Acceptance Sampling Plans - Made Easy
Upcoming Virtual Courses
Quality Systems
Acceptance Sampling Plans - Made Easy (March 2025)
Mar 25 to Mar 26, 2025
Overview
To the casual observer, Acceptance Sampling Plans can be incredible complex and hard to apply. Worse yet, the subject is a jungle with non-intuitive jargon and crazy acronyms. So why bother?
- The key advantage is that Sampling Plans can save time, money and resources. It certainly answers the question: How much is enough?”
- Sampling Plans help decision makers understand the risk involved in accepting a product or process.
- Well-designed training can cut through the jungle and provide a clear pathway.
This workshop provides a set of simple-to-follow procedures that will keep-it-simple to apply. A wide variety of industry applications will motivate the subject. While the terminology and acronyms used are “industry standard”, participants will not be burdened with statistical complexity. Participants do not need any background in statistics.
For FDA-regulated companies, sampling is a key statistical method used for Design Control, Process Validation, CAPA, complaint monitoring, and for Receiving, In-Process, & Finished Device Acceptance. We will discuss the recommendations of the guidance documents developed by the FDA and the Global Harmonization Task Force (GHTF) along with industry standards.
Objectives
The key to answering the question “How much is enough?” is to identify the risks involved in deciding on the quality of a product or process. At the end of this workshop, participants will be able to:
- Describe the factors that influence the selection of a sample size
- Apply valid statistical techniques for establishing sample size
- Clearly express the risk in a decision on the quality of a product or process
What to expect
There are two interactive deliveries in this workshop. Each part is two hours.
- Acceptance Sampling Plans for Variable Inspections
- Acceptance Sampling Plans for Inspection by Attribute
Each fast-paced webinar will cover the details of application without the burden of statistical complexity. Analysis results from popular statistical software programs will be illustrated.