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Chapter 7

School

Ryerson UniversityDepartment

Global Management StudiesCourse Code

GMS 401Professor

Robert MeiklejohnChapter

7This

**preview**shows page 1. to view the full**4 pages of the document.**GMS – Chapter 7 – Statistical Quality Control

Statistical quality control – use of statistical techniques and sampling in monitoring and testing

of quality of G and S

Important because it provides an economical way to evaluate the quality of products and meet

expectations of the customers

Acceptance sampling – the part of statistical quality control that relies primarily on inspection

of previously produced items

Inspection – appraisal of a G or S against a standard

Statistical process control planning process

1. Define a quality control point

2. For each characteristic: (1) determine a quality control point (2) plan how inspection is

to be done, how much to inspect and whether centralized or on site

3. Plan the corrective action

Statistical process control (SPC) – statistical evaluation of the product in the production

process

Operator takes periodic samples from the process and compares the with

predetermined limits

Random variation – natural variation in the output of a process, created by countless

minor factors

Assignable variation – non-random variability in process output; a variation whose

cause can be identified

Periodic samples of process output are taken and sample statistics, such as sample

means or the number of occurrences of certain types of outcome are determined

The variability of samples statistic is described by its sampling distribution

The frequency of the distribution would reflect the process variability

The sample distribution of the sample mean exhibits less variability than process

distribution

Sample distribution is approximately normal

Central limit theorem – the distribution of sample averages tends to be normal

regardless of the shapes of the process distribution

Control chart – a time oriented plot of sample statistic with limits

Used to distinguish between random and assignable variation

Purpose is to monitor process output to see if it is random

Minor difficulty: the theoretical distribution extends in either direction to infinity,

meaning any value is theoretically possible

Control limits – the dividing lines between random and assignable deviations from the

mean of the distribution

UCL (upper control limit), LCL (lower control limit) – a sample that falls between the two

limits is considered random variation, outside: assignable variation

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