Lecture 5_Outline - Quality & Performance

Lecture 5_Outline - Quality & Performance - Lecture...

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Lecture 5 - Outline 1 Lecture 5: Quality and Performance (Textbook Chapter: 5) Objectives z Costs of Quality z Total Quality Management z Six Sigma z Acceptance Sampling z Statistical Process Control z Statistical Process Control Methods z Process Capability Cost of Quality - A failure to satisfy a customer is considered a defect - Prevention costs - Appraisal costs - Internal failure costs - External failure costs - Ethics and quality Total Quality Management z Customer satisfaction ± Conformance to specifications ± Value ± Fitness for use ± Support ± Psychological impressions z Employee involvement ± Cultural change ± Teams z Continuous improvement ± Kaizen
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Lecture 5 - Outline 2 ± A philosophy ± Not unique to quality ± Problem solving process The Deming Wheel Six Sigma Six Sigma Improvement Model Acceptance Sampling z Application of statistical techniques z Acceptable quality level (AQL)
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Lecture 5 - Outline 3 z Linked through supply chains Statistical Process Control z Used to detect process change z Variation of outputs z Performance measurement – variables z Performance measurement – attributes z Sampling z Sampling distributions Sampling Distributions 1. The sample mean is the sum of the observations divided by the total number of observations 2. The range is the difference between the largest observation in a sample and the smallest. The standard deviation is the square root of the variance of a n x x n i i = = 1
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Lecture 5 - Outline 4 distribution. An estimate of the process standard deviation based on a sample is given by where σ = standard deviation of a sample Sample and Process Distribution: Causes of variation z Common causes ± Random, unavoidable sources of variation ± Location ± Spread ± Shape z Assignable causes ± Can be identified and eliminated ± Change in the mean, spread, or shape ± Used after a process is in statistical control () ( ) 1 or 1 2 2 = σ = σ n n x x n x x i i i 2
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Lecture 5 - Outline 5 1. Control charts: A time-ordered diagram that is used to determine whether observed variations are abnormal. - A sample statistic that falls between the UCL and the LCL indicates that the process is exhibiting common causes of variation; a statistic that falls outside the control limits indicates that the process is exhibiting assignable causes of variation. a. Indicators of out of control conditions
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Lecture 5 - Outline 6 ¾ Control charts are not perfect tools for detecting shifts in the process distribution because they are based on sampling distributions. Two types of error are possible with the use of control charts.
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This note was uploaded on 02/14/2011 for the course MGSC 395 taught by Professor Zimmer during the Fall '10 term at South Carolina.

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Lecture 5_Outline - Quality & Performance - Lecture...

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