Level: Intermediate
JMP is probably the software with the most powerful capabilities and systematic applications among reliability data analysis software. In this report, we will systematically introduce univariate distribution, bivariate relationship, prediction, modeling, and life data analysis methods within the allowable time using the JMP reliability/survival analysis platform. In particular, we will introduce reliability activities and data analysis processes through hypothetical examples that do not jump from the real examples, such as the regeneration theorem and methods used in reliability testing.
Hirono Motohisa
Joined Ricoh Co., Ltd. in 1984. Since then, he has been involved in the company's quality management and reliability management, as well as raising awareness and promoting statistics. He served as head of the QM Promotion Office in the Quality Headquarters and director of the SF Business Center before assuming his current position. He was a lecturer at the Faculty of Engineering at Tokyo University of Science (1997-1998) and a part-time lecturer at the Faculty of Policy Management at Keio University (2000-2004). His main areas of expertise are statistical quality control and reliability engineering. His main publications include "Graphical Modeling in Practice," "How to Utilize Multivariate Data with JMP," "23 Lectures on Statistical Calculation Methods with Anscombe-style Numerical Examples," "Multivariate Analysis for Engineers Using JMP," and "Eye-Opening Multivariate Analysis."
Koichi Endo
Joined Toshiba Corporation in 1987. After working on product and process development for power ICs (power supply ICs, 500V driver ICs for motors, etc.), he is currently engaged in failure analysis technology development. He holds a PhD in Information Science from Osaka University.
*No handouts will be provided.
