Los participantes en el curso comprenderán los conceptos fundamentales del Diseño de Experimentos y entenderán como planearlos y aplicarlos correctamente en situaciones específicas dentro de sus empresas, con un enfoque en la mejora continua procesos y la solución de Problemas.
Duración: (18 horas)
Introduction to Minitab
Decrease the time required for statistical analysis by quickly learning to navigate Minitab’s user-friendly and customizable environment. Learn how to import/export data and output between Minitab and various software and database systems. Enhance your ability to create, manipulate, and restructure data. Develop sound statistical approaches to data analysis by learning how to create and interpret a wide variety of graphs and numerical measures useful for quality improvement initiatives. This course focuses on the utilization of these tools as they pertain to applications commonly found in manufacturing, engineering, and business processes.
Topics covered include: Charts, Histograms, Boxplots, Dotplots, Scatterplots, Tables, Measures of Location and Variation, ODBC
Measurement System Analysis, including Hypothesis Testing, Bias, Linearity, & Stability, Variable GR&R, Attribute GR&R.
Introduction to DOE
This course teaches the concepts and terminology used in the field of experimental design and then covers the planning and execution of multi-factor experiments. The planning step enables students to make decisions regarding objectives, responses, factors and the plan to be used in the experiment. Sesion
DOE Factorial Designs
Learn to generate a variety of full and fractional factorial designs using Minitab’s intuitive DOE interface. Real-world applications demonstrate how the concepts of randomization, replication, and blocking form the basis for sound experimentation practices. Develop the skills necessary to correctly analyze resulting data to effectively and efficiently reach experimental objectives. Use Minitab’s customizable and powerful graphical displays to interpret and communicate experimental results to improve products and processes, find critical factors that impact important response variables, reduce process variation, and expedite research and development projects.
Tools and topics Covered Include: Design of Factorial Experiments; Normal Effects Plot and Pareto of Effects;Main Effect, Interaction, and Cube Plots; Center Points; Overlaid Contour Plots; Multiple Response Optimization
