Abstract: To be more competitive in today’s job market, Problem Solving and Decision Analytics are some of the powerful career skills that are competitive across many industries. Within STEM education, the Scientific Method and single variable data analysis are not be commensurate with today’s complex problems. Not all problem-solving methods are created equal and may not be designed to counteract cognitive bias decision making.
Engineers like to think they are logical and immune to cognitive bias. Unfortunately, everyone is susceptible, which results in flawed decision making. A subset of Industrial Problem Solving, such as Structured Problem Solving (DMAIC, 8D) and Multiple Hypothesis intrinsically resist bias while minimizing poor decisions.
In this seminar, I will review Industrial Problem-Solving methodologies that embrace both Structured Scientific Problem-Solving method as well as Empirical problem-solving tools such as Design of Experiments, & Statistical multi-variable data analysis. These faster problem-solving techniques are typically 200% to 400% faster than single hypothesis and have been vetted with my R&D product team at Applied Materials and are career enhancer whether you headed to Academia or to industry in the future.
Bio: Dr. Chris Olsen is the Sr. Director of Oxidation Products in the Front End Products (FEP) Group of Applied Materials and had been with the company for 23 years of his 25 years in the Semiconductor industry. Dr. Olsen researches process chemistry, surface science driven kinetics & hardware development in ultra-conformal radical oxidation of SiO2 in high aspect ratio (HAR) 3DNAND Flash memory. Chris holds a Ph.D. in Materials Science & Engineering from UC Berkeley and BS in Materials Engineering from UCLA. Chris holds over 75 U.S. patents and is an author on over 50 publications.