Statistical Quality Control (SPC) using Minitab
Course Overview
| ID | 22030014 |
| Duration | 2.0 days |
| Methods | Lecture with examples and exercises. |
| Prerequisites | General knowledge of math |
| Target group | Engineers, Quality Assurance |
| Vorgängerkurs | 2203001 |
Overview
This training provides a comprehensive treatment of the major aspects of using statistical methodology for quality control and improvement. Both traditional and modern methods are presented, including state-of-the-art techniques for statistical process monitoring and control and statistically designed experiments for process characterization and optimization. The training focuses on DMAIC (define, measure, analyze, improve, and control--the problem-solving strategy of six sigma).
Dates
Zurzeit stehen keine offenen Termine zur Verfügung. Nutzen Sie alternativ die Inhouse‑Option.
Learn with customized examples and content—precisely tailored to your requirements.
Your benefits at a glance
- Flexible preferred date
- Customized content
- Intensive exchange
- High practical relevance
Description
Learn how to apply statistical process control (SPC) methods with Minitab. Use the various control charts for attribute data, variables, or time-weighted data, as well as graphical process control techniques. Conduct process capability analyses and measurement system analyses with Minitab.
Services
- Lunch / catering
- Help with hotel / travel
- Comelio certificate
- Flexible: free cancellation up to one day before
Comelio Media
Still looking for additional reading? Discover suitable specialist books in our catalog.
Content
Modern Quality Management And Improvement
The Meaning of Quality and Quality Improvement - Statistical Methods for Quality Control and Improvement - Management Aspects of Quality Improvement - The DMAIC Problem Solving Process
Data Summary and Presentation
Describing Variation: The Stem-and-Leaf Plot, The Histogram, Numerical Summary of Data, The Box Plot, Probability Distributions - Important Discrete Distributions - Important Continuous Distributions - Probability Plots
Statistical Inference In Quality Control and Improvement
Statistics and Sampling Distributions - Point Estimation of Process Parameters - Statistical Inference for a Single Sample - Statistical Inference for Two Samples - The Analysis of Variance (ANOVA)
Variables Control Charts
Control Charts for –x and R: Statistical Basis of the Charts, Development and Use of –x and R Charts, Charts Based on Standard Values, Interpretation of –x and R Charts, The Operating-Characteristic Function, The Average Run Length for the –x Chart - Control Charts for –x and s: Construction and Operation of –x and s Charts, The –x and s Control Charts with Variable Sample Size, The s² Control Chart - The Shewhart Control Chart for Individual Measurements
Attribute Control Charts
The Control Chart for Fraction Nonconforming: Development and Operation of the Control Chart, Variable Sample Size, Applications in Transactional and Service Businesses, The Operating-Characteristic Function and Average Run Length Calculations - Control Charts for Nonconformities (Defects): Procedures with Constant Sample Size, Procedures with Variable Sample Size, Demerit Systems, The Operating-Characteristic Function, Dealing with Low Defect Levels - Choice Between Attributes and Variables Control Charts
Determining Process And Measurement Systems Capability
Process Capability Analysis Using a Histogram or a Probability Plot - Process Capability Ratios - Process Capability Analysis Using a Control Chart - Process Capability Analysis with Attribute Data - Gauge and Measurement System Capability Studies
Designed Experiments In Process and Product Improvement
Factorial Experiments: Statistical Analysis, Residual Analysis - The 2k Factorial Design: The 2² Design, The 2k Design for 3 and more Factors, Blocking and Confounding in the 2k Design - Fractional Replication of the 2k Design - Fractional Replication of the 2k: The One-Half Fraction of the 2k Design, The 2k–p Fractional Factorial Design
Sampling Procedures
The Acceptance-Sampling Problem - Single-Sampling Plans for Attributes - Double, Multiple, and Sequential Sampling - Acceptance Sampling by Variables - Chain Sampling - Continuous Sampling
Instructor
Our statistics trainer for DOE (Design of Experiments) and SPC (Statistical Process Control) and data analysis with Minitab Marco Skulschus studied economics in Wuppertal and Paris and has been working for more than 10 years as a lecturer, author of specialist books on databases and data analysis, and as a consultant for statistical analysis with Minitab.
Publications
- Grundlagen empirische Sozialforschung (Comelio Medien )
978-3-939701-23-1 - System und Systematik von Fragebögen (Comelio Medien )
978-3-939701-26-2 - Oracle SQL (Comelio Medien )
978-3-939701-41-5 - MS SQL Server - T-SQL - Abfragen und Analysen (Comelio Medien )
978-3-939701-69-9