Acceptance Sampling - Methods and Applications 2017

Topics

• Sampling Concepts
  • Defining the Operating Characteristic (OC) curve
  • Understanding Acceptable Quality Level (AQL)
  • Risk (producer and consumer) and the Sampling Plan
• Sequential sampling plans
  • Calculating the accept and reject regions
  • The sequential probability ratio
  • The fan chart as a special case
• Applications
  • Process validation
  • Design verification and validation
  • Incoming inspection
• Variables Sampling Using Z1.9
  • Variability unknown methods (range and standard deviation)
  • The methods (variability known and variability unknown)
  • Comparative sample sizes
  • Calculating the process parameters - the modern approach
  • Combining attributes and variables plans
• Skip-lot sampling plans (SkSP)
  • The OC curve
  • Defining the parameters
  • An alternate to Z1.4 reduced inspection (ANSI/ASQC S1)
• Chain sampling plans (ChSP)
  • The OC curve
  • Defining the parameters
• Continuous sampling plans (CSP)
  • Clearing interval
  • Processes that don`t produce lots
  • OC curve and Average Outgoing Quality Limit (AOQL)
  • Sampling fraction
  • Mil-Std-1235
  • CSP-1, CSP-2, and CSP-3
• Introduction/Fundamentals - Regulatory Requirements
  • Statistical techniques in ISO 13485
  • Statistical techniques in FDA QSR
  • Process and product monitoring
  • Validated processes
  • FDA Warning Letters
  • Design verification and validation
• Attribute Sampling using Z1.4
  • Single, double, or multiple sampling
  • Setting the sampling parameters (AQL and lot size)
  • Describing the sampling plan
  • Acceptance history (normal, reduced, or tightened sampling)
  • Average sample number (ASN)
  • OC curve
  • Average outgoing quality (AOQ)
  • Average total inspected (ATI)
  • Using Accept on Zero (AOZ) plans instead
• Attribute Sampling Using the Dodge-Romig System
  • Limiting Quality Level (LQL)
  • Average Outgoing Quality Limit (AOQL)
  • Using the system
• Introduction/Fundamentals - Statistics
  • Graphical Techniques
  • Descriptive Statistics
  • The hypergeometric distribution
  • The binomial distribution
  • Tests for normality
  • The normal distribution

Who should Attend

• Quality Engineers
• Quality Managers
• Quality Analysts
• Supplier Quality Engineers
• Design and Development Engineers
• Production and Process Engineers
• Verification and Validation Specialists