

　We have two subjects in Information. One is “Information Study for Participating Community”, other is “Information Study by Scientific Approach”. Student can choose either one. In the new national guideline, everyone have to choose “Information StudyⅠ”. That include programming and that is considering to enter a college entrance examination. And we make “Information StudyⅡ” to learn after “Information StudyⅠ”. “Information StudyⅡ” include data science. We prepare to teach “Information StudyⅠ” and “Information StudyⅡ”.

View full abstract

　This article is the third report of 3 separate reports on the study group on big data analysis in the quality control field. This article addresses the machine learning to apply to statistical quality control. Especially, the problems for applying machine learning to statistical quality control are pointed out.

View full abstract

　Many machine learning applications are expected to help manufacturing quality improvement. This article indicates several effective applications and potential for visual inspection, interpretability, anomaly detection and quality control.

View full abstract

　We often hear the word “Big data” and “AI technology” nowadays.
　There’re a lot of reports on automated system such as self-driving cars, automatic transportation and automatic sorting in the industryworld.
　We’re also emphasizing our research on the utilization of the big data and AI technology.
　I described the utilization of the big data and AI technology that we’re researching at our company in this report.
　Furthermore, I described the needs to introduce them in the future employee training program.

View full abstract

　On July 11, 2018, the special talk on “Big Data, Machine Learning, and Data Science” was given by Prof. Vijay Nair at Sekisui Chemical Co., LTD. Kyoto Research Auditorium. Primary organizer is JSQC. Prof.Nair was a professor at Michigan University and also served as the president of ISI （International Statistical Institute）. Now he works at Wells Fargo Bank as the head of Statistical Learning and Advanced Computing Department. He gave the speech about for two hours from the both sides of theory and practice. It covers the following topics：What is Big Data?, What is New with Big Data?, Primary Data vs. Secondary Data, Myths about Big Data, Machine Learning and AI, ML vs. Statistics, Data Science and Big Data. After the talk, questions and answers were actively conducted.

View full abstract

　Hospitals must tackle medication incidents in order to provide high quality medical treatment. Though there are many types of contributing factors, it is effective to identify those which involve the work process and thereby create an opportunity for　improvement. Currently, analysis methods such as root-cause analysis（ RCA） and the process-oriented analysis method（ POAM） are utilized. These do not prescribe a procedure in detail for identifying process factors, and as a result, a majority of medical personnel cannot identify them easily or identify potential improvements in the working process.
　This paper takes POAM, which focuses on process factors, and identifies reasons for shortcomings in its application. It develops three analysis tools, designated：“medication process model,” “error mode list,” and “identifying factor tree.” It also proposes a method to systematically identify susceptible process factors in the working process. The method is applied to an actual medication incident and the medical staff involved, and improvement of the analysis results is demonstrated.
　This method enables medical personnel to identify factors in working processes leading to susceptibility to error, and to plan countermeasures. It can therefore reduce medication incidents.

View full abstract

　This paper describes a case study of the evaluation of the geometry of holes made by rotary ultrasonic machining using ellipsoidal characteristics. The characteristics under consideration are half of the average sum of the distances from the two foci of the ellipse（ half sum of the distance）, roughness of the hole inner surface, the difference between the maximum and minimum of the half sum of the distance, and oblateness. The machining factors are feed speed and rotation speed of the tool, ultrasonic vibration power, and coolant pressure.
　In order to clarify the hole making mechanism and develop statistical models of these characteristics incorporating these four machining factors, we first designed two levels of factorial experiment and executed sixteen experimental runs. Next, we analyzed the data by analysis of variance. Then we selected parameters and constructed the statistical models. Finally, we discuss the results and show this approach is better for the evaluation of the geometry of holes than the method based on circles.

View full abstract

　In 2016, the unlawful practice relating to automobile fuel efficiency levels by domestic manufacturers came to light；a major incident that led to the reorganization of the automobile industry. While such practices should not be ignored, I think that part of the problem is related to the ease with which the present fuel efficiency measurement system allows for fraudulent activities to occur. As a consumer it is a problem whether their vehicle runs or not, but this matter is diverging from that. It has been recognized for a long time that actual fuel efficiency levels are lower than figures stated in print. Therefore, even if the fuel efficiency standards undergo a change, the problem cannot be expected to be resolved sufficiently. There is great meaning in conducting an experiment based on actual running conditions that takes into account relevant noise factors.
　Therefore, using past research on automobile fuel efficiency which utilizing quality engineering as a reference, I conducted a multiple-vehicle comparative experiment on fuel efficiency. In addition to simply comparing performance between models, I also evaluated the degree to which vehicle efficiency levels matched those values stated in print.

View full abstract