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Bayfield Mud Company Case Study

  • Dilip
  • Navjot
  • Amanpreet Singh

Introduction

According to the research study of the bag pounds problem, therefore the control division gathered the weight carrier as a sample from three several shifts (morning, afternoon, nighttime) every day. According to given article the six samples gathered per shift, which means size of the sample is usually six. To analysis the survey of three different shift, we will apply x-bar chart and selection chart.

Moreover we will need mean value we.e is 50, description listed below. In addition we may also calculate the number chart figure for each and every samples in different shifts, which will be find out by applying formula (Largest-Smallest).

Analysis

D3(Value extracted from Sigma table)=0

D4 (Value extracted from Sigma table)==2.004

N(Sample Size)=6

Standard Deviation=1.2

Desired Control Limit 3Sigma =99.73%

Formulation

For X Chart

UCL x (Top Control Limit for x bar) = X-Dbl Bar+Zï€ ï³x

Lower Control Limit (Top Control Limit = X-Dbl Bar-Zï€ ï³x

x= is certainly calculated by /Sqrt(n)

For R Chart

UCLR (Top Control Limit for the number) = D4*RBar

LCLR(Decrease Control Limit for the Range)= D3*Rbar

Morning Shift

For X Chart

For R Chart

Samples

Time

Shifts

Average

Smallest

Largest

Range

X Bar (Averages)

49.80

R-Bar (CL)

3.45

1

6

Day 1 Morning

49.6

48.7

50.7

2.0

UCLx

51.27

LCL r

0.00

2

7

50.2

49.1

51.2

2.1

LCLx

48.33

UCL r

6.91

3

8

50.6

49.6

51.4

1.8

CL

50

4

9

50.8

50.2

51.8

1.6

5

10

49.9

49.2

52.3

3.1

6

11

50.3

48.6

51.7

3.1

7

12

48.6

46.2

50.4

4.2

8

1

49

46.4

50

3.6

9

6

Day 2 Morning

48.6

47.4

52

4.6

10

7

50

49.2

52.2

3.0

11

8

49.8

49

52.4

3.4

12

9

50.3

49.4

51.7

2.3

13

10

50.2

49.6

51.8

2.2

14

11

50

49

52.3

3.3

15

12

50

48.8

52.4

3.6

16

1

50.1

49.4

53.6

4.2

17

6

Day 3 Morning

48.4

45

49

4.0

18

7

48.8

44.8

49.7

4.9

19

8

49.6

48

51.8

3.8

20

9

50

48.1

52.7

4.6

21

10

51

48.1

55.2

7.1

22

11

50.4

49.5

54.1

4.6

23

12

50

48.7

50.9

2.2

24

1

48.9

47.6

51.2

3.6

Afternoon Shift

For X Chart

For R Chart

Samples

Time

Shifts

Average

Smallest

Largest

Range

X Bar (Averages)

48.93

R-Bar (CL)

4.38

1

2

Day 1 Afternoon

49

46

50.6

4.6

UCLx

50.40

LCL r

0.00

2

3

49.8

48.2

50.8

2.6

LCLx

47.46

UCL r

8.78

3

4

50.3

49.2

52.7

3.5

CL

50

4

5

51.4

50

55.3

5.3

5

6

51.6

49.2

54.7

5.5

6

7

51.8

50

55.6

5.6

7

8

51

48.6

53.2

4.6

8

9

50.5

49.4

52.4

3

9

2

Day 2 Afternoon

49.70

48.6

51

2.4

10

3

48.4

47.2

51.7

4.5

11

4

47.20

45.3

50.9

5.6

12

5

46.8

44.1

49

4.9

13

6

46.8

41

51.2

10.2

14

7

50

46.2

51.7

5.5

15

8

47.4

44

48.7

4.7

16

9

47

44.2

48.9

4.7

17

2

Day 3 Afternoon

49.8

48.4

51

2.6

18

3

49.8

48.8

50.8

2

19

4

50

49.1

50.6

1.5

20

5

47.8

45.2

51.2

6

21

6

46.4

44

49.7

5.7

22

7

46.4

44.4

50

5.6

23

8

47.2

46.6

48.9

2.3

24

9

48.4

47.2

49.5

2.3

Night Shifts

X Bar Chart

R Chart

Samples

Time

Shifts

Average

Smallest

Largest

R-Bar

X Bar Average

48.65

R- Bar (CL)

3.36

1

10

Day1 Night

49.2

46.1

50.7

4.6

UCLx

51.50

UCLr

6.73

2

11

49

46.3

50.8

4.5

LCLx

45.80

LCLr

0

3

12

48.40

45.4

50.2

4.8

CL

50

4

1

47.6

44.3

49.7

5.4

5

2

47.4

44.1

49.6

5.5

6

3

48.20

45.2

49

3.8

7

4

48

45.5

49.1

3.6

8

5

48.40

47.1

49.6

2.5

9

10

Day 2 Night

47.2

46.6

50.2

3.6

10

11

48.6

47

50

3

11

12

49.8

48.2

50.4

2.2

12

1

49.6

48.4

51.7

3.3

13

2

50

49

52.2

3.2

14

3

50

49.2

50

0.8

15

4

47.2

46.3

50.5

4.2

16

5

47

44.1

49.7

5.6

17

10

Day 3 Night

49.2

48.1

50.7

2.6

18

11

48.40

47

50.8

3.8

19

12

47.2

46.4

49.2

2.8

20

1

47.4

46.8

49

2.2

21

2

48.8

47.2

51.4

4.2

22

3

49.6

49

50.6

1.6

23

4

51

50.5

51.5

1

24

5

50.5

50

51.9

1.9

Analysis Report

After calculating and analysing the three different shifts of three times. We can discover that second shift and third shift regularly uncontrollable. Although, 21 Samples of range chart is only uncontrollable which is 7.10 which is higher how to write scholarship essays than UCLr which is 6.9. Despite, this is only shift which is in charge.

By observing the next shift it is clearly noticed that x chart is out of control, whereas R chart of second shift is in charge only 13 Samples has gone out of control which is 10.20 whereas UCLr is definitely 8.7842

Right now, for third change, the X bar Chart the process is consistently uncontrollable whereas the R chart is flawlessly in control.

Recommendation.

In order to control the system, Company should be done some changes, point out below

  • In order to develop the productivity, training ought to be provide to the brand new employees especially in the night time shift. Another solution enterprise can shift experienced worker in night shift to maintain the balance.
  • Bayfield Mud Company should analyze their machinery on standard basis as recommended by managers. As we know a small issued can convert into big hindrance during execution.
  • Company should retain the services of some quality control expert who can take proper responsibilities of audit and track every issues with all documents in useful way.
  • Bayfield Company should do automated testing creative college essay topics device to observe the bag weights.

Unformatted text preview: Case Studies Bayfield Mud Company In November 2007, John Wells. a customer service representative of Bayfield Mud Company, was summoned to the Houston ware- houseofWet-Land Drilling, inc, to inspect three boxcars of mud— treating agents that Bayfield had shipped to the Houston firm. (B ayfield’s corporate offices and its largest plant are located in Orange, Texas, which is just west of the Louisiana—Texas border.) Wet-Land had filed a complaint that the 50~pound bags of treating agents ,just received from Baylield were short-weight by approxi- mately 5%. The short—weight bags vvere initially detected by one of Wet- Land’s receiving clerics, who noticed that the railroad scale tickets indicated that net weights were significantly less on all three box- cars than those of identical shipments received on October 25, 2007. Bayfield's traffic department was called to determine if'lighter- weight pallets were used on the shipments. (This might explain the lighter net weights.) Bayfield indicated, however, that no changes had been made in loading or palletizing procedures. Thus, Wet- Land cngineers randomly checked 50 bags and discovered phat the average net weight was 47.5] pounds. They noted from past ship- ments that the process yielded bag net weights averaging exactly 500 pounds, with an acceptable standard deviation o of 1.2 pounds. Consequently, they concluded that the sample indicated a signifi— cant short-weight. (The reader may wish to verify this conclusion.) Hayfield was then contacted, and Wells was sent to investigate the complaint. Upon arrival, Wells verified the complaint and issued a 5% credit to Wet—Land. Wet-Land management, however, was not completely satisfied with the issuance of credit. The charts followed by their mud engi- neers on the drilling platforms were based on 50—pound bags of treating agents. Lighter-weight bags might result in poor chemical Control during the drilling operation and thus adversely affect drilling efficiency. (Mudtreating agents are used to control the pH and other chemical properties of the core doling drilling operation.) This defect could cause severe economic consequences becausa oi the extremely high cost of oil and natural gas Well-drilling opera- tions. Consequently, special—use instructions had to accompany the deliver of these shipments to the drilling platforms. Moreover, the shalt-weight shipments had to be isolated in Wet-Land’s warehouse. causing extra handling and poor space utilisation. Thus, Wells was informed that Wet-Land might seek a new supplier of mud—treating agents it, in the lotto-e, it received bags that deviated significantly from 50 pounds. The quality control department at Hayfield suspected that the lightweight bags might have resulted from “growing pains” at the Orange plant. Because of the earlier energy crisis, oil arid natural gas exploration activity had greatly increased. in turn, this increased activity created increased demand for products produced by related industries, including drilling mods. Consequently, Bayiield had to expand from acne-shift (6:00 AM. to 2:00 PM.) to a two-shift (2:00 PM. to 10:00 PM.) operation in mid-2005, and finally to a three-shift operation (24 hours per day) in the fall of 2007. The additional night-shift bagging crew was staffed entirely by new employees. The most-experienced toremen were temporarily assigned to supervise the night-shift employees. Most emphasis was placed on increasing the outptti of bags to meet ever-increasing demand. [twas suspected that only occasional reminders were made to double-check the bag weight-feeder. [A double-check is per- ———_———?—_—n—__ Average Average Range Range Time (pounds) Smallest Largest Time {pounds} Smallest Largest 6:00 AM. 49.6 48.7 50.7 6:00 468 41.0 5 | .2 7:00 50.2 49.] 51.2 7:00 500 46.2 .5 | .7 8:00 50.6 49.6 51.4 8:00 474 44.0 48.? 9:00 50.8 50.2 51.8 9:00 47.0 44.2 48.9 10:00 49.9 49.2 52.3 10:00 47.2 46.6 50.2 11:00 50.3 48.6 51.7 11:00 48.6 47.0 50.0 12 Noon 48.6 46.2 50.4 12 Midnight 49.8 48.2 50.4 1:00 PM. 49.0 46.4 50.0 1:00 A.M’. 49.6 48.4 51.7 2:00 49.0 46.0 50.6 2:00 50.0 49.0 52.2 3:00 498 48.2 50.8 3:00 50.0 49.2 50.0 4:00 503 49.2 52.7 4:00 —-7.2 46.3 50.5 5:00 51.4 50.0 55.3 5:00 47.0 44.1 49.7 6:00 51.6 49.2 547 6:00 48.4 45.0 49.0 7:00 51.8 50.0 55.6 7:00 48.8 44.8 49.7 8:00 51.0 48.6 53.2 8:00 49.6 48.0 5| .8 9:00 50.5 49.4 52.4 9:00 50.0 48.1 52.7 10:00 49.2 46.1 50.7 10:00 5 l .0 48.1 55.2 1 [:00 49.0 46.3 50.8 11:00 50.4 49.5 54.| 12 Midnight 48.4 45.4 50.2 12 Noon 50.0 48.7 50.9 1:00 AM. 47.6 44.3 49.7 1:00 1-'.M. 48.9 47.6 51.2 2:00 474 44.l 49.6 2:00 498 48.4 51.0 3:00 482 ~52 490 3:00 49.8 48.8 50.8 4:00 48.0 —-5.5 491 4:00 50.0 49.1 50.6 5:00 48.4 47.1 496 5:00 47.8 45.2 51.2 6:00 48.6 47.4 52.0 6:00 46.4 44.0 49.7 7:00 50.0 49.2 52.2 7:00 46.4 44.4 50.0 8:00 49.8 49.0 52.4 8:00 47.2 46.6 48.9 9:00 50.3 49.4 51.7 9:00 48.4 47.2 49.5 10:00 50.2 49.6 51.8 10:00 49.2 48.! 50.7 1 |:00 50.0 49.0 52.3 | 1:00 48.4 47.0 50.8 12 Noon 50.0 48.8 52.4 12 Midnight 47.2 46.4 49.2 1:00 PM. 50.1 49.4 53.6 |:00 AM. 474 46.8 49.11 2:00 49.7 48.6 51.0 2:00 488 47.2 51.4 3:00 48.4 47.2 51.7 3:00 49.6 49.0 50.6 4:00 47.2 45.3 509 4:00 51.0 50.5 5| .5 5:00 46.8 —-4.1 490 5:00 50.5 50.0 519 formed by systematically weighing abttg on a scale to determine if Discussion lluestinns the proper weight is being loaded by the weight~feeden If there is Significant deviation from 50 pounds. corrective adjustments are made to the weighterclease mechanism.) To verify this expectation, the quality control staff randomly sampled the bag output and prepared the chart above. Six bags were sampled and weighed each hour. Source: Professor Jerry Kinard, Western Carolina University. 1. What is your analysis of the beg-weight problem? 2. What procedures would you recommend to maintain proper quality cotttroi? ...
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