Patrick Giuliano, Senior Analytical Technical Support Engineer, JMP
Charles Chen, Principal Continuous Improvement Expert, Morrill Learning Center
A leading semiconductor manufacturer has developed a novel multidisciplinary program for applied engineering statistics (AES), by incorporating applied problem-solving (6S DMAIC), JMP statistical thinking (STIPS), and core JMP curriculum course content, sponsored by JMP Education. The program's key features culminate in the use of JMP 17 features in powerful, systematic, and practical analytical contexts. The 6S Black Belt curriculum has been seamlessy innovated, based on both AES and JMP curriculum content across DMAIC phases.
The first initiative involved transitioning from Minitab 19 to JMP 16, followed by mapping the JCSA, JGPH, JANR, JMSA, JSPC modules to the DMAIC framework. These JMP core courses help facilitate DMAIC Black Belt Project execution more effectively through AES thinking. Several JMP case studies are demonstrated, including item analysis (Attribute GRR), text mining/data mining hybrid correlation, model-driven multivariate SPC, and group orthogonal supersaturated design.
To train internal instructors to teach Black Belt JMP modules, several advanced JMP curricula (JMP 17) have been created. In addition to internal Black Belt certification, the JMP STIPS Certification Exam was offered, as was the JMP DOE Certification Exam. JMP STIPS courses were made available to any internal employee. The program innovates the traditional 8D project framework by adding JMP 17 tools to make 8D project root cause analysis more objective and data-driven to resolve complex system-level quality challenges . The 2023 March Madness Forum Events, sponsored by 64 presenters, have drawn full attention across the organization, recognize the success of the JMP-oriented AES program.
