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Quality Control. Ross L. Fink. Quality Control. Quality control involves controlling the delivery processes to adhere to the specifications (or product design). Quality Control Approaches. 100 % Inspection Acceptance Sampling Statistical Process Control (SPC) or Control-Chart Method.
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Quality Control Ross L. Fink
Quality Control • Quality control involves controlling the delivery processes to adhere to the specifications (or product design).
Quality Control Approaches • 100 % Inspection • Acceptance Sampling • Statistical Process Control (SPC) or Control-Chart Method
Acceptance Sampling Accept or Reject Entire Lot Based Upon Quality of Sample
Statistical Process Control • Basic Approach • Take one sample of size 5 each hour • Measure quality characteristic • Plot measurement over time (sample number)
Distribution of Measurement on Control Chart • Since we are taking a mean, the Central Limit Theorem of the Sample Mean applies • Therefore, mean follows a normal distribution. • Three Sigma Limits
Theory of Control Charts • Purpose of control charts is to separate natural variability (common cause) from nonrandom variability (assignable cause). • In-control (common cause) versus out-of-control (assignable cause).
Control Chart Rules • Simple Rules • One point above UCL • One point below LCL • Most organizations use more complex rules • e.g., seven consecutive points increasing
Constructing a Control Chart • Obs. 1 2 3 4 5 • Sample • 1 11.63 14.44 14.52 17.58 12.71 • 2 13.30 16.21 15.04 16.09 14.19 • 3 12.60 11.49 14.73 15.58 17.41 • 4 13.68 13.49 13.24 16.98 16.23 • 5 15.12 15.21 11.69 14.91 16.36 • 6 15.70 16.09 16.78 15.48 14.56 • 7 13.46 14.28 17.09 13.84 15.85 • 8 14.22 13.90 14.47 15.18 19.31 • 9 12.44 15.12 16.00 14.62 16.05 • 10 14.04 14.88 19.26 14.37 16.35 • 11 12.42 13.25 15.56 15.18 14.13 • 12 15.65 12.94 16.16 15.98 18.67 • 13 15.71 13.78 14.19 16.02 13.78 • 14 14.80 12.17 16.00 12.93 12.34 • 15 15.63 12.14 14.98 16.61 14.21 • 16 10.13 15.43 17.09 17.72 18.72 • 17 13.73 15.26 13.53 14.43 15.22 • 18 11.44 17.00 13.72 13.11 13.80 • 19 10.72 10.12 15.80 19.72 11.72 • 20 15.43 15.00 15.58 14.99 15.40
Find Sample Means and Ranges • Obs. 1 2 3 4 5 Mean Range • Sample • 1 11.63 14.44 14.52 17.58 12.71 14.18 5.95 • 2 13.30 16.21 15.04 16.09 14.19 14.96 2.93 • 3 12.60 11.49 14.73 15.58 17.41 14.36 5.92 • 4 13.68 13.49 13.24 16.98 16.23 14.72 3.75 • 5 15.12 15.21 11.69 14.91 16.36 14.66 4.67 • 6 15.70 16.09 16.78 15.48 14.56 15.72 2.22 • 7 13.46 14.28 17.09 13.84 15.85 14.90 3.63 • 8 14.22 13.90 14.47 15.18 19.31 15.42 5.39 • 9 12.44 15.12 16.00 14.62 16.05 14.85 3.62 • 10 14.04 14.88 19.26 14.37 16.35 15.78 5.22 • 11 12.42 13.25 15.56 15.18 14.13 14.11 3.14 • 12 15.65 12.94 16.16 15.98 18.67 15.88 5.72 • 13 15.71 13.78 14.19 16.02 13.78 14.70 2.23 • 14 14.80 12.17 16.00 12.93 12.34 13.65 3.83 • 15 15.63 12.14 14.98 16.61 14.21 14.71 4.47 • 16 10.13 15.43 17.09 17.72 18.72 15.82 8.59 • 17 13.73 15.26 13.53 14.43 15.22 14.43 1.73 • 18 11.44 17.00 13.72 13.11 13.80 13.81 5.56 • 19 10.72 10.12 15.80 19.72 11.72 13.61 9.60 • 20 15.43 15.00 15.58 14.99 15.40 15.28 0.59
Table • Factors for Computing Control Chart Limits • Sample Size Mean Factor Upper Range Lower Range • N A2 D4 D3 • 2 1.880 3.268 0 • 3 1.023 2.574 0 • 4 .729 2.282 0 • 5 .577 2.115 0 • 6 .483 2.004 0 • 7 .419 1.924 0.076 • 8 .373 1.864 0.136 • 9 .337 1.816 0.184 • 10 .308 1.777 0.223
In-Control v. Out-Of-Control • What are the implications of being in-control? • What are the implications of being out-of-control?