Statistical Sampling Plans for Quality Engineers

Name: Statistical Sampling Plans for Quality Engineers
Rating: 4.7 (11 reviews)

Master ANSI Z1.4, ANSI Z1.9, C=0, and Minitab to confidently calculate valid sample sizes for quality audits.

Created byAndres Ruelas

Last updated 8/2023

English

What you'll learn

Learn How to Create Sampling plans for Industrial Process Control with ANSI Z1.4, Z1.9 and C=0
Use Minitab to Calculate Sampling Plan AQL, RQL, Alpha and Beta Values
Identify Which Sampling Plans to use based on the Manufacturing Process
Create Statistical Rationales justifying how many samples to take for process validation and process quality control

Course content

5 sections • 31 lectures • 3h 18m total length

Course Introduction, Table of Contents and Verified Vs Validated Processes7:17
After downloading the Minitab Exercise Files please open them depending on the Minitab version installed.
Files .MPJ are compatible with all versions of Minitab.
Files .MPX are only compatible with Minitab version 21 and newer.
Sampling by Attributes and Variables4:36
Explore two main sampling approaches - attributes and variables - and learn how international standards justify sampling plans. Compare pass/fail criteria with numeric measurements and process capability insights.
Exercise: Variable or Attribute Sampling?2:44
Explore attribute and variable sampling decisions through hands-on exercises using ANSI Z1.4, Z1.9, and Minitab, including diameter, length, burst test examples and non-fraction lot rules.

Attribute Based Sampling with Z1.4 and MIL-STD-1059:28
Explore attribute based sampling using ANSI Z1.4, Z1.9, and C=0; compare MIL-STD-105 with ANSI C1.4 and C1.9; learn how AQL defines acceptable defects.
Exercise: How many samples to take following Z1.4?3:45
Calculating AQL Values using Minitab and Understanding Producer Risk Alpha10:08
Exercise: Sampling with Minitab using Z1.43:40
apply NCC 1.4 sampling plans in Minitab to determine sample sizes for three lots and count defects to accept or reject each lot.
Introduction to RQL and Beta: Rejectable Quality Levels1:55
Exercise: Identifying RQL, AQL, Alpha and Beta Values1:34
Calculating RQL values of Z1.4 Sampling Plans using Minitab18:11
Conclusion: Calculating RQL Values of Z1.4 using Minitab4:14
Exercise: Calculate RQL values of Z1.4 Sampling plans using Minitab7:34
ANSI Z1.4 Single Based Sampling and Double Based Sampling Plans7:55
Calculating RQL Values with Minitab for Double Based Sampling Plans5:49
Demonstrate double bass sampling with Minitab, comparing 500-sample plans accepting 11 vs 15 defects, and determine acceptance, rejection, or additional sampling in gray areas guided by the rkl value.
Exercise: How Many samples for Double Based Sampling Plans?2:46
ANSI Z1.4 Normal, Tightened and Reduced Inspection Rules6:38
Analyzing Normal, Tightened and Reduced Inspection Plans with Minitab5:00
Compare normal, tightened, and reduced inspection plans for an AQL of one using Minitab, examining sample sizes of 315 and 125 and defect allowances.
Exercise: How many samples to take for Normal, Tightened and Reduced Inspection4:29
Determine sample sizes for normal, tightened, and reduced inspections (1250/21; 1250/18; 500/10) using Aql, Q, and Minitab; assess end-customer protection with rkl and beta 0.1.

Introduction to C=0 Attribute Sampling Plans11:43
Explore c=0 attribute sampling plans, where zero defects reject the lot, and see how cql, rql, and aql guide sample sizes 57, 35, 22 using minitab.
Exercise: Create C=0 Sampling plans that are equivalent to ANSI Z1.4 Plans2:54
Create C=0 sampling plans using ANSI Z1.4 to achieve 90% power at Rkl 1.5 with 153 samples and zero defects; also target 95% power at Rkl 1 with 299 samples.
Analyzing the difference between ANSI Z1.4 and C=0 sampling plans7:28
Compare ANSI Z1.4 and c=0 sampling plans, showing c1.4 tolerates defects while c=0 requires zero defects. See how rkl and beta in Minitab guide cheaper sample sizes with equivalent protection.
Why Don't all companies use C=0 Sampling plans?5:26
Explore why some companies switch from Ansi c 1.4 to c equals zero sampling plans, and how to determine rkl and aql, use conversion tables, and verify with Minitab.
Exercise: Creating C=0 Sampling plans that are equivalent to ANSI Z1.4 Minitab9:13
Learn to create equivalent c=0 sampling plans to ANSI Z1.4 using Minitab, deriving Rkl values, and matching end-user protection with 31, 43, and 54-sample plans.
CRITICAL LESSON: Don't Simply Switch from ANSI Z1.4 to C=0!5:31
Evaluate the trade-offs between ANSI Z1.4 and ANSI Z1.9 and C=0 sampling plans under Minitab, showing stricter quality and the need for system validation before switching.

Introduction to Variable Based Sampling Plans using ANSI Z1.914:57
Exercise: How many samples to take for ANSI Z1.9 Variable Sampling?4:25
Learn ANSI Z1.9 variable sampling: determine sample sizes using G3 with Aql 2.5% (35 samples, k=1.57) and G1 with Aql 0.10 (k=2.42, 15 samples), then accept or reject via Minitab.
ANSI Z1.9 Double Specification Sampling Plans10:46
explain the c1.9 double specification sampling method for double-sided limits, using aql 0.65, q and ql distances, and m and k thresholds to accept or reject lots with minitab.
Reducing the Number of Samples from ANSI Z1.9 using Minitab8:20
Reduce the number of samples in ANSI Z1.9 plans with Minitab by converting prior plans to variable-based sampling, adjusting CQL and the critical distance K, and comparing RQL values.
Exercise: Reducing the Number of Samples from ANSI Z1.9 using Minitab9:11
Explore reducing the number of samples in ANSI Z1.9 with Minitab by adjusting the AQL and CQL values and the critical k distance, demonstrating 25 vs seven and five samples.
Congratulations on Finishing this course. Closing Comments0:43
Conclude the sampling plan masters course with reflections on learning and invite study of quality engineering, Lean Six Sigma, Minitab statistics, process validations, and new product introductions at ksom academy.

Requirements

No Previous Minitab Experience Required.
No Previous Statistical Experience Required

Description

Master the art and science of statistical sampling plans to guarantee product quality, pass your compliance audits, and advance your engineering career.

In manufacturing, selecting the wrong sample size is a costly mistake. If your sample size is too low, you risk releasing defective products to the customer or failing an audit. If it is too high, you waste thousands of dollars in time and materials.

Sampling Plan Mastery is a straight-forward, step-by-step course designed to take you from a complete beginner to a confident Process Control Engineer who can justify exactly why a sample size was chosen using statistical evidence.

What You Will Master In This Course:

Attribute Sampling: Navigate and implement ANSI Z1.4 standards seamlessly.
Variable Sampling: Implement ANSI Z1.9 for continuous data characteristics.
Zero-Defect Sampling: Master the modern C=0 attribute plans to reduce inspection costs.
Advanced Switching Rules: Confidently transition between Normal, Tightened, and Reduced inspection states.
Minitab Integration: Use Minitab extensively to optimize your sampling sizes, saving your company money while protecting the end user.

Why Learn From CusumAcademy?
Led by Andres Ruelas, a veteran NPI Quality Engineer and Minitab specialist, this course bypasses dense academic jargon. Every lesson uses real-world manufacturing scenarios and step-by-step video instructions.

Stop guessing your sample sizes. Scroll up, click Enroll Now, and gain the statistical skills to back up your engineering decisions today.

Who this course is for:

Recommended for Quality Engineers, Manufacturing Engineers and Process Engineers
Engineers who need to create sampling plans following international standards
General Quality Staff Managers unfamiliar with process sampling in regulated industries
New Product Engineers who need to design inspection procedures

Statistical Sampling Plans for Quality Engineers

What you'll learn

Explore related topics

Course content

Introduction to Sampling Plans In Industrial Manufacturing3 lectures • 15min

Attribute Based Sampling Plan ANSI Z1.4 and MIL-STD-10515 lectures • 1hr 33min

Modern Attribute Based Sampling Plan C=06 lectures • 42min

Variable Based Sampling ANSI Z1.96 lectures • 48min

Consultoría y Preguntas para el Instructor1 lecture • 1min

Requirements

Description

Who this course is for: