Process Capability and Statistical Quality Control - Review Notes

Statistical quality control includes acceptance sampling and process 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 prespecified range. The techniques presented in this chapter are used to ensure quality control of processes and output. 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.

Process control monitors quality while the product or service is being produced. 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. 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.

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
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Updated 31.5.2012
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