AN EXPERIMENTAL STUDY ON THE AUTOMOTIVE PRODUCTION LINE USING ASSEMBLY LINE BALANCING TECHNIQUES

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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 8, Issue 3, March 2017, pp. 22–33 Article ID: IJMET_08_03_003
Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=3
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication Scopus Indexed
AN EXPERIMENTAL STUDY ON THE
AUTOMOTIVE PRODUCTION LINE USING
ASSEMBLY LINE BALANCING TECHNIQUES
P Saurabh Jha and Mohd Salman Khan
M.Tech Scholar, Department of Mechanical and Automation Engineering, ASET,
Amity University, Noida, UP, India
ABSTRACT
The main aim of an assembly line is to group the different facilities and workers in
an efficient manner in order to obtain effective utilization of man power and machine.
This calls for uniform rate of production as well as decrease in the work in process
inventory. Hence, this paper attempts to achieve these in an assembly line of an
automotive manufacturing unit using three different techniques such as Largest
candidate rule (LCR), Kilbridge and wester column method (KWC) and Rank
positional weighted method (RPW). All the three methods show better efficiency and a
comparison is also drawn amongst the three to determine the best suited technique
pertaining to the current research work.
Key words: Largest candidate rule, Rank positional weight, kilbridge and wester
column method, assembly line balancing.
Cite this Article: P Saurabh Jha and Mohd Salman Khan. An Experimental Study on
the Automotive Production Line Using Assembly Line Balancing Techniques.
International Journal of Mechanical Engineering and Technology, 8(3), 2017, pp. 22–
33.
http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=8&IType=3
1. INTRODUCTION
Assembly line balancing consists of a series of work stations that comprises of work
elements. A set of work element having tasks which have a defined cycle time or operating
time with a set of interrelated activities in a certain order. Each work element possesses a task
time which is a standard time to complete the elemental task. The collective time of all the
workstations is the total work content that determines the total time for the assembly.
Assembly line balancing is mainly done for the effective utilization of machine and to achieve
less congestion within the production system. The three suitable techniques of assembly line
balancing i.e. largest candidate rule, kilbridge and wester column method and rank positional
weighted method are applied here to determine the best results pertaining to the assembly line
which will eventually decrease the idle time and material handling.

2. LITERATURE REVIEW
Assembly planning and line balancing was integrated [1] to incorporate decisions on process
planning. the system methodology was first explained along with the drawing of the product.
The precedence diagram is drawn that gives us visual explanation of the assembly line. A
heuristic procedure for assigning the tasks in the assembly line was performed using kilbridge
and wester column method. The aim was to minimize the balance delay and providing smooth
postural load in-between the workstations [2]. A detailed study [3] was presented regarding
the balancing in a production system. The problems of assembly lines are classified as simple
and general model assembly line balancing problems. Mathematical model, heuristic
procedure and stochastic algorithm are proposed for optimizing the balancing problems.
Largest candidate rule and kilbridge and wester column method were explained in detail using
flow chart. In order to not violate the cycle time and precedence constraints, largest candidate
rule is determined to assign tasks to the workstation and maintain smooth and continuous flow
[4]. A comparison was done between LCR and KWC to a better line efficiency amongst the
two on a refrigeration plant. These methods showed huge improvements when compared with
the existing line that helped distribute the task evenly so that the idle time of both the
machines and men are decreased [5]. A manual assembly line balancing was done by all the
three methods of LCR, KWC and RPW and was found that RPW provided the best results
with a very high line efficiency as well as labour efficiency [6]. Another researcher also
computed the assembly line balancing using all the three methods and tabulated the results
pertaining to idle time, line efficiency and smoothness index [7]. Coming to the practical
scenario, when applying these methods, they show drastic improvement. Researchers [8] have
applied Largest candidate rule in the garment industry and the assembly line efficiency have
increased up to 26%. And also, the productivity increased. Thus, this paves way for its
application in a real time huge manufacturing set ups. LCR can also be studied on
computational experiments that will help to make the software more user friendly and
interactive [9]. Different balancing methods were evaluated with the help of operation time.
Remaining time is computed at each workstation and then analyzed using rank positional
weight method (RPW) [11]. Researchers also found that RPW is a method that minimizes the
workstations thereby minimizing the balance delay and ultimately improving the line
efficiency. slack time is reduced task is completed in a shorter time [12]. A multi-product
assembly line balancing problem [13] was investigated using the method of RPW. The
methodology provides a clear scenario of the work done and an expert system is proposed.
The bottlenecks of an engine assembly were decreased by RPW method thereby increasing
the production by25% [14]. Other researches [15] have used other methods such as genetic
algorithm to solve the assembly line balancing problems.
3. CASE STUDY
The Autoline industry manufactures sheet metal components, sub-welding assemblies and
assemblies for the automobile industry. The present research work focusses on the assembly
line balancing of the high deck body.

An Experimental Study on the Automotive Production Line Using Assembly Line
Balancing Techniques
Figure 1 Assembly line plant Layout
FL-2
FL-3
FL-4
FL-5
FL-6
ML-1
ML-2
ML-3
ML-4
ML-5
HD-4
HD-3
HD-2
HD-1
ML-6
ML-7
ML-8
ML-9
Side
Panel-LH
HD-7
HD-6
HD-5
IL-1
Front Panel
geo-2
Front Panel
S.P.M-1
Front Panel
S.P.M-2
Inversion
fixture
Side
Panel-RH
Side
Panel
S.P.M-1
Side Panel
S.P.M-2
CO2
Fixture
Inversion
fixture
Input as metal
stamped sheet
Input as metal
stamped sheet
Front
Panel
FL: FLOOR LINE FL-1
ML: MAIN LINE
LHRH
High Deck Finishing
HIGH DECK ACE BODY
ASSEMBLY LINE PLANT LAYOUT
Loading
Point
Dispatched
Inspection

Data recorded in observing the ace high deck body assembly line.
 Total maximum production time = 12 hours/day = 720 min
 Breaks and maintenance/cleaning time = 60 + 40 min = 100 min
 Production time = 620 min.
 Average no. of workers = 70-72/day.
 Targeted body = 50/day.
 Idle time= 40 min /day
The assembly line consists of five stages that consists of floor line, main line, finishing
line, front panel and side panel.
Table 1 observed time for different workstation
Figure 2 Precedence diagram
Workstation Observed Time
Floor line 16.19
Front Panel 8.17
Side Panel 13.02
Main line 28.29
Finishing line 24.41
Total 90.08 min
2 3 4 5 6
7
8
9
10
11
12
13
14 15 16 17
18
19 20
21
22
2324252627282930313233

Table 2 Line data
Components Elements Cycle time (min) Precedence
Floor line-1 1 2.46 ---
Floor line-2 2 2.58 1
Front Panel 7 1.37 ---
Front panel geo 8 3.08 7
Spot permanent maching-1 9 2.50 8
Inversion fixture-1 11 0.11 10
Side Panel LH 12 2.51 ---
Side Panel RH 13 2.24 ---
Spot permanent maching-1 14 1.15 12,13
Spot permanent fixture 16 2.36 15
Inversion fixture-2 17 3.26 16
Main line-1 18 2.39 6,11
Main line-2 19 4.13 17,18
Main line-3 20 3.18 19
Main line-4 21 4 20
Main line-5 22 3.47 21
Main line-6 23 3.32 22
Main line-7 24 3.1 23
Main line-8 25 2.37 24
Main line-9 26 2.33 25
High deck-1 27 2.39 26
High deck-2 28 2.30 27
High deck-3 29 2.38 28
High deck-4 30 2.10 29
High deck-5 31 3.24 30
High deck-6 32 2.53 31
High deck-7 33 9.47 32
4. RESEARCH METHODOLOGY
The methodologies used in this research work consists of assembly balancing techniques such
as Largest candidate rule, rank positional weighted method and Kilbridge and wester column
method. The parameters of assembly line balancing are as follows:
 Cycle time = (Total available production time)/ Total No. of units to be produced
 Min no. of workstations required (theoretical) = Total Work Content/Cycle time
 Balance delay = [(No of workstations*Cycle Time – Total Work Content)/ (No of
workstations*Cycle Time)] x 100
 Line Efficiency = (100 – Balance Delay) %
 Line Smoothness Index 2
m ax
1
( )
k
j
j
SI S S

 

4.1. Largest Candidate Rule
The steps involved are: -
 List all the elements in the decreasing order of their elemental task time
 To assign an element in a work station to start from the beginning of list moving downward
searching first feasible element which can be placed in a workstation? A feasible element is
one that satisfy the precedence requirement and when that element is placed in a workstation,
the total time of work station should not exceed the cycle time
 Strike off the element which is assigned to a work station so that it cannot be considered
again.
 Continuing in the similar manner until all the elements are assigned to different workstation.
Table 3 Sorted data for LCR
Elements Cycle time (min) Precedence
33 9.47 32
19 4.13 17,18
21 4 20
22 3.47 21
23 3.32 22
17 3.26 16
31 3.24 30
5 3.2 4
20 3.18 19
3 3.15 2
24 3.1 23
8 3.08 7
2 2.58 1
32 2.53 31
12 2.51 ---
9 2.5 8
1 2.46 ---
18 2.39 6,11
27 2.39 26
29 2.38 28
4 2.37 3
25 2.37 24
16 2.36 15
26 2.33 25
28 2.3 27
13 2.24 ---
30 2.1 29
6 2.03 5
7 1.37 ---
14 1.15 12,13
10 1.11 9
15 1.1 14
11 0.11 10

Table 4 Largest candidate rule method
 Balance delay = (6 x 18.018) – 90.28 x 100 = 16.49 %
6 x 18.018
 Line efficiency = 100 – 16.49
= 83.51 %
 Smoothness index =√ [(17.27-16.27)2
+(17.27-15.69)2
+(17.27-15.32)2
+(17.27-16.26)2
+(17.27-
17.27)2
+(17.27-9.47)2
] = 8.31
4.2. Kilbridge and Wester Column Method
The elements in this method are selected for assignment to stations on the basis of their
position in the precedence diagram. Therefore, all the elements were arranged in the form of
columns in the diagram which in turn is organized into a list according to their column, with
the elements in the first column is taken first. The highest value of each column is placed first.
Workstations Elements Cycle Time (min) Total Work Content Ideal Time
I
12
1
2
3
4
5
2.51
2.46
2.58
3.15
2.37
3.2
16.27 1.74
II
13
6
7
8
9
14
10
15
11
2.24
2.03
1.37
3.08
2.5
1.15
1.11
1.1
1.11
15.69 2.32
III
18
16
17
19
20
2.39
2.36
3.26
4.13
3.18
15.32 2.69
IV
21
22
23
24
25
4
3.47
3.32
3.1
2.37
16..26 1.75
V
26
27
28
29
30
31
32
2.33
2.39
2.3
2.38
2.1
3.24
2.53
17.27 0.74
VI 33 9.47 9.47 8.54
Total 90.28 min 17.78 min

Subsequently, repeating the previous steps for as many additional stations as possible until all
elements have been assigned as shown in the precedence diagram [7].
Table 5 KWC for Assembly line
 Balance delay = (6 x 18.018) – 89.28 x 100 = 17.41 %
6x 18.018
= 82.59%
 Smoothness index =√ [(17.7-17.66)2
+ (17.7-16.52)2
+(17.7-17.7)2
+(17.7-16.2)2
+(17.7-14.7)
2
+(17.7-6.5)2
]
= 11.61
Elements Cycle
time(min)
Column Precedence Workstation Total work
content
Ideal
time
1 2.46 A ---
33 9.47 B 32
2 2.58 B 1
3 3.15 C 2 I 17.66 0.35
32 2.53 C 31
31 3.24 D 30
4 2.37 D 3
5 3.20 E 4
30 2.10 E 29
8 3.08 F 7 II 16.52 1.49
12 2.51 F ---
9 2.50 F 8
29 2.38 F 28
13 2.24 F ---
6 2.03 F 5
7 1.37 F ---
11 1.11 F 10
12 0.11 F ---
28 2.30 G 27
14 1.15 G 12,13 III 17.7 0.318
27 2.39 H 26
15 1.10 H 14
16 2.36 I 15
26 2.33 I 25
17 3.26 J 16
18 2.39 J 6,11
25 2.37 J 24 IV 16.2 1.81
19 4.13 K 17,18
24 3.1 K 23
21 4 L 20
22 3.47 L 21 V 14.7 3.31
23 3.32 L 22
20 3.18 L 19 IV 6.5 11.51
Total 89.28 min 18.78
min

Figure 3 Works elements arranged by KWM
4.3. Rank Position Wighted Method
The elements are arranged in a decreasing order of their positional weight. The positional
weight of an element corresponds to the time of the longest path from the beginning of the
element to the reminder of the network. It can be said as a combination of largest candidate
rule and kilbridge and western method [10].
Table 6 Rank Positional weight for assembly line
Components Elements Cycle time
(min)
Precedence Positional
Weight
Floor line-1 1 2.46 --- 72.62
Floor line-2 2 2.58 1 70.16
Floor line-3 3 3.15 2 67.58
Floor line-4 4 2.37 3 64.43
Floor line-5 5 3.2 4 62.06
Floor line-6 6 2.03 5 58.86
Front Panel 7 1.37 --- 65
Front panel geo 8 3.08 7 63.63
Spot permanent maching-1 9 2.5 8 60.37
Inversion fixture-1 11 0.11 10 56.94
Side Panel LH 12 2.51 --- 64.82
Side Panel RH 13 2.24 --- 64.55
Spot permanent maching-1 14 1.15 12,13 62.31
Spot permanent fixture 16 2.36 15 60.06

Inversion fixture-2 17 3.26 16 57.7
Main line-1 18 2.39 6,11 56.83
Main line-2 19 4.13 17,18 54.44
Main line-3 20 3.18 19 46.18
Main line-4 21 4 20 43
Main line-5 22 3.47 21 39
Main line-6 23 3.32 22 35.53
Main line-7 24 3.1 23 32.11
Main line-8 25 2.37 24 29.11
Main line-9 26 2.33 25 26.74
High deck-1 27 2.39 26 24.41
High deck-2 28 2.3 27 22.02
High deck-3 29 2.38 28 19.72
High deck-4 30 2.1 29 17.34
High deck-5 31 3.24 30 15.24
High deck-6 32 2.53 31 12
High deck-7 33 9.47 32 9.47
Table 7 Line Balancing Results from RPW
Workstation Elements Positional Weight Cycle time (min) Total work content Ideal time
I
1
2
3
7
12
13
4
72.62
70.06
67.58
65
64.82
64.55
64.43
2.46
2.58
3.15
1.37
2.51
2.24
2.37
16.68 1.33
II
8
14
5
15
9
16
6
10
63.63
62.31
62.06
61.16
60.37
60.06
58.86
58.05
3.08
1.15
3.2
1.1
2.5
2.36
2.03
1.11
16.53 1.48
III
17
11
18
19
20
21
57.7
56.94
56.83
54.44
46.18
43
3.26
0.11
2.39
4.13
3.18
4
17.07 0.94
IV
22
23
24
25
26
27
39
35.53
32.11
29.11
26.74
24.14
3.47
3.32
3.1
2.37
2.33
2.39
16.98 1.03
V
29
30
31
32
19.72
17034
15.24
12
2.38
2.1
3.24
2.53
12.55 5.46
VI 33 9.47 9.47 9.47 8.54
Total 89.28 min min

 Balance delay = (6 x 18.018) – 89.28 x 100 = 17.41 %
6 x 18.018
= 82.59%
 Smoothness index=√ [(17.07-16.68)2
+ (17.07-16.53)2
+(17.07-17.07)2
+(17.07-16.98)
2
+(17.07-12.55)2
+(17.07-9.47)2
]
= 8.8
5. CONCLUSION
The graph shows the comparison of various parameters of the three assembly line balancing
techniques. It can be seen that the smoothness index of largest candidate rule and Rank
positional weighted method are less than kilbridge and wester column method. This means
that the smoothness of the production flow will not be good according to KWC method. LCR
shows the best line efficiency when compared to RPW and KWC. Also, LCR has the least
idle time of all. Thus, while looking at the overall performance, Largest Candidate rule of
assembly line balancing method is the best technique that could be followed for this case
study.
Figure 4 Comparison of parameters for all the techniques
REFERENCES
[1] Abdulhasan, B. B. Integrating Assembly Planning and Line Balancing Using Precedence
Diagram. Eng. & Tech. Journal, 27(5), 2009, pp.1017-1025.
[2] Jaturanonda, C., Nanthavanij, S., & Das, S. K. Heuristic procedure for the assembly line
balancing problem with postural load smoothness. International Journal of Occupational
Safety and Ergonomics, 19(4), 2013, pp. 531-541.
[3] Lakhoua, H. K., & Kahla, K. B. Impact of the Work Flexibility on
Organization. International Journal of Innovative Research and Development, 5(4), 2013,
pp.343-349.
[4] Kathoke, T. B., Venkatesh, J. V. L., & Waghchore, R. K. Heuristic Approach for
Assembly Line Balancing Problems. International Journal of Advanced Manufacturing
Systems,2(1), 2011, pp.67-71.
0
10
20
30
40
50
60
70
80
90
LCR KWC RPW
Line Efficiency Balance Delay Ideal Time SmoothnessIndex

[5] Verma, S., Gupta, R. D., & Sethi, B. Analysis and evaluation of assembly line balancing
in a refrigeration plant. International Journal of Engineering Research and Industrial
Applications, 3(2), 2010, pp.71-82.
[6] Mohammed, J. Y. A. M. R., & Hamza, A. Selection of Balancing Method for Manual
Assembly Line of Two Stages Gearbox. Global Perspectives on Engineering
Management, 2(2), 2013, pp.70-81.
[7] Pachghare, V., & Dalu, R. Assembly Line Balancing Methods-A Case
Study. International Journal of Science and Research , 3(5), 2014, pp.1901-1905.
[8] Jaganathan, V. P. Line balancing using largest candidate rule algorithm in a garment
industry: a case study. International journal of lean thinking, 5(1), 2014, pp.1-11.
[9] Kathoke, T. B., Ghawade, P. S., Waghchore, R. K., & Paropate, R. V. Computational
Experiments on Assembly Line Balancing Problems Using Largest Candidate Rule.
International Journal of Engineering Science and Innovative Technology, 2(3), 2013,
pp.252-257.
[10] Deshpande, V. A., & Joshi, A. Y. Application of Ranked Positional Weight Method for
Assembly Line Balancing–A Case Study. Proceedings of International Conference on
Advances in Machine Design & Industry Automation, 2007, pp.348-352.
[11] Kayar, M., & Akyalçin, Ö. C. Applying different heuristic assembly line balancing
methods in the apparel industry and their comparison, Fibres & Textiles in Eastern
Europe, 6(108), 2014, pp. 8-19.
[12] Yadav, K. S., & Singh, R. V. Case study on Design and Optimization of Industrial AC
Assembly line, International Journal of Research in Aeronautical and Mechanical
Engineering,2(6), 2014, pp.145-154.
[13] Manoria, A., Mishra, S. K., & Maheshwar, S. Expert System based on RPW Technique to
Evaluating Multi Product Assembly Line Balancing Solution, International Journal of
Computer Applications,40(4), 2012, pp.27-32.
[14] Chavarae K.B., & Mulaa A.M. Application of Ranked Position Weighted (RPW) Method
for Assembly Line Balancing, International Journal for Research in Applied Science &
Engineering Technology,3(4), 2015, pp.254-262.
[15] Chong, K. E., Omar, M. K., & Bakar, N. A. Solving assembly line balancing problem
using genetic algorithm with heuristics-treated initial population. Proceedings of the
World Congress on Engineering,2, 2008.
[16] Anoop Kumar Elia and Dr.D.Choudhary, Modeling of Assembly Line Balancing for
Optimized Number of Stations and Time. International Journal of Mechanical
Engineering and Technology, 4(2), 2013, pp. 152–161.
[17] S.K. Gupta, Dr. V.K. Mahna, Dr. R.V. Singh, Rajender Kumar, Mixed Model Assembly
Line Balancing: Strategic Tool to Improve Line Efficiency in Real World. International
Journal of Computer Engineering & Technology (IJIERD), 3(1), 2012, pp. 58–66.

AN EXPERIMENTAL STUDY ON THE AUTOMOTIVE PRODUCTION LINE USING ASSEMBLY LINE BALANCING TECHNIQUES

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