Textbook Notes (280,000)
CA (160,000)
Ryerson (10,000)
GMS (1,000)
GMS 401 (200)
Chapter 7

GMS 401 Chapter Notes - Chapter 7: Design Specification, Six Sigma, Process Capability

Global Management Studies
Course Code
GMS 401
Robert Meiklejohn

This 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
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
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
find more resources at oneclass.com
find more resources at oneclass.com
You're Reading a Preview

Unlock to view full version