Course "Statistical Sampling Plans - Methods and Applications" has been pre-approved by RAPS as eligible for up to 12 credits towards a participant's RAC recertification upon full completion.
Acceptance sampling plans are important tools for manufacturers. Effectively used they can help reduce costs while assuring quality and controlling risks. Unfortunately, this rich field of techniques is not as prominent as it once had been. As a result, quality practitioners don't always appreciate the wide range of available options or understand how to choose among alternate statistical sampling plans.
Because there are no published standards or guides to help select the right technique for each application, this workshop invaluable. For example, a sampling plan to make an acceptance decision on an incoming lot is not the right plan to sample records in a quality audit. Even incoming inspection has many viable options - variables sampling plans can significantly reduce inspection cost compared to common attributes sampling plans.
This workshop balances understanding the statistical concepts of sampling and creating practical applications. The workshop uses a large number of exercises to help participants understand the theories, master the techniques, and participate in practical exercises.
Any company that uses sampling plans can benefit from this workshop. The workshop uses examples from medical device manufacturing. However, the methods, tools, and techniques are not industry specific.
Why should you attend:
Nearly all companies use sampling plans as part of quality control and quality assurance. However, some methods are better suited to certain applications. Understanding the available methods can help make better choices to optimize cost and conformance.
Participants will learn the statistical basis for acceptance sampling plans and the tools and methods to describe them, particularly the Operating Characteristic curve. This forms the basis for selecting sampling plans and understanding the associated risk. In particular, regulators, such as FDA Investigators, expect companies to use this information to help implement valid statistical techniques. However, cost is a consideration as well. Participants will learn how to calculate sampling costs and use the information to help choose efficient plans that control the risk.
Participants receive a set of Excel spreadsheets that help explain and implement the sampling plans.
Who will benefit:
- Quality Managers
- Risk Managers
- Quality Engineers
- Production and Process Engineers
- Manufacturing Engineers
- Design Engineers
- Purchasing Managers
- Supplier Quality Engineers
- Quality Supervisors
- Quality Inspectors
Day 1 Schedule
Fundamentals - Regulatory Requirements
- Statistical techniques in FDA QSR
- Statistical techniques in ISO 13485:2016
- FDA Warning Letters
Fundamentals - Statistics
- Descriptive statistics
- Graphical techniques
- The binomial distribution
- The hypergeometric distribution
- The normal distribution
- Tests for normality
- Acceptable Quality Level (AQL)
- The Operating Characteristic (OC) curve
- Risk (producer and consumer) and the sampling plan
Attribute Sampling (Z1.4 & c=0)
- Sampling parameters (Level, Lot size, & AQL)
- Single, double, and multiple sampling plans
- Normal, reduced, and tightened sampling plans
- Describing the sampling plan
- OC Curve
- Discrimination and the Operating Ratio
- Average sample number curve (ASN)
- Average total inspected (ATI)
- Average outgoing quality (AOQ)
Attribute Sampling (Dodge-Romig)
- Understanding the system
- Average outgoing quality limit (AOQL)
- Limiting quality level (LQL)
Day 2 Schedule
Variables Sampling Using Z1.9
- Variability known and unknown methods
- Using the variability unknown method
- Comparative sample sizes
- Combining attributes and variables plans
Sequential Sampling Plans
- The sequential probability ratio
- Calculating the accept/reject region
- Using the fan chart as a special case
Continuous Sampling Plans
- Process that don't produce lots
- Plan Parameters - Clearing Interval & Sampling Fraction
- OC Curve and Average Outgoing Quality
- CSP-1, CSP-2, and CSP-3 sampling plans
Skip-lot Sampling Plans
- Defining the Parameters
- The OC Curve
- Alternate to Z1.4 Reduced Inspection - S1
Chain Sampling Plans
- Defining the parameters
- The OC Curve
Sampling Plans for Quality Audits
- Records as Audit Evidence
- Statistical Samples v. Convenience Samples
- Bounding the Error Rate
- Using FDA's Plans in QSIT
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President, Ombu Enterprises
Dan O'Leary is President of Ombu Enterprises, LLC, a company offering training and execution in Operational Excellence, focused on analytic skills and a systems approach to operations management. Dan has more than 30 years' experience in quality, operations, and program management in regulated industries including aviation, defense, medical devices, and clinical labs. He has a Masters Degree in Mathematics; is an ASQ certified Biomedical Auditor, Quality Auditor, Quality Engineer, Reliability Engineer, and Six Sigma Black Belt; and certified by APICS in Resource Management.
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