Tabtrainer Minitab: Process Capability Analysis-Continuous

Achieve top-level expertise in Minitab with Prof. Dr. Murat Mola, recognized as Germany's Professor of the Year 2023.

What you'll learn
- Explain the concept of process capability and distinguish between overall and potential capability.
- Perform a complete process capability analysis for continuous, normally distributed data using Minitab®.
- Verify normality assumptions using the Anderson-Darling test and interpret p-values correctly.
- Construct and interpret X-bar and R control charts to assess process stability.
- Differentiate between standard deviation within and standard deviation overall, and understand their implications for capability.
- Calculate and interpret key capability indices including Cp, Cpk, Pp, Ppk, and Cpm.
- Assess the centering and variation of a process using visual tools such as histograms, probability plots, and dot plots.
- Identify and analyze causes of process shift and variation using practical tools like root cause analysis and supplier-based grouping.
- Apply improvement measures and validate their effectiveness through comparative capability analysis.
- Communicate capability results effectively to stakeholders and support continuous quality improvement initiatives.

Requirements
- Software Minitab
- No Specific Prior Knowledge Needed: all topics are explained in a practical step-by-step manner.

Description
1.Data Preparation & Exploratory Analysis

How to import and clean quality data

Use of descriptive statistics to assess central tendency and dispersion

Identifying outliers and initial trends

Performing theAnderson-Darling testto verify normal distribution assumptions

2.Process Stability Analysis

Construction and interpretation ofX-bar and R control charts

Application of all 8 AIAG control tests to identify process instabilities

Understanding subgroup structures and the difference between within-group and between-group variation

Verifying whether the process is stable enough to begin capability analysis

3.Capability Metrics and Their Interpretation

Introduction to key process capability indicators:Cp, Cpk, Pp, Ppk, and theCpm (Taguchi Index)

Understanding the difference betweenoverallandpotential capability

Explanation ofprocess centeringandprocess shift (Katayori)

Visual interpretation throughhistograms,density functions, andz-benchmarks (Sigma Level)

Assessing scrap rates usingPPM values(Parts Per Million)

4.Root Cause Analysis and Optimization

Root cause investigation using supplier-coded ID data

Creation ofdot plotsto compare raw material quality across suppliers

Implementing technical and supplier-related improvement actions

Evaluating before-and-after scenarios using theCapability Sixpack tool

5.Final Evaluation and Best Practices

Comparing pre- and post-optimization results based on capability indices and control charts

Interpretation of visual and statistical outputs to determine long-term capability

Guidance for saving, documenting, and communicating capability projects

Understanding when a process can be consideredstatistically capable, and how to sustain performance

Learning Outcome:

By the end of this course section, participants will be able to:

Apply the complete capability analysis cycle from start to finish

Use key performance indicators to assess and compare process capability

Identify causes of process instability and high variation

Implement targeted improvements to meet customer requirements

Use Minitab® tools efficiently, including control charts, capability plots, and the Capability Sixpack

This training empowers learners to makedata-driven decisions, communicate process capability clearly, and supportsustainable quality improvementsin real industrial settings.

Who this course is for:
- Data Analysts, Six Sigma Belts, Minitab Process Optimizers, Minitab Users
- Quality Assurance Professionals: Those responsible for monitoring production processes and ensuring product quality will gain practical tools for defect analysis.
- Production Managers: Managers overseeing manufacturing operations will benefit from learning how to identify and address quality issues effectively.
- Six Sigma Practitioners: Professionals looking to enhance their expertise in statistical tools for process optimization and decision-making.
- Engineers and Analysts: Individuals in manufacturing or technical roles seeking to apply statistical methods to real-world challenges in production.
- Business Decision-Makers: Executives and leaders aiming to balance quality, cost, and efficiency in production through data-driven insights and strategies.
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