1. Control Charts are tools for tracking variation based on the principles of probability and statistics SPC: Statistical Process Control

2. Variation Exists in any process  error rate made by receptionist entering guest record data,  bus time between two points,  ounces of beverage in a bottle,  number of minutes past the alarm that you stay in bed in the morning.

3. Sources of Variation: 2 Types Common (random) causes: chance or generally unidentifiable sources of variation.  Slight variation in walking speed  Slight variation in raw material Controllable or Assignable causes: A reason why the change occurred  people blunder, faulty setup, or a batch of defective raw material,worn equipment, fluctuating temperature  Super huge peanuts arrived from supplier so we only got 8 in each bag.

4. Controllable Causes (a) Location Grams Average

5. Controllable Causes (b) Spread Grams Average

6. Controllable Causes (c) Shape Grams Average

7. The Normal Distribution -3  -2  -1  +1  +2  +3  Mean 68.26% 95.44% 99.74%  = Standard deviation

8. How variation impacts our process: Generally random variation cannot economically be eliminated from a process. Controllable variation can be detected and elimination of its causes is economically justified. Observations beyond the control limits are attributed to controllable variation.

9. Process Control Chart Activities Periodically sample from our operation or process. Calculate some characteristic like average, standard deviation, or range. Plot the characteristic in time order on the chart.

10. Purpose of Charts To ensure the process variation is in control To ensure that the process is capable of meeting the requirements (specifications and tolerances of the organization)

11. Variable Control Charts (X bar & R) Measurement charts: some characteristic we can measure (weight, time, distance) X: average measurement for the sample R: range of the measurements in the sample Variable charts have lots of information, better for advanced analysis of a process

12. Control Limit Formulas & Constants (A2, D3, & D4) In Textbook pg. 167 Our sample size n= ?

13. Control Chart Examples Nominal UCL LCL Sample number Variations Appears to have normal variation

14. Control Chart Examples Nominal UCL LCL Sample number Variations A process with a gradual trend

15. Control Chart Examples Nominal UCL LCL Sample number Variations Points Outside of the Control limit

16. Attribute Chart: P-Charts Number of defective units in a sample. Yes/No, Pass/Fail, Go/No Go criteria  p- easy to measure (pass/fail) but sample size must be big enough to detect at least one defective item on average  p=percentage faulty in sample  N= size of the sample

17. Control Charts for Attributes UCL p = p + 3  p LCL p = p - 3  p  p = p (1 - p )/ n P-Chart

18. “Six Sigma Quality” When a process operates with  6σ variation inside the tolerance limits, only 2 parts out of a million will be unacceptable.