1. Statistical Process Control Chapters 20

2. 12345678 A B C D E F G H

3. Some Common Problems in Planning We plan in terms of actions (tasks) rather than objectives Responsibilities are not clear We plan in silos, out of context We underestimate the time and effort required to implement We don’t make reviews part of the plan.

4. Six-Step Problem-Solving Process Step 1: Identify and Select the problem Step 2: Analyze the problem Step 3: Generate Potential Solutions Step 4: Select and Plan the Solution Step 5: Implement the Solution Step 6: Evaluate the Solution

5. Statistical Quality Control Process Control Acceptance Sampling Variables Charts Attributes Charts VariablesAttributes Types of Statistical Quality Control

6. Measures performance of a process Uses mathematics (i.e., statistics) Involves collecting, organizing, & interpreting data Objective: Regulate quality Used to  Control the process as products are produced or service is performed Statistical Quality Control (SPC) key tool for 6 Sigma

7. Control Charts R Chart Variables Charts Attributes Charts  X Chart P C Continuous Numerical Data Categorical or Discrete Numerical Data Control Chart Types

8. Characteristics for which you focus on defects Classify products as either ‘good’ or ‘bad’, or count # defects  e.g., radio works or not Categorical or discrete random variables AttributesVariables Quality Characteristics ¨Characteristics that you measure, e.g., weight, length ¨May be in whole or in fractional numbers ¨Continuous random variables

9. Statistical Process Control Variations  Common cause: due to process itself  Special cause 2 ways of investigating variation  Plot data using histogram, looking for a normal distribution.

10. Standard Deviation 1 σ away from mean in either direction accounts for approx. 68% of readings in the group (red area) 2 σ away from mean in either direction accounts for approx. 95% of readings in the group (red and green area) 3 σ away from mean in either direction accounts for approx. 99% of readings in the group (red, green, and blue areas)

11. Process Control Charts

12. Show changes in data pattern  e.g., trends Make corrections before process is out of control Show causes of changes in data  Assignable causes Data outside control limits or trend in data  Natural causes Random variations around average Control Chart Purposes

13. Type of variables control chart  Interval or ratio scaled numerical data Shows sample means over time Monitors process average Example: Weigh samples of coffee & compute means of samples; Plot  X Chart

14. Type of variables control chart  Interval or ratio scaled numerical data Shows sample ranges over time  Difference between smallest & largest values in inspection sample Monitors variability in process Example: Weigh samples of coffee & compute ranges of samples; Plot R Chart

15. Formulas

16. Type of attributes control chart  Nominally scaled categorical data e.g., good-bad Shows % of nonconforming items Example: Count # defective chairs & divide by total chairs inspected; Plot  Chair is either defective or not defective p Chart

17. # Defective Items in Sample i Size of sample i z = 2 for 95.5% limits; z = 3 for 99.7% limits p Chart Control Limits i k 1i i k 1i i k i p p n x p and k n n n )p(p zpLCL n )p(p zpUCL           

18. Statistical Process Control Chart Using SPC to Address On-Time Medication Delivery

19. Type of attributes control chart  Discrete quantitative data Shows number of nonconformities (defects) in a unit  Unit may be chair, steel sheet, car etc.  Size of unit must be constant Example: Count # defects (scratches, chips etc.) in each chair of a sample of 100 chairs; Plot c Chart

20. # Defects in Unit i # Units Sampled Use 3 for 99.7% limits c Chart Control Limits

21. Process Capability C pk Assumes that the process is: under control normally distributed

22. Form of quality testing used for incoming materials or finished goods  e.g., purchased material & components Procedure  Take one or more samples at random from a lot (shipment) of items  Inspect each of the items in the sample  Decide whether to reject the whole lot based on the inspection results What Is Acceptance Sampling?

23. Set of procedures for inspecting incoming materials or finished goods Identifies  Type of sample  Sample size (n)  Criteria (c) used to reject or accept a lot Producer (supplier) & consumer (buyer) must negotiate What Is an Acceptance Plan?

24. Producer's risk (  )  Probability of rejecting a good lot  Type 1 error – results in over adjustment Consumer's risk (ß)  Probability of accepting a bad lot  Type II error – results in under adjustment Producer’s & Consumer’s Risk

25. ANY QUESTIONS?