【正文】 b u t m a y a l s o u s e a o r c h a r t o n n o n t i m e o r d e r e d d a t a s u c h a s w h e n c o m p a r i n g f a c i l i t i e s . i s t h e c o u n t o f o c c u r r e n c e s , i s t h e a v e r a g e。 3 p 177。 Occurrences are independent and rare 96 Exercise 10: Selecting a Control Chart Objective: Practice deciding which type of chart to try first for various situations. Time: 20 mins. Instructions: Work in small groups and fill in the right column. What You Are Measuring Appropriate Chart(s) and Possible Considerations 1. Cycle time from order until customer delivery 2. Monthly utility expenses 3. Patient‘s blood sugar level 4. Assembly time 5. Daily employee absenteeism percentage 6. Productivity ratio 7. Number of rings before phone is answered 8. Scrap percentage 9. Number of product returns 10. Days inventory on hand 11. Sales dollars (monthly or weekly) 12. Sales (units) 13. Water purity sampled 4 times each day 14. Yield 15. Number of machine Breakdowns (weekly) 16. Capacity utilization by line (percentage) 97 Exercise 10: Answers I Data may need transformation I I I Data may need transformation p I c or u p or I If n 1000, then use I c, u or I If c is not rare, then use I I I I X, R I (or if binomial) I (if is not rare) c or p By line (not time order), so don‘t connect dots with line What You Are Measuring Appropriate Chart(s) and Possible Considerations 1. Cycle time from order until customer delivery 2. Monthly utility expenses 3. Patient‘s blood sugar level 4. Assembly time 5. Daily employee absenteeism percentage 6. Productivity ratio 7. Number of rings before phone is answered 8. Scrap percentage 9. Number of product returns 10. Days inventory on hand 11. Sales dollars (monthly or weekly) 12. Sales (units) 13. Water purity sampled 4 times each day 14. Yield 15. Number of machine Breakdowns (weekly) 16. Capacity utilization by line (percentage) p c 98 Summary This module has covered: ? How to select an appropriate control chart ? How to use Minitab to construct control charts ? How to transform data ? How to spot control charts that don‘t look right and how to fix them ? How to interpret control charts ? How to maintain control charts Appendix: Discrete Data and Control Charts 100 Summary Table of Control Charts S i t u a t i o n C h a r t U s e d C o n t r o l L i m i t C a l c u l a t i o n s C o m m e n t s C o u n t i n g d e f e c t s h e N u m b e r o f d e f e c t s , a c c i d e n t s , o r f l a w s : o f a c c i d e n t s / m o n t o f b r e a k d o w n s / w e e k o f t i m e s t h e p h o n i s n o t a n s w e r e d w i t h i n t h r e e r i n g s o f f l a w s o n a n a u t o m o b i l e F r a c t i o n o f “ d e f e c t i v e s ” F r a c t i o n o f r e q u e s t s n o t p r o c e s s e d w i t h i n 1 5 m i n u t e s f r a c t i o n o f o r d e r s n o t p r o c e s s e d p e r f e c t l y t h e f i r s t t i m e t h r o u g h ( f i r s t p a s s y i e l d ) V a r i a b l e s d a t a , o n e f i g u r e a t a t i m e S a l e s , c o s t s , v a r i a n c e s , c u s t o m e r s a t i s f a c t i o n s c o r e , t o t a l V a r i a b l e s d a t a , s e t s o f m e a s u r e m e n t s c c h a r t u c h a r t n p c h a r t I n d i v i d u a l s c h a r t X 177。 peak of curve at the mean Binomial distribution Used for p Charts p is constant across subgroups。 could be caused by a different setup, raw material, the gage, or an operator made an adjustment ? Test 4 could be caused by different process streams, different lots, operators (running high amp。 Select ?Stamp‘ Enter ?Date‘ Data can be formatted like this (all measurements in one column) Our data are formatted this way。 R Chart) Start Type of data ? Equal sample sizes ? Equal opportunity ? p chart p rt np chart rt Individuals chart I i i al rt EWMA chart rt Continuous Yes No Yes Rational Subgroups Discrete Yes No No u chart u rt c chart c rt Do limits look right? Try individuals chart r i i i als chart Need to detect small shifts quickly? Individual measurements or subgroups ? Try transformation to make data normal r tr sformati to make ta rmal Do limits look right? Yes No Either/Or No Yes Individual measurements Occurrences X, R chart , rt Items with attribute Counting items with an attribute or counting occurrences? 78 When to Use X, R Charts ? Though used in both administrative and manufacturing applications, it is the tool of first choice in many manufacturing applications ? Advantages over other charts: ?Subgroups allow for a precise estimate of ―local‖ variability ? Changes in process variability can be distinguished from changes in process average ? Small shifts in process average can be detected 79 X, R Charts X, R Chart Average Transaction Time Each data point on the top chart represents the average of a subgroup. Each corresponding point on the lower chart represents the range within that subgroup. UCL = LCL = X = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 (4 samples each) (minutes) Range within subgroup (minutes) 0 1 2 3 4 5 6 7 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22