The final presentation from the Team, IT of Seoul Tech.

1. Members: Jin-Yong Yim
Seung-Min Noh
Chan-Bum Jung
Faculty Advisor: Dr. Seong-Yong Jang

2. Objectives#1
Scenario 1#2
Scenario 2#3
IT‘s Recommendations#4
Additional Problems
#5 Conclusion
#6

3. Objectives

4. Objectives
Aims to The Successful Consulting
Minimize Total Travel
Distance & Time
Minimize The Scrap
Identify Optimal # of Operators
& Their Utilization

5. Scenario 1

6. Scenario 1
1st Recommendation
Positioning of Machines
2nd Recommendation
Optimal # of Operators

7. 1.PositioningofMachines
Generate Machines’ Layout Alternatives
Step 1
Compare Each Alternative
Recommend the Best Layout
Step 3
1 2 3
Positioning
From-To
Chart
Cell
Grouping
Pareto
Rule

8. Step 1 : Generate Machines’ Layout Alternatives
1
Layout Alternative 1
Travel Distance
Machine NJ Location
Travel DistanceFrequency
Frequency
Machine NJ Location

9. NJ01 NJ02 NJ03 NJ04 NJ05 NJ06 NJ07 NJ08 NJ09 NJ10 NJ11 NJ12 Total
M #1 133,212 1,938 18,624 5,568 44,340 0 12,699 230,753 2,142 33,147 70,866 22,248 575,537
M #2 217,355 29,365 12,597 541 128,960 41,940 62,118 31,456 29,992 298,840 59,520 30,705 943,389
M #3 134,853 7,329 8,239 8,239 88,179 2,144 16,128 101,460 13,884 35,464 26,598 16,224 458,741
M #4 233,916 1,656 4,092 0 95,535 2,283 4,852 0 1,298 124,740 31,185 1,760 501,317
M #5 187,179 19,775 5,526 0 163,275 43,260 17,820 15,264 64,584 37,544 49,818 15,552 619,597
1
Layout Alternative 1
Machine
Location
·
·
·
Rank Machine # Contribution Volume Rank Machine # Contribution Volume
1 2 943,389 17 9 428,625
2 26 705,687 18 14 424,318
3 7 669,169 19 10 407,977
4 16 652,457 20 11 381,077
5 5 619,597 21 15 366,854
6 1 575,537 22 22 357,430
7 8 572,260 23 6 320,774
8 29 546,944 24 20 308,723
9 13 536,634 25 18 288,907
10 17 528,823 26 28 223,439
11 4 501,317 27 33 219,898
12 19 462,063 28 21 196,969
13 25 459,644 29 12 181,573
14 3 458,741 30 24 117,676
15 23 435,284 31 32 66,174
16 27 430,465 32 31 11,311

10. 1Alternative
Layout Alternative 1
Masters Molding
Facility Layout
Molding Machines
Material / Die Locations
Dryer Corral
Order and Dryer Boards
Die Trucks
Finished Parts
Lift Trucks
Key
2
7
26
NJ05
NJ01
5
16
1
3
4
6 9
8
10
11
17
15
14
13
12
20
18
19
31
32
33
28
29
21
22
23
24
30
25
27 NJ12
NJ02
NJ03
NJ04
NJ09
NJ08
NJ07
NJ06
NJ11
2
NJ01
26
NJ05
7
NJ10NJ10

11. Step 1 : Generate Machines’ Layout Alternatives
2
Layout Alternative 2
indicate that a machine assigned to a cell is not required
by all parts assigned to that cell.
indicate that a part assigned to a cell requires processing
by a machine not in the cell.
What is the

12. 2
Layout Alternative 2
Given a P-M matrix, what makes one partitioning better than another?

13. 2
Layout Alternative 2
Ronald G. Askin, and Charles R. Standridge. (1993).
“Modeling and Analysis of Manufacturing Systems.” John Wiley & Sons, Inc.Reference

14. 2
Layout Alternative 2

15. 2
Layout Alternative 2
Only …
If Frequency >= 60, Then Value = 1

16. Layout Alternative 2
Group C Group B Group A
2

17. Masters Molding
Facility Layout
Molding Machines
Material / Die Locations
Dryer Corral
Order and Dryer Boards
Die Trucks
Finished Parts
Lift Trucks
Key
2Alternative
Layout Alternative 2
3
5
17
25 26
NJ05
NJ01
2
22
23
18
29
7
16
27
4
14
13
10
21
28
831
24
32
19
11
20
NJ12
NJ10
6 15
3330
12
1
9
NJ02
NJ03
NJ11
NJ04
NJ09
NJ08
NJ07
NJ06
3
5
17
25 26
NJ05
NJ01
2
22
23
18
29
7
16
27
Group A
4
14
13
10
8
19
NJ12
NJ10
Group B
12
1
9
NJ02
NJ03
NJ11
Group C

18. Step 1 : Generate Machines’ Layout Alternatives
3
Layout Alternative 3
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
1000000
2 26 7 16 5 1 8 29 13 17 4 19 25 3 23 27 9 14 10 11 15 22 6 20 18 28 33 21 12 24 32 31
ContributionVolume
Machine #
Pareto Contribution Volume Analysis
Group A
(20%)
Group B
(30%)
Group C
(50%)

19. 3
Layout Alternative 3
14
28 29
NJ05
NJ0113
25
22
19
32
5 4
11
17
20
12
30
10
1
16
24
3
6
15
18
8
21
26
7
9
23
27 NJ12
NJ02
NJ03
NJ04
NJ09
NJ08
NJ07
NJ06
NJ11
NJ10
NJ05
NJ01
33
312
231
14
28
22
32
33
11
20
12
31
10
24
6
15
18
21
9
14
28
22
32
33
11
20
12
10
24
6
15
18
21
9
31
2
33
7
7
33
14
28
22
32
11
20
12
10
24
6
15
18
21
9
1
NJ08
115
15
Total Travel Distance
1992
1934
1881
1832
19921934 (-58)1881 (-111)1832 (-160)
Priority
1. Proximity
2. Space
3. Contribution volume
Alternative

20. Step 2 : Compare Each Alternative
Compare Alternatives
$ 5,964,000
$ 4,513,000
$ 1,568,000
1992 miles
(602 hr) 1785 miles
(539 hr)
1794 miles
(542 hr)
1832 miles
(554 hr)
1,000,000
3,000,000
5,000,000
7,000,000
9,000,000
0
500
1,000
1,500
2,000
2,500
The Initial From-To Chart Cell Grouping Pareto Rule
Cost ($) Distance (miles)

21. 2.Optimal # of Operators
Optimal # of Operators
Step 1
Operators’ Utilization
Operators

22. # of Operators
84%
87%
91%
95%
99%
75%
80%
85%
90%
95%
100%
105%
16 17 18 19 20
Quality Control Satisfaction
(22,000 hrs)
# of Operators
TheLevelofQualityControlSatisfaction
(19,800 hrs)
Step 1 : Optimal # of Operators

23. Operators‘ Utilization
Step 2 : Operators’ Utilization
Operators’ Utilization
20%
40%
60%
80%
100%
10 Operators 18 Operators
73 %
82 %

24. Scenario 2

25. Scenario 2
1st Recommendation
Adding Dedicated
Material Handlers?
2nd Recommendation
Adding Dedicated
Quality Resources?

26. Scenario 2
Dedicated Material Handler’s Utilization
: appx.
Total # of Operators Required including One Material Handler
: 18
1st Recommendation
Adding Dedicated Material Handlers?
Efficiency was not improved

27. Scenario 2
# of Quality Resources Required
: 5 (Based on Quality Control Level)
Total # of Operators Required
: 18
2nd Recommendation
Adding Dedicated Quality Resources?
Efficiency was not improved

28. IT‘s Recommendations

29. IT‘s Recommendation
New Construction (Arena 3D Player Animation)

30. IT‘s Recommendation
1. Remove the dryer transporting time
2. Reduce travel time with more open space by eliminating the dryer corral
3. Lift trucks are no longer necessary because raw materials are located
on the 2nd floor
4. Shorten travel distance due to more open space on the 2nd floor
5. Save money by decreasing the total number of operators in the plant
6. Cost of changing the layout is moderate compared to the other three
machines’ layout alternatives
Advantages of IT’s Recommendation

31. IT‘s Recommendation
These figures were estimated based on the cost value of Korean molding companies.
$ 1,364 X 33
= appx. $ 45,000
(Fixed Dryer Hoppers)
(Iron Floor )
$ 392 X 1530 Square ft
= appx. $ 600,000
(Oven Dryer )
$ 5,000 X 1
= appx. $ 5,000
Cost
Total
Cost
Dryer
Floor
Oven

32. IT‘s Recommendation
Extract the scraps from the finished goods
Insert the scraps into the mixer machine
Insert raw materials into the mixer machine
Mix the scraps with the raw materials(Recycling)
Produce new raw materials
Scrap
Raw
material
Scrap
Crush the scraps using a disintegrator
Raw
Material
Scrap

33. Conclusion

34. Conclusion
$ 5,964,000
$ 4,513,000
$ 1,568,000 $ 650,000
1992 miles
(602 hr) 1785 miles
(539 hr)
1794 miles
(542 hr)
1832 miles
(554 hr)
1585 miles
(476 hr)
0
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
0
500
1,000
1,500
2,000
2,500
The Initial From-To Chart Cell Grouping Pareto Rule IT's
Recommendation
Cost ($) Distance (miles)

35. Additonal Problem

36. Additional Problems
WorkStation 1
TRIA(7, 9, 12)(min)
WorkStation 2
TRIA(4, 8.5, 15)(min)
WorkStation 3
TRIA(5.6, 9.8, 17)(min)
Bubbles, cracks, etc Further assembly steps
Additional Assembly Line
(2%)
* Rejection Rate
Wastes
(7.7%)Rework(7%)Rework

37. Additional Problems
WorkStation 1 WorkStation 2 WorkStation 3
# in Queue(PC) 0.010(Max.2) 0.005(Max.2) 0.007(Max.2)
Utilization(%) 9.36 10.10 10.98
# of scrapped parts
Average cycle time
(for the parts that are not rejected at any workstation)
Maximum cycle time
(for the parts that are not rejected at any workstation)
# of times a rejected part was rejected
Collected Statistics
52 pieces
25.881 minutes
38.958 minutes
5 times

38. Additional Problems
Comparison of Alternatives Time (min)
The initial cycle time 25.881
The cycle time by the queue priority 26.586
The cycle time by creating new re-workstations 25.514
Collected Statistics
WorkStation 1
TRIA(7, 9, 12)(min)
WorkStation 2
TRIA(4, 8.5, 15)(min)
WorkStation 3
TRIA(5.6, 9.8, 17)(min)
Re-WorkStation 1
The processing time is
increased by 50%
Re-WorkStation 2
The processing time is
increased by 50%

39. Q & A

40. Appendix

41. Appendix (Pareto Rule)
Select the candidate machine in close proximity to the Group A - machine’s
most critical two NJ locations
Rule 1.
Select the candidate machine which can fit for the Group A - machine’s
space
Rule 2.
Select the candidate machine which is less important by the total contribution
volume than the other candidate machines in Group C
Rule 3.

42. Appendix (Cell Grouping)
Selected Values of 40 or more
Too Large number of 1’s

43. Appendix (Cell Grouping)
Selected Values of 80 or more
Too Small number of 1’s

44. Appendix (Cell Grouping)
Selected Values of 60 or more
Grouping efficiency = 0.811 Grouping efficacy = 0.500
Alternative 1

45. Appendix (Cell Grouping)
Alternative 2
Grouping efficiency = 0.756 Grouping efficacy = 0.463
Selected Values of 60 or more

46. Appendix (Cell Grouping Method)
Step 1
( Machine-part matrix )
The direct clustering algorithm
( Ordered machine-part matrix )
Example

47. Appendix (Cell Grouping Method)
Step 2
( Column-sorted machine-part matrix )
Sorting the columns to move toward
the left all columns having a 1 in the
first row
Step 3
Sorting the rows by moving upward
rows having a 1 in the first column
( Row-sorted machine-part matrix )

48. Appendix (Cell Grouping Method)
Step 4
( Formation of two cells )
The machine can be grouped
into 2 cells
Unfortunately, it is not always
the case that cells can be formed
without conflicts existing
( Formation with conflicts existing )

49. Appendix (Node Method-Floyd Algorythm)
M# Node
M1 V58
M2 V89
M3 V83
M4 V73
M5 V80
M6 V84
M7 V91
M8 V85
M9 V86
M10 V24
M11 V25
M12 V38
M13 V37
M14 V63
M15 V18
M16 V17
M17 V42
M18 V43
M19 V60
M20 V15
M21 V14
M22 V52
M23 V51
M24 V98
M25 V11
M26 V48
M27 V49
M28 V53
M29 V56
M30 V57
M31 V21
M32 V90
M33 V76
Place Node
NJ1 V71
V99
NJ2 V67
NJ3 V68
NJ4 V74
NJ5 V10
V94
NJ6 V8
NJ7 V2
NJ8 V6
NJ9 V77
NJ10 V30
NJ11 V29
NJ12 V95
Board V65
Lift1 V7
Lift2 V33
Die1 V5
Die2 V75
Die3 V96
Dryer V62
Store V70

50. Appendix (Node Method-Floyd Algorythm)
The Floyd–Warshall algorithm compares all possible
paths through the graph between each pair of
vertices.
Therefore, we can define shortestPath(i, j, k) in terms
of the following recursive formula:

51. Appendix (Node Method-Floyd Algorythm)
Start End Total Dis P a t h
V2 V5 810 V2 V3 V4 V5
V2 V6 972 V2 V3 V4 V5 V6
V2 V7 1,336 V2 V3 V4 V5 V6 V7
V2 V9 1,453 V2 V3 V4 V5 V6 V7 V8 V9
V2 V10 1,124 V2 V3 V4 V5 V6 V7 V10
V2 V13 1,148 V2 V3 V4 V15 V14 V13
V2 V14 1,101 V2 V3 V4 V15 V14
V2 V16 846 V2 V3 V97 V18 V17 V16
V2 V17 835 V2 V3 V97 V18 V17
V2 V24 1,335 V2 V3 V4 V15 V14 V13 V12 V24
V2 V25 1,535 V2 V3 V97 V18 V19 V20 V21 V22 V23 V25
V2 V27 1,409 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31 V30 V29 V28 V27
V2 V28 1,395 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31 V30 V29 V28
V2 V31 1,203 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31
V2 V32 1,118 V2 V3 V97 V18 V19 V20 V34 V33 V32
V2 V35 1,693 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31 V30 V36 V35
V2 V38 1,658 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31 V30 V36 V37 V38
V2 V39 1,690 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31 V30 V36 V37 V38 V39
V2 V41 1,861 V2 V3 V97 V18 V19 V20 V34 V33 V32 V31 V30 V36 V37 V38 V39 V40 V41
V2 V42 1,450 V2 V3 V97 V18 V19 V20 V34 V33 V44 V43 V42
V2 V45 1,378 V2 V3 V97 V18 V19 V20 V34 V33 V44 V45
V2 V46 1,389 V2 V3 V97 V18 V19 V20 V34 V33 V44 V45 V46
V2 V48 980 V2 V3 V97 V18 V19 V48
V2 V49 994 V2 V3 V97 V18 V19 V48 V49
V2 V55 758 V2 V1 V58 V55
V2 V56 809 V2 V1 V58 V55 V56
V2 V57 768 V2 V1 V58 V55 V57
V2 V59 1,008 V2 V1 V58 V55 V54 V59
V2 V60 1,218 V2 V1 V58 V55 V54 V59 V60
V2 V63 990 V2 V1 V58 V55 V54 V53 V63
V2 V64 1,444 V2 V1 V58 V55 V54 V59 V60 V61 V64
V2 V65 1,411 V2 V1 V58 V55 V54 V59 V60 V61 V64 V65
V2 V66 1,431 V2 V1 V58 V55 V54 V59 V60 V61 V64 V65 V66
V2 V67 1,559 V2 V1 V58 V55 V54 V53 V63 V62 V69 V68 V67
V2 V69 1,215 V2 V1 V58 V55 V54 V53 V63 V62 V69
V2 V71 1,639 V2 V1 V58 V55 V54 V53 V63 V62 V69 V68 V70 V71
V2 V72 1,769 V2 V1 V58 V55 V54 V53 V63 V62 V69 V68 V70 V71 V72
V2 V74 1,996 V2 V1 V58 V55 V54 V53 V63 V62 V69 V68 V70 V71 V72 V73 V74
V2 V75 2,299 V2 V1 V58 V55 V54 V53 V63 V62 V69 V68 V70 V71 V72 V73 V74 V75
V2 V76 1,664 V2 V1 V58 V55 V54 V53 V63 V62 V69 V68 V70 V76
V2 V82 1,753 V2 V1 V58 V55 V54 V53 V52 V83 V79 V81 V82
V2 V83 1,346 V2 V1 V58 V55 V54 V53 V52 V83
V2 V84 1,346 V2 V1 V58 V55 V54 V53 V52 V83 V84
V2 V85 1,599 V2 V3 V97 V18 V19 V20 V34 V33 V44 V43 V86 V85
V2 V88 1,675 V2 V3 V97 V18 V19 V20 V34 V33 V44 V43 V86 V87 V88

52. Appendix (Appointment of Workers)
( The Current System) ( Alternative 1 – From-to Chart Method)

53. Appendix (Appointment of Workers)
( Alternative 2 – Cell Grouping Method) ( Alternative 3 – Pareto Rule Method)

54. Appendix ( Data Fitting )

55. Appendix ( Pictures)
( A Material Hand Cart) ( A Fixed Dryer Hopper)

56. Appendix ( Pictures)
( A Material Warehouse) ( An Oven Dryer)