Quality Training

Statistics with Minitab Module 2. Advanced

Objectives

This course is designed to give the learner in-dept practical skills in statistical data analysis with Minitab. It is available as a public or in-company session. For in-company training, we encourage learners to bring their work-related data to maximize their learning experience.

• Review of the Minitab environment.
• Review of key statistical fundamentals.
• Review of ANOVA as it applies to Gage R&R.
• Review of I-MR and Xbar-R control charts as they apply to capability analysis.
• Life-time probability distributions and their relevance to product reliability – Normal, Lognormal, Exponential and Weibull.
• Process capability analysis with Minitab – normal data, non-normal data, and distribution-free data.
• Acceptance sampling for process validation – RQL, AQL, alpha & Beta risks.
• Measurement system analysis – Type 1 Gage Study, GR&R (crossed and nested), Attribute Agreement Analysis.
• Linear regression analysis.
• Introduction to binary logistic regression analysis.
• Introduction to product reliability – overview, reliability estimation etc.

  Content includes

  Day 1: Capability Analysis

  1. Review Minitab Environment 2. Review key Statistical Concepts ü CLT, Central Tendency and Dispersion 3. Life-time Probability Distributions ü Normal, Lognormal, Exponential and Weibull distributions: § Visualize distribution properties – pdf, cdf, hazard function etc. § Use distributions to predict product failure. ü Learn how to use Minitab’s Individual Distribution Identification tool to find a distribution which best describes your data. 4. Review of Control Charts ü IMR Charts ü Xbar-R Charts 5. Assessing Process Capability ü Understand process capability assumptions. ü Understand capability metrics – Cp, Cpk, Pp, Ppk and Cpm. ü Learn how to use Minitab’s Capability Sixpack to assess assumption of normality. ü Learn how to analyse the capability of a stable process. ü Learn how to analyse capability of a non- normal process. ü Get an overview of non-parametric distribution methods.

Day 2: Measurement Systems Analysis (MSA) and Sampling for Validation

1. Acceptance Sampling by Attributes ü Review of Binomial Distribution ü Review of Hypergeometric Distribution ü Understand concepts and importance of acceptance sampling. ü Understand key indices such as AQL, LTPD/RQL, AOQL, OC Curve. ü Understand the risks associated with sampling – alpha and beta risks. ü Learn how to use Minitab to define a Zero Acceptance sampling plan for validation. 2. Measurement Systems Analysis (MSA) ü Understand key terminology – accuracy, precision, stability, linearity, repeatability, reproducibility etc. ü Learn how to use Gage Study Type 1 to determine capability and bias of your measurement system. ü Use Gage R&R (Crossed) to assess: § how well your measuring system can distinguish between parts being measured. § whether operators measure consistently. § Understand AIAG acceptability guidelines. § Understand the importance of “Gaurdbanding”. ü Learn how to conduct Gage R&R (Nested) study.

Day 3: Regression, Stability and Medical Device Reliability Analysis

1. Regression Fundamentals ü Understand key concepts and terms – response and regressor variables, least-squares method, residuals, coefficient of determination(R-sq) etc. ü Understand the difference between regression and correlation. ü Understand the difference between simple and multiple linear regression models. ü Understand data considerations for regression analysis. ü Understand the effect of multi-collinearity on your model. ü Learn when and how to use the following Minitab regression tools: § Fitted Line Plot § Fit Regression Model ü Understand how to analyse regression outputs from Minitab – plots, ANOVA, Model Summary, etc. 2. Introduction to Medical Device Reliability ü Overview of reliability terminology. ü Estimating reliability of implantable devices. ü Reliability Demonstration Test Plans. ü Regression with Life Data. End of Course Quiz

Who should attend

Personnel from Manufacturing, Quality, R&D, Product Design, Inspection & Test, Process Validation etc.

Upcoming dates:

No training dates available at the moment.