Quality Control. Dr. Richard Jerz rjerz.com

Transcription

1 Quality Control Dr. Richard Jerz 1

2 Specifying Quality Tolerances Fits Applies to manufacturing Applies to service, too 2

3 Purpose of Tolerances Impossible to make all parts to exact dimension Interchangeability of parts Avoid selective assembly Different degrees of size (toys versus jets) Quality depends upon repeatability and sizing Loose and tight fit 3

4 Fit Types (Parts) Clearance Always a clearance Interference Always interference Press fits Transition Clearance or interference depends upon specific parts 4

5 Clearance Fit 5

6 Standard Inch Fits Use of a symbols Typically not shown on drawings, dimensions are typically shown Symbols: RC, LC, LT, LN, FN Numbers degree of fit Complete Description Two letters and number Example: RC2 6

7 Design Suggestion Shafts rotating under 600 rpm with ordinary loads; >RC5 Shafts rotating over 600 rpm with heavy loads; < RC5 Shafts sliding freely; approx. LC Push fits with keyed shafts and clamp, no fitting; LT Parts assembled with some basic fitting; LN Permanent assembly with no freely moving parts; FN1 Permanent assembly with severe loading effects; FN3 Permanent assembly with press needed for assembly; FN5 7

8 Tolerance Example 1 RC7 Table 17 8

9 Matching Specs to Processes Capability analysis 9

10 Tolerances and Machining Processes 10

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14 Example: Robot Repeatability Data 14

15 Inspection Questions How Much/How Often Where/When Centralized vs. On site Inputs Transformation Outputs Acceptance sampling Process control Acceptance sampling 15

16 Inspection Costs Cost Total Cost Cost of inspection Optimal Amount of Inspection Cost of passing defectives 16

17 Methods of Assuring Quality Inspection before/after production Acceptance sampling Corrective action during production Process control Quality built into the process Continuous improvement The least progressive The most progressive 17

18 Where to Inspect in the Process Raw materials and purchased parts Finished products Before a costly operation Before an irreversible process Before a covering process 18

19 Examples of Inspection Points Type of business Fast Food Hotel/motel Inspection points Cashier Counter area Eating area Building Kitchen Parking lot Accounting Building Main desk Supermarket Cashiers Deliveries Characteristics Accuracy Appearance, productivity Cleanliness Appearance Health regulations Safe, well lighted Accuracy, timeliness Appearance, safety Waiting times Accuracy, courtesy Quality, quantity 19

20 Acceptance Sampling Form of inspection applied to lots or batches of items before or after a process, to judge conformance with predetermined standards (supplemental Chapter) 20

21 Statistical Process Control Statistical evaluation of the output of a process during production Define Measure Compare to a standard Evaluate Take corrective action Evaluate corrective action 21

22 What to Inspect? Variables Attributes 22

23 Error Conditions Type 1 Type 2 /2 /2 Mean Probability of Type I error LCL UCL 23

24 Type 1 and Type 2 24

25 Statistical Process Control Variations and Control Random variation: Natural variations in the output of process, created by countless minor factors Assignable variation: A variation whose source can be identified 25

26 Process Capability Tolerances (design) specifications Process variability Natural variability in a process Process capability Process variability relative to specification 26

27 Control Charts Statistics Normal distribution Central limit theorem Out of control 27

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29 Normal Distribution Standard deviation Mean 95.44% 99.74% 29

30 Control Limits Sampling distribution Process distribution Mean Lower control limit Upper control limit 30

31 Control Chart Figure 10-8 Abnormal variation due to assignable sources Normal variation due to chance Abnormal variation due to assignable sources Out of control UCL Mean LCL Sample number 31

32 Mean and Range Charts Sampling Distribution (process mean is shifting upward) UCL x-chart Detects shift LC L UCL R-chart Does not detect shift 32 LCL

33 Control Charts Warning conditions Two successive points near limit Run of five above or below mean Trend Erratic behavior 33

34 Industry Trends Continuous Improvement In process inspection 100% inspection Use of statistical quality control Deming concepts Automate control of equipment 34