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Agenda. AnnouncementsQuestionsHW1Control Charts (Variables) Cont.Quality CostsSPC Vs SQC (Inspections and Acceptance Sampling)Control Charts (Attributes)Process Capability. Quality Costs. . Quality Costs. Quality Cost: Traditional View TM2-5. Competitive Benefits of TQM Exhibit 2-8.
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1. ISQA 572/ 449Models for Quality Control/ Process Control and Improvement Dr. David Raffo
Tel: 725-8508, Fax: 725-5850
Email: davidr@sba.pdx.edu
2. Agenda Announcements
Questions
HW1
Control Charts (Variables) Cont.
Quality Costs
SPC Vs SQC (Inspections and Acceptance Sampling)
Control Charts (Attributes)
Process Capability
3. Quality Costs
4. Quality Costs
5. Quality Cost: Traditional View TM2-5
6. Competitive Benefits of TQM Exhibit 2-8
7. SPC Vs SQC (Inspections and Acceptance Sampling)
8. Approaches to Quality TM 4-1
9. Quality Control Modes TM 4-2
10. Statistical Process Control: Prevention TM 4-3
11. Disadvantages of Inspection Wasteful
Sampling and inspection add cost and decrease value
Inaccurate
Even 100% inspection is only 80% effective because of the possibility of human errors
Impractical(Costly)
Inspection may involve destructive testing
12. Disadvantages of Inspection Wrong message
Inspection communicates to people and suppliers that bad parts will still be tolerated.
Risks
In sampling and inspection there is a risk of accepting bad lots and rejecting good lots
No continuous improvement
Sampling is still inspection, not prevention, so that quality is not typically continuously improved.
13. Advantages of a Stable Process Management and workers know the process capability and can predict performance, costs and quality levels.
Productivity will be at a maximum and costs will be minimized.
Management will be able to measure the effects of changes in the system with greater speed and reliability.
14. Advantages of a Stable Process If management wants to alter specification limits, it will have the data to back up its decision.
(A stable process does not necessarily meet specs nor exhibit minimal variation - it’s just predictable)
15. Acceptance Sampling Acceptance sampling has three basic decisions: accept, reject, or resample.
Reason for using acceptance sampling:
Cost of passing defects is low
Destructive testing is required
Cost of inspection high relative to cost of loss
Assumes stable process
Large number of items must be processed in a short time
16. Acceptance Sampling Terms
Producer’s Risk (?): Risk of rejecting a lot with acceptable quality level. (type I error)
Consumer’s Risk (?): Risk of accepting a lot with unacceptable quality level. (type II error)
Acceptable Quality Level (AQL): The maximum percentage defective that can be considered satisfactory.
Lot Tolerance Percent Defective (LTPD): The percent defective where the consumer desires the probability of acceptance to be at a low level.
17. Acceptance Sampling - Attributes Types of plans
Single
N, n, c
(1000, 50, 1)
Double
N, n1, n2, c1, c2 , c3
(3000, 50, 80, 1, 3, 5)
Sequential
n, ca, cr
(50, 0, 4); (50, 1, 5)
18. Acceptance Sampling - Attributes Measures
Average Outgoing Quality (AOQ)
Average Total Inspection
Average Sample Number
Standard Sampling Plans
MIL-STD-105E
Dodge-Romig
Chain Sampling
Skip-Lot
Deming kp
19. Acceptance Sampling - Variables Advantages
Smaller sample than equivalent attribute plan
Provides more information
Provides insight into quality improvements
Disadvantages
Separate plan for each variable
Inspection costs are higher
Distribution estimate required
20. Acceptance Sampling - Variables Process Parameter
Average quality of the product/process or variability of the quality is known
Single Specification
n & Xa
Double Specification
n, XLa, XUa
Lot Proportion Nonconforming
Form 1 (k-method)
Form 2 (M-method)
21. Control Charts (Attributes)
22. Advantages & Disadvantages of Attribute Charts Advantages
Some quality characteristics can only be viewed as a attribute.
Quality characteristic may be measurable as a variable but an attribute is used for time, cost or convenience.
Combination of variables can be measured as an attribute rather than use a multivariate chart.
23. Advantages & Disadvantages of Attribute Charts Disadvantages
Attributes don’t measure the degree to which specifications are met or not met.
Doesn’t provide much information on cause.
Variable chart can indicate potential changes which allow preventive actions.
Larger sample size required.
24. Types of Attribute Charts p-Chart - Fraction Nonconforming
Can have constant or variable sample size.
Good tool for relating information about average quality level.
np-Chart - Number of Nonconforming
Number of nonconforming items may be easier for user to understand.
25. Types of Attribute Charts c-Chart - Number of Nonconformities
Used when desire is to control the number of defects where one defect may not cause the entire product to be defective.
Often used where area of opportunity is continuous and a constant size
26. Types of Attribute Charts u-Chart - Number of Nonconformities/unit
Area of opportunity is of variable size.
U-Chart - Number of Demerits/unit
Allows the use of variable weights for different classes of defects.
27. p Chart TM 4-12
28. p Chart TM 4-13
29. p Chart TM 4-14
30. p-Chart Exhibit 4-26
31. Hotel Suite Inspection - Defects Discovered Exhibit 4-27
32. C-Chart Calculations Centerline c-bar = (S c)/m #sub-groups
UCLc = c-bar + 3*sqrt(c-bar)
LCLc = c-bar - 3*sqrt(c-bar)
33. c Chart for Hotel Suite Inspection Exhibit 4-28
34. Process Capability
35. Process Capability Analysis Creates uniformity of output
Level of quality is maintained or improved
Facilitates product and process design
Assists in supplier selection and control
Reduces total costs
36. Process Capability : Normal Curve TM 4-15
37. Process Capability TM 4-17
38. Capability Indexes Cp
Ability to meet two-sided specification limits
Cp = (USL-LSL)/(6? )
Assumes
Stable process
Normal distribution
Variables data
Centered process
Goal Cp>1.0
39. Capability Indexes Capability Ratio
CR = (6?)/(USL-LSL)
Poor if CR>1
40. Capability Indexes CPU & CPL
Ability to meet one-sided specification limit
CPU = (USL-X)/(3?)
CPL = (X-LSL)/(3?)
Assumes
Stable process
Normal distribution
Variables data
41. Process Capability Chart Exhibit 4-20
42. Capability Indexes Cpk
Ability to meet two sided specification but the process does not have to be centered
Cpk = Cp - [|m-X|/(3?)] where m=nominal centerline
43. Process Capability Index TM 4-18
44. Process Capability: Varieties TM 4-19