Quality Data Analysis

Dear reader,

In your next lecture you will find some basic information about the quantitative tools and methods for managing, modeling and monitoring data in industrial and business scenarios.

Topics:

1. Quality engineering & Industry 4.0
2. Quality data modeling:
   1. Standard assumptions & related tests
   2. Modelling patterns via linear models
   3. Modeling autocorrelated data via time series analysis
   4. Modeling survey data (categorical & ordinal)
3. Quality monitoring of continuous variables:
   1. Traditional statistical process control (SPC) for the mean and the variance
   2. SPC for autocorrelated data
   3. Model based and model-free approaches for quality control of autocorrelated data
4. Quality modelling and monitoring for “big” data streams:
   1. Modeling multivariate data
   2. Dimensional reduction via Principal Component Analysis
   3. Control chart for multivariate data
5. Toward zero-defect manufacturing: process quality and product specifications. Capability analysis. Univariate
   and multivariate control charts for small shifts (EWMA, CUSUM)
6. Modelling and monitoring attribute and qualitative data: control chart for defective rates and survey data
7. Quality Improvement – The role of improvement in the six-sigma roadmap. Quality improvement via empirical
   model building (for management engineering only- hints).