Human Error; Human Error Prevention; Human Error Reduction; Error; Human Performance; Human Performance Improvement; Root Cause Analysis; Corrective Action; Process Improvement

APPLIED STATISTICS FOR QUALITY IMPROVEMENT AND COST REDUCTION – 3 DAYS 

Why This Seminar?

Do you have trouble choosing a sample size – e.g., for validation studies? Are your QC sampling plans providing enough information about product quality? Are your calculations of product reliability yielding values that are unrealistically low, but you don’t know how to calculate ones that are more realistic? Are you unable to analyze reliability studies where not all the on-test devices could be made to fail? Are you uncertain how to analyze data sets that contain many replicate values? Are you unsure about how to choose measurement device calibration tolerances? Are you using SPC charts without a full understanding of their meaning? This seminar will address these and many other statistical concerns and will teach you how to understand the bases of applied industrial statistical methods.

Audience

This seminar is designed for anyone who must understand, apply and communicate quality and reliability statistics in the most effective way – e.g., six sigma team members.

Learning Objectives

Upon completion of this seminar, one will be able to more effectively perform six sigma and similar projects. Specifically, one will be able to:

  • Understand the basic theorems and practical vocabulary of statistics;
  • Calculate various product and process measures with confidence intervals;
  • Understand statistical “power” and when it needs to be calculated;
  • Assess data “normality” and understand how to transform non‐normal data into normality;
  • Handle data that cannot be transformed into normality;
  • Analyze incomplete data sets;
  • Set policies regarding measurement equipment calibration tolerances;
  • Evaluate a QC sampling plan and know how to change it to meet your needs;
  • Understand and use control charts to improve production processes;
  • Understand and calculate process capability indices – e.g., Cp, Cpk, Pp, and Ppk.

Outline

Day 1: Basic

  • Regulatory Requirements
  • Population vs. Sample
  • Parameter vs. Statistic
  • Probability
  • Law of Large Numbers
  • Distributions (Charting and Graphing)
  • Binomial Distribution
  • Normal Distribution
  • Central Limit Theorem
  • Standard Deviation and Standard Error
  • Linear Regression & Correlation Coefficients
  • Quiz

Day 2: Intermediate

  • Confidence Intervals
  • Significance Tests

–– Null Hypothesis

–– t‐Tests and P‐values

  • Power calculation (for t‐Tests)
  • Confidence & Reliability Calculations

–– Attribute (pass / fail) data

–– Variables (measurement) data

––– Normal vs. Non‐Normal data

––– K‐tables

––– Normal Transformations

–– Quiz

Day 3: Advanced

  • Reliability Plotting
  • Statistical Analysis of Gages
  • QC Sampling Plans
  • Statistical Process Control (SPC)
  • SPC Process Capability Indices
  • Quiz

Note:  Given one’s already existing understanding of the material to be covered in Day 1, one may opt to register for only Days 2 and 3 – of course, with a reduced registration fee.

Handouts

  • Copy of PowerPoint slides used for the seminar;
  • Copy of exercises and quizzes used for the seminar;
  • Certificate of Completion showing 7 education hours per day, with 0.7 Continuing Education Units per day that may be used toward university course credits or professional re-certifications, signed by your instructor

 

Human Error; Human Error Prevention; Human Error Reduction; Error; Human Performance; Human Performance Improvement; Root Cause Analysis; Corrective Action; Process Improvement