Minitab – Statistical Quality Analysis (Manufacturing)

Minitab Gage Run ChartThis hands-on workshop is normally taught in 1 day (or 1.5 days with additional or custom content). Prerequisite: Minitab Essentials and Introduction to Basic Statistics, or working knowledge of Minitab and basic statistical methods.

Develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems. Learn the basic fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control manufacturing processes. Develop the skills to know when and where to use the various types of control charts available in MINITAB for your own processes. Learn how to utilize important capability analysis tools, many enhanced in MINITAB Release 14, to evaluate your processes relative to internal and customer specifications. The course emphasis is placed on teaching quality tools as they relate to manufacturing processes.

Tools Covered Include: Gage R&R, Destructive Testing, Gage Linearity, Gage Stability, Attribute Agreement, Variables and Attribute Control Charts, Capability Analysis for Normal, Non-normal and Attribute data.

Optional topics are special additions to standard Minitab training workshops, and extend the course by about 1/2 day. All Minitab training workshops use the latest, current version of Minitab, and authorized Minitab training materials.

Measurement Systems Analysis (MSA)

  • Gage studies for continuous data: Gage R&R (Crossed) graphsMinitab Gage R&R summary graph
    • assessing measurement system variation; variance components and associated graphs
    • gage R&R study (crossed); gage R&R study (nested – for destructive measurements);
    • gage linearity and bias studies to measure stability of measurement system over time using
    • calculate statistics to assess linearity and bias of measurement system
  • MSA (Measurement Systems Analysis) terms and target values:
    • stability (statistical control),
    • Repeatability and Reproducibility (R&R), precision, accuracy, % study variation, % P / T,
    • discrimination,
    • bias, linearity of spread and bias
  • tree diagrams to model variance component models; crossed vs nested factors using tree diagrams

Gage Linearity and Bias StudyMinitab Linearity and Bias Graph and Analysis

  • Attribute Agreement Analysis, using binary, nominal and ordinal measurements:
    • graphic and statistical assessment of measurement system; kappa statistic; Kendall’s coefficient of concordance
    • Attribute Gage Study (Analytic Method) – AIAG long method
  • video on Sampling (from Against All Odds: Inside Statistics series);
  • Demonstration of Deming Funnel Experiment – overadjusting a process increases process variability!

Control Charts (SPC):

  • Xbar-S chart with stagesMinitab SPC chart with process stages identified
  • special cause variation; tests for special causes;
  • charts for continuous data:
    • X-bar, R charts;
    • X-bar and s charts;
    • I-MR charts;
  • charts for attributes data:
    • nonconforming units vs counts of nonconformities;
    • p and np charts; u and c charts;
    • binomial distribution (for proportions); Poisson distribution (for counts)
  • Discussion & idenfication of: Variability, Stability, and Capability;
  • specification limits vs control limits;
  • assumptions for SPC charts;
  • testing for independence, normality, and single source of variation
  • assumptions for Capability calculations;

Capability Analysis

  • Process Capability SixpackMinitab - Process Capability 6Pack
  • for continuous data:
    • Capability Sixpack and Analysis (Normal)
    • Cp, CPL, CPU, Cpk, CCpk, Pp, PPU, PPL, Ppk, Cpm
    • confidence intervals for capability indices
    • capability analysis with non-Normal data
    • individual distribution identification; Box-Cox transformation; Johnson transformation
  • capability analysis for attributes data:
    • binomial capability analysis
    • Poisson capability analysis
  • One Point Signal control charts: EWMA, CUSUM charts;
  • comparison of standard (Shewhart), EWMA, CUSUM charts;
  • what if assumptions of SPC are not met?
  • when to use SPC or Engineering Process Control?


Practice applying these tools using datasets from manufacturing quality applications (solutions included in workbook).

  • Measurement studies:
    • assessing consistency in color readings, paper breaking strength, improving the measurement system
    • attribute agreement for catalytic converter sustrates, hot sauce ratings
  • control charts:
    • continuous data: photograhic film density measurements, bath bar appearance, refractive index of fiber optic cable, door latch diameter
    • attributes data: inspecting gear assemblies
  • capability analysis:
    • continuous data: shifting the process, variation reduction
    • attribute data: polymer weight capability study

Each workshop participant receives an official Minitab workbook and data files, as well as a certificate for Recertification Units.

See other Minitab Training Courses, comments from previous participants, and some previous clients who have taken Carol Kavanaugh’s workshops!