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Homepage > training offer > Closed training > Verification and Validation of Processes – Statistical Study Plans
Verification and Validation of Processes – Statistical Study Plans

Verification and Validation of Processes – Statistical Study Plans

Process approval (validation and verification) based on well-designed study plans (using statistics) is extremely important for two reasons: it helps avoid approving a defective process and protects against unjustified blocking of a process that meets the required quality standards. Both situations can generate significant costs. Therefore, beyond planning studies, their optimization is crucial in terms of risk borne by both manufacturers and customers, as well as in terms of costs (sample size).

The training prepares participants to conduct verification and validation of production processes using statistical methods. Selected statistical methods and the fundamentals of mathematical statistics will be discussed, and the development of effective study plans will be practiced. As a result, participants will gain practical knowledge that will enable them to manage processes more effectively while minimizing costs and risk.

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IN-COMPANY TRAINING

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2 days / 16 training hours
Stationary / On-line
The day may be established
Individual pricing
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TRAINING PROGRAM

For in-company training, the proposed program is a preliminary suggestion and can be freely adapted to the individual needs of the company.

The following program is indicative (the division into days is arbitrary) and the trainer adapts the course of the training to the specific characteristics of the group. Individual topics may be discussed at a different time or in a different form than indicated in the plan.

Module 1

INTRODUCTION TO STATISTICAL METHODS

Content:

  • Introduction to the use of statistics in industry
  • Basic statistical standards required for process verification and validation
  • Guidelines for validation and verification – overview
  • Probability distributions – overview of applications

Module 2

BASIC STATISTICAL TOOLS

Content:

  • Basic statistical measures – distinguishing between a parameter and a statistic
  • Data stratification
  • Use of a histogram for process evaluation
  • Confidence interval and reliability – basic information for study planning

Exercises:

Determination of basic statistical measures

Analysis of process behavior using histograms – practical cases

Module 3

NORMAL DISTRIBUTION – ESSENCE AND APPLICATION

Content:

  • Why is the normal distribution so important?
  • Methods of testing data normality (analytical and graphical tests)
  • Estimation of process defect rate using the standardized normal distribution
  • How to proceed when normality of the distribution cannot be confirmed

Exercises:

Testing distribution normality (graphical method)

Assessment of distribution type based on a probability plot – practical cases

Module 1

HYPOTHESIS TESTING

Content:

  • Type I and Type II errors (alpha and beta levels) in hypothesis testing – the basis for preparing study plans
  • Parametric tests for means and standard deviations (variances)
  • Nonparametric tests for comparing data sets
  • Testing for outliers (parametric Grubbs’ and Dixon’s tests and a nonparametric test)

Exercises:

Testing data sets for similarities and differences

Analysis of outliers – gross errors

Module 2

SELECTION AND EVALUATION OF STUDY PLANS

Content:

  • Study plan – what is it?
  • Selection of study plans based on ISO 2859 and ISO 3951 standards – overview of options
  • Why cannot study plans based on AQL be used for process validation?
  • AQL vs RQL – when to use which level
  • AOQL analysis when determining the appropriate acceptable defect level at the validation stage
  • Determination of sample sizes based on C and R for variable and attribute inspections
  • Determination and analysis of OC curves for study plans (consumer’s and producer’s risks)
  • What is the acceptance number in a study plan?
  • Selection of study plans based on guidelines
  • Single-stage vs double-stage plans – how to reduce sample size without increasing the risk of false signals
  • Alpha and beta levels – which is more important from the perspective of the company validating the process
  • Translating a study plan into AQL and Pp/Ppk

Exercises:

Selection of study plans based on ISO 2859 – simple and special cases

Determination of sample sizes based on C and R

Analysis of RQL values in relation to product safety

Selection of study plans based on OC curves – which plan is better for the supplier and which for the customer

ADDITIONAL INFORMATION

Most of the training consists of workshops involving the analysis of data from example processes. Training participants create and analyze study plans (based on real data). They also learn to use key indicators in the most practical way possible – whenever feasible, using their own data.

The detailed scope of the training will be agreed upon after further analysis of training needs.

After the training, each participant will receive a certificate confirming completion of the training.

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    Head of Quality Assurance Department
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