Statistical quality control includes acceptance sampling and process control. Total quality management has more concepts apart from statistical quality control.
Acceptance sampling involves testing a random sample of existing goods and deciding whether to accept an entire lot based on the quality of the random sample.
Statistical process control involves testing a random sample of output from a process to determine whether the process is producing items within a pre-specified range. The details of techniques are presented in this chapter. Techniques for measurement of process control as well as charting procedures are presented along with a discussion of size of samples, number of samples, frequency of sampling, and control limits. Key points to consider are the costs to justify inspection as well as the correct sampling plan to ensure quality. While there are variations in every process, as variation is reduced, quality is improved.
Motorola made process capability famous by adopting its well-known six-sigma quality limits, ensuring only 3.4 defects per million using six-sigma quality limits. SPC recommends that a machine needs adjustments if the output is falling outside 3 sigma limits of the process. Motorola came out with the policy that they will employ processes whose six sigma limit on either side is equal to the difference between the acceptable specification level and the specified size. So naturally, the defects produced in the process will come down. Additionally, the six sigma limit will allow the process mean to drift up to 1.5 sigma and still the defect produced by the process will be only 2 per million items.
Motorola's Six Sigma program also has a method to analyze the existing processes and reduce their sigma or variability by studying the process by changing the input variables' levels and observing the resulting sigma.
KEY OUTLINE
Assignable Variation Defined
Common Variation Defined
Variation Around Us
Upper and Lower Specification or Tolerance Limits Defined
Process Capability
Six-Sigma Defined
Capability Index Defined
Capability Index (Cpk)
Process Control Procedures
Statistical Process Control (SPC) Defined
Attributes Defined
Process Control With Attribute Measurement: Using p Charts
Process Control With Variable Measurement: Using X-bar and R Charts
Variables Defined
How to Construct X-bar and R Charts
Acceptance Sampling
Design of a Single Sampling Plan for Attributes
Operating Characteristic Curves
Conclusion
Source
http://highered.mcgraw-hill.com/sites/0072983906/student_view0/technical_note8/
Full Material from the book
Video Lectures from MIT
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_____________
_____________
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Updated 7.12.2014, 31.5.2012, 10.12.2011
MBA Core Management Knowledge - One Year Revision Schedule
Acceptance sampling involves testing a random sample of existing goods and deciding whether to accept an entire lot based on the quality of the random sample.
Statistical process control involves testing a random sample of output from a process to determine whether the process is producing items within a pre-specified range. The details of techniques are presented in this chapter. Techniques for measurement of process control as well as charting procedures are presented along with a discussion of size of samples, number of samples, frequency of sampling, and control limits. Key points to consider are the costs to justify inspection as well as the correct sampling plan to ensure quality. While there are variations in every process, as variation is reduced, quality is improved.
Motorola made process capability famous by adopting its well-known six-sigma quality limits, ensuring only 3.4 defects per million using six-sigma quality limits. SPC recommends that a machine needs adjustments if the output is falling outside 3 sigma limits of the process. Motorola came out with the policy that they will employ processes whose six sigma limit on either side is equal to the difference between the acceptable specification level and the specified size. So naturally, the defects produced in the process will come down. Additionally, the six sigma limit will allow the process mean to drift up to 1.5 sigma and still the defect produced by the process will be only 2 per million items.
Motorola's Six Sigma program also has a method to analyze the existing processes and reduce their sigma or variability by studying the process by changing the input variables' levels and observing the resulting sigma.
KEY OUTLINE
Assignable Variation Defined
Common Variation Defined
Variation Around Us
Upper and Lower Specification or Tolerance Limits Defined
Process Capability
Six-Sigma Defined
Capability Index Defined
Capability Index (Cpk)
Process Control Procedures
Statistical Process Control (SPC) Defined
Attributes Defined
Process Control With Attribute Measurement: Using p Charts
Process Control With Variable Measurement: Using X-bar and R Charts
Variables Defined
How to Construct X-bar and R Charts
Acceptance Sampling
Design of a Single Sampling Plan for Attributes
Operating Characteristic Curves
Conclusion
Source
http://highered.mcgraw-hill.com/sites/0072983906/student_view0/technical_note8/
Full Material from the book
Video Lectures from MIT
_____________
_____________
_____________
______________
Updated 7.12.2014, 31.5.2012, 10.12.2011
MBA Core Management Knowledge - One Year Revision Schedule
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