Piece B, at 3.39 inches is nonconforming. Acceptance Sampling 6ħ We can also convert variables into attributes (often using a specification) Consider an important dimension with a specification of 3.5☐.1 inches. The critical dimension for this part number is 3.47 inches.
Is the shipment good enough to put into your inventory? How will you decide? Acceptance Sampling 4ĥ You have a few approaches Consider three potential solutions Look at all 5,000 widgets (100% inspection) Don t look at any, put the whole shipment into stock (0% inspection) Look at some of them, and if enough of those are good, keep the lot (Acceptance sampling) In a sampling plan, we need to know: How many to inspect or test? How to distinguish good from bad? How many good ones are enough? Acceptance Sampling 5Ħ First we need to distinguish two kinds of information Attributes We classify things using attributes A stop light can be one of three colors: red, yellow, or green The weather can be sunny, cloudy, raining, or snowing A part can be conforming or nonconforming Variables We measure things using variables The temperature of the oven is 350 F The tire pressure is 37 pounds per square inch (psi). Acceptance Sampling 2ģ Sampling Plans Some Initial Concepts Acceptance Sampling 3Ĥ A Typical Application You just received a shipment of 5,000 widgets from a new supplier. Focusing on the analytic skills and systems approach of operations management, Ombu helps companies achieve efficient, effective process and regulatory compliance. He has a Masters Degree in Mathematics is an ASQ certified Biomedical Auditor, Quality Engineer, Reliability Engineer, and Six Sigma Black Belt and is certified by APICS in Resource Management., LLC Ombu works with small manufacturing companies, offering training and execution in Operational Excellence.
1 Attributes Acceptance Sampling Understanding How it Works Dan O Leary CBE, CQE, CRE, CSSBB, CIRM, LLC Copyright 2008, 2009 by, LLC Acceptance Sampling 1Ģ Instructor Introduction Dan O Leary Dan has more than 30 years experience in quality, operations, and program management in regulated industries including aviation, defense, medical devices, and clinical labs.
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