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GMS 401 (203)
Chapter 10

Chapter 10

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Department
Global Management Studies
Course
GMS 401
Professor
Kirk Bailey
Semester
Winter

Description
C HAPTER 10 – S TATISTICALQ UALITY C ONTROL INTRODUCTION - The best companies emphasize designing quality into the process, thereby greatly reducing the need for inspection/tests - Statistical quality control: use of statistical techniques and sampling in monitoring and testing of quality of goods and services - Important because it provides an economical way to evaluate the quality of products and meet the expectations of customers - Inspection: appraisal of good or service against a standard ⋅ Statistical Process Control Planning Process - Effective statistical process control requires the following planning steps: 1. Define the quality characteristics important to customers and how each is measured 2. For each characteristic a. Determine a quality control point b. Plan how inspection is to be done, how much to inspect, and whether centralized or on-site c. Plan the corrective action S TATISTICALP ROCESS C ONTROL - Statistical process control (SPC): statistical evaluation of the product in the production process ⋅ Types of Variations and Sampling Distributions - Random (or chance) variation: natural variation in the output of a process, created by countless minor factors - Assignable variation: non-random variability in process output; a variations whose cause can be identified ⋅ Control Charts - Control charts: a time-ordered plot of sample statistics with limits - Used to distinguish between random and assignable variation - Control limits: the dividing lines for the value of sample statistic between concluding no process shift and a process shift, hence random and assignable variations - Type 1 error: concluding that a process has shifted (an assignable variation is present) when it has not (only random variation is present) - Type 2 error: concluding that a process has not shifted (only random variation is present) when it has (an assignable variation is present) ⋅ Designing control Charts - The following steps are usually taken to design control charts 1. Determine a sample size n. the larger the better 2. Obtain 20 to 25 samples of size n 3. Establish preliminary control limits using appropriate formulas and graph them 4. Plot the sample statistic values on the control chart and note whether any points fall outside the control limits 5. If you find no points outside control limits, assume that there are no assignable cause and therefore the process is stable and in control. If not, investigate and correct assignable causes of variation; then repeat the process from step 2 and on ⋅ Sample Mean and Range Control Charts - Sample mean (xbar) control chart: the control chart for sample mean, used to monitor the process mean - Formula sheet! - Sample range (R) control chart: the control chart for sample range, used to monitor process dispersion or spread ⋅ Why Use both Sample Mean and Sample Range Control Charts? - Sample mean control charts provide different perspectives on a process - Sample mean control charts are sensitive to shifts in the process mean, whereas sample range control charts are sensitive to shifts in the process mean whereas sample range control charts are sensitive to changes in process dispersion or spread - Figure 10-10 page 332 ⋅ Individual Unit and Moving Range Control Charts - Individual unit (X) control chart: control chart for individual unit, used to monitor s
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