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Ashleigh NelsonDr. Tekel Wanorie - 54-315-01 : Operations ManaChapter 10 AssignmentOto!er "0# "014 - $ Worke% On This Assignmen

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ement

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Key

255523678.xls Data

Quality Control -- Assignment Problems. Note tat tere are tree sets o! "ata.

A.

#s te $ro%ess in %ontrol&

(Ounces, oz)

Sample # a b c d

' '(.)7 2'.2' 2*.5' 2'.'(

2 2'.)3 2'.*5 2'.)6 2'.)8

3 2*.'' 2'.37 '(.8( 2*.'8

) 2*.(* 2*.88 2*.5( 2'.'*

5 2'.2) 2*.)' 2*.'5 2'.5*

6 2*.75 2*.8' 2'.)3 2'.3)

7 2*.5* 2'.)' 2'.'2 2*.'*

8 2'.3) 2'.5* 2'.75 2'.)5

( 2*.*' '(.(* 2*.67 2*.(*

'* 2*.(* 2*.'2 2*.82 2*.73

'' 2'.'2 2'.'* 2*.'3 2*.7'

'2 2*.72 2'.33 22.*) 2'.3(

'3 2'.)( 2'.3) 2'.'8 2'.5*

') 2'.5* 2'.'( 2'.3) 2*.'(

'5 2*.)6 2*.'( 2*.57 2'.*3

'6 2*.37 2*.*8 2'.** 2*.87

'7 2*.28 2'.'* 2*.)7 2*.5('8 2*.)5 2*.52 2'.)7 2'.)'

'( 2'.2( 2'.35 2'.2( 2'.28

2* 2*.33 2'.2* 2*.25 2*.(8

2' 2'.22 2'.** 2*.56 2*.5)

22 22.** '(.52 2*.76 2'.38

23 2'.*7 2*.(7 2'.33 2*.5)

2) '(.(8 '(.67 2*.86 2'.*'

25 2*.22 2'.8) '(.65 2*.67

+. A!ter a number o! %om$laints about its "ire%tory assistan%e, a tele$one %om$any examine"

sam$les o! %alls to "etermine te !reuen%y o! rong numbers gi/en to %allers. 0a% sam$le

1se te !olloing "ata to %onstru%t one mean x-bar %art an" one range %art 4-%art.

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Key

255523678.xls Data

%oniste" o! '** sam$les.

#s te $ro%ess stable i.e, in %ontrol& Determine 2-sigma %ontrol limits.

am$le 0rrors

' 5

2 3

3 5

) 7

5 )

6 6

7 8

8 )

( 5

'* (

'' 3

'2 )

'3 5

') 6

'5 6

'6 7

'7 5

'8 )

'( 82* 2

C

i/en te !olloing "ata !or te number o! "e!e%ts $er s$ool o! %able, using tree-sigma limit,

is te $ro%ess in %ontrol& Com$ute 1C an" C.

bser/ation No. o! errors

' 2

2 )

3 '

) *

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Key

255523678.xls Data

5 '

6 3

7 2

8 *

( 2

'* '

'' 3

'2 3

'3 2

') '

'5 5

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Quality Control -- Assignment Probl Note that there are three sets of data.

A.

Is the process in control?

(Ounces, oz) X Bar Chart

Sample # a b c d Mean X Bar

1 19.47 21.21 20.51 21.19 20.60 20.872 21.43 21.05 21.46 21.48 21.36 20.87

3 20.11 21.37 19.89 20.18 20.39 20.87

4 20.90 20.88 20.59 21.10 20.87 20.87

5 21.24 20.41 20.15 21.50 20.83 20.87

6 20.75 20.81 21.43 21.34 21.08 20.87

7 20.50 21.41 21.12 20.10 20.78 20.87

8 21.34 21.50 21.75 21.45 21.51 20.87

9 20.01 19.90 20.67 20.90 20.37 20.87

10 20.90 20.12 20.82 20.73 20.64 20.87

11 21.12 21.10 20.13 20.71 20.77 20.87

12 20.72 21.33 22.04 21.39 21.37 20.87

13 21.49 21.34 21.18 21.50 21.38 20.8714 21.50 21.19 21.34 20.19 21.06 20.87

15 20.46 20.19 20.57 21.03 20.56 20.87

16 20.37 20.08 21.00 20.87 20.58 20.87

17 20.28 21.10 20.47 20.59 20.61 20.87

18 20.45 20.52 21.47 21.41 20.96 20.87

19 21.29 21.35 21.29 21.28 21.30 20.87

20 20.33 21.20 20.25 20.98 20.69 20.87

21 21.22 21.00 20.56 20.54 20.83 20.87

22 22.00 19.52 20.76 21.38 20.92 20.87

23 21.07 20.97 21.33 20.54 20.98 20.87

24 19.98 19.67 20.86 21.01 20.38 20.8725.000 20.22 21.84 19.65 20.67 20.60 20.87

52'.3(

X Bar Chart 1C9 2'.6*6 Average of Means:

C9 2*.'27 Range:

4 Cart 1C9 2.3*(

C9 *.***

Use the folloin! data to constr"ct one #ean $%&'ar( chart and one ran!e chart $

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R chart

UCL X LCL X Range R Bar UCL R LCL X

21.61 20.13 1.74 1.01 2.31 0.0021.61 20.13 0.43 1.01 2.31 0.00

21.61 20.13 1.48 1.01 2.31 0.00

21.61 20.13 0.51 1.01 2.31 0.00

21.61 20.13 1.35 1.01 2.31 0.00

21.61 20.13 0.68 1.01 2.31 0.00

21.61 20.13 1.31 1.01 2.31 0.00

21.61 20.13 0.16 1.01 2.31 0.00

21.61 20.13 1.00 1.01 2.31 0.00

21.61 20.13 0.78 1.01 2.31 0.00

21.61 20.13 0.99 1.01 2.31 0.00

21.61 20.13 1.32 1.01 2.31 0.00

21.61 20.13 0.32 1.01 2.31 0.0021.61 20.13 1.15 1.01 2.31 0.00

21.61 20.13 0.84 1.01 2.31 0.00

21.61 20.13 0.92 1.01 2.31 0.00

21.61 20.13 0.82 1.01 2.31 0.00

21.61 20.13 1.02 1.01 2.31 0.00

21.61 20.13 0.07 1.01 2.31 0.00

21.61 20.13 0.95 1.01 2.31 0.00

21.61 20.13 0.68 1.01 2.31 0.00

21.61 20.13 2.48 1.01 2.31 0.00

21.61 20.13 0.79 1.01 2.31 0.00

21.61 20.13 1.34 1.01 2.31 0.0021.61 20.13 2.19 1.01 2.31 0.00

25.32*

20.866

'.*'3

)&chart(.

1 2 3 4 520.00

20.20

20.40

20.60

20.80

21.00

21.20

21.40

21.60

,ol"#n -

* +ar,

1 2 3 4 5 60.00

0.50

1.00

1.50

2.00

2.50

3.00

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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

* +ar ,hart

,ol"#n ,ol"#n / ,ol"#n I ean

U, * , * *&+areanU,**

7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

) ,hart

)an!e ) +ar U, ) , *

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+. A!ter a number o! %om$laints about its "ire%tory assistan%e, a tele$one %om$any examine"

sam$les o! %alls to "etermine te !reuen%y o! rong numbers gi/en to %allers. 0a% sam$le

%oniste" o! '** sam$les.

#s te $ro%ess stable i.e, in %ontrol& Determine 2-sigma %ontrol limits.

am$le 0rrors Pro$ De!

' 5 *.*52 3 *.*3

3 5 *.*5 P= 0.0530

) 7 *.*7 UCL P= 0.0978

5 ) *.*) LCL P= 0.0082

6 6 *.*6

7 8 *.*8 P falls in between LCL and UCL

8 ) *.*)

( 5 *.*5

'* ( *.*(

'' 3 *.*3

'2 ) *.*)

'3 5 *.*5

') 6 *.*6

'5 6 *.*6

'6 7 *.*7

'7 5 *.*5

'8 ) *.*)

'( 8 *.*8

2* 2 *.*2

'*6 '.*6

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i/en te !olloing "ata !or te number o! "e!e%ts $er s$ool o! %able, using tree-sigma limit,

is te $ro%ess in %ontrol& Com$ute 1C an" C.

bser/ation No. o! errors

' 2

2 )3 ' C= 2.00

) * UCL= 6.24

5 ' LCL= 0.00

6 3

7 2 C falls between the two (UCL and LCL) wh

8 * !eans that it is in ont"ol

( 2

'* '

'' 3

'2 3

'3 2

') '

'5 5

30

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