Understanding Single Sampling Attributes Acceptance Sampling for Defectives. Going beyond ANSI Z1.4  (701055LIVE)

Venue: Online

Location: Palo Alto, California, United States

Event Date/Time: Sep 30, 2008
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Description

This training will answer all your questions about acceptance sampling for defectives. The international standards will not be use the in this class. In this brief but intense class you will learn:

* How Single Sample Plans work.
* How sample sizes and acceptance number impact your ability to detect defectives.
* To take a risk-based approach to choose sampling plans.
* How you can set up your own statistically valid plans.
* To understand the probabilities involved in acceptance sampling (single sampling plans).
* About operating curves for such plans including AQL and RQL for manufacturer and customer protection.
* How to establish and justify confidence statements on the quality of your processes based on validation studies and/or historical data.

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Additional Information

Areas Covered in the seminar: This knowledge will help you to save resources by taking smaller samples that required by the ANSI and ISO standards How Single Sample Plans work * How sample sizes and acceptance number impact your ability to detect defectives. * To take a risk-based approach to choose sampling plans. * How you can set up your own statistically valid plans. * To understand the probabilities involved in acceptance sampling (single sampling plans). * About operating curves for such plans including AQL and RQL for manufacturer and customer protection. * How to establish and justify confidence statements on the quality of your processes based on validation studies and/or historical data. Who will benefit: This program is specially designed for personnel in: * Aerospace * Medical Device * Pharmaceutical and Biotechnology industries with daily responsibilities in the Quality Assurance * Regulatory Affairs * Compliance Auditing * Validation * Manufacturing * Consultants * Training * Quality Control * Product Submission