M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
An Optimal Balancing Of Multiple Assembly Line
For A Batch Production Unit
M. Mohan Prasad
K. Ganesan
R.K.Suresh,
Assistant Professor,
Department of Mechanical Engineering,
P. A. College of Engineering and Technology,
Pollachi - 642 002, Coimbatore - Dt,
Tamil Nadu, India.
[email protected]
Associate Professor,
Department of Mechanical Engineering,
PSG College of Technology,
Peelamedu, Coimbatore - 641 004,
Tamil Nadu, India.
Principal,
Department of Mechanical
Engineering,
Ahalia School of Engineering and
Technology,
Palakkad - 678 557,
Palakkad - Dt, Kerala, India.
ABSTRACT
Higher Productivity in organizations leads to national
prosperity and better standard of living for the whole
community. This has motivated several workers on
productivity improvement at different levels of XXXX India
Pvt Ltd, Chennai. The main objective of this project is to
increase the production by changing the layout of the
assembly line in making of Transmit Mixer. At present 12
machines are being manufactured in a total of 2 shifts per
day. Time study is carried out to identify and avoid the idle
time to increase the production rate to 24 machines per
day. The organization facing the problems like production
time, online inventory, delay and idle time. Here our
objective is to reduce the idle time, identifying the cycle
time and optimal method of production. The COMSOAL
(Computer Method for Sequencing Operations for Assembly
Lines) and RPW (Ranked Positional Weight) algorithms have
been used to get the optimal solution. This algorithm
provides the better solution, thereby reducing unnecessary
movements of the worker within the station. The overall
cycle time got reduced when compared with the existing
cycle time in order to meet the customer demand. Thus we
are proposing this scientific approach to get the optimal
solution for increased rate of production of the company
without affecting the quality and cost.
KEYWORDS
Assembly line balancing;
COMSOAL; RPW
ARTICLE INFO
Received May 2013
Accepted July 2013
Available online December 2013
1. INTRODUCTION
Assembly line balancing (ALB) relates to a finite set of work elements or tasks, each having an
operation processing time and a set of precedence relations, which specify the permissible
orderings of the tasks. One of the problems in organizing mass production is how to group work
tasks to be performed on workstations so as to achieve the desired level of performance.
Line balancing is an attempt to allocate equal amounts of work to the various workstations along
the
line. The fundamental line balancing problem is how to assign a set of tasks to an ordered set
________________________________
* Corresponding Author
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
of workstations, such that the precedence relations are satisfied and some measure of
performance is optimized.
1.1 PROBLEM STATEMENT
The main objective of this project is to increase the production by changing the layout of the
assembly line in making of Transmit Mixer. At present 12 machines are being manufactured
in a total of 2 shifts per day. Time study is carried out to identify and avoid the idle time to
increase the production rate to 24 machines per day. The organization facing the problems
like production time, online inventory, delay and idle time. Here our objective is to reduce the
idle time, identifying the cycle time and optimal method of production.
2. LINE BALANCING
Although the product layout produce a large volume of goods in a relatively short time
once the line is established there are numerous problems that arise in connection with
this type of layout that do not become important in the process layout. One of the complex
problems is the problem of line balancing, which may be considered the problem of
balancing operations or stations in terms of equal times and times required to meet the
desired rate of production. In practical cases perfect balance is achieved in straight line
layouts.
The problem in line balancing is minimizing the idle time on the line for all combinations
of workstations subject to certain restrictions. An important restriction is the production
volume that is to be produced. If the demands of the product change, then there should
be a change in line balancing. Usually an assembly line is used for a variety of products, it
becomes necessary to consider a fixed a fixed number of workstations.
In general, there are two types of line-balancing situations, each of which involves
different considerations. It is sometimes difficult in practical cases to distinguish between
the two categories, but it is useful to consider the line balancing problem as Assembly-line
balancing and Fabrication-line balancing: The distinction refers to the type of operations
taking place on the line to be balance. The tern “assembly line” has gained a certain
popular interpretation as it used with the reference to the automotive industry. The term
“fabrication line”, on the other hand implies a production line made up of operations that
form or change the physical or chemical characteristics of the product involved. Machining
operation would fit into this classification, as would heat - treating operation.
2.1 HEURISTIC METHODS OF LINE BALANCING
In this section, we described several methods for solving line balancing problems. These methods
are heuristic approaches, meaning that they are based on logic and common sense rather than on
a mathematical proof. None of the methods guarantees an optimal solution, but they are likely to
result in good solutions which approach the true optimum.
To get optimal solution we consider two different algorithms namely
 COMSOAL (Computer Method of Sequencing Operation for Assembly Lines)
 RPW(Ranked Positional Weight)
2.2 COMSOAL:
This acronym stands for ‘computer method of sequencing operation for assembly lines’. The
basic methodology of COMSOAL was developed by A.L Arcus, which is based on the biased
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
sampling. A large number of feasible solution can be generated the essential idea behind
COMSOAL is the random generated of a feasible sequence. Such a sequence may be constructed
by assigning a positive probability of selection to each task that will fit in the current time and
then selecting one of the tasks at random. The procedure is repeated until all the tasks have
been assigned.
Generate a random solution satisfying all constraints, storing the number of stations it needs.
Repeat this random generation process, keeping the best solution, and discarding poor ones.
The second stage can be aborted if a partial solution is already worse than a previous (better)
solution.
2.2.1 ALGORITHM
The COMSOAL program proceeds in 6 steps as follows:
 STEP 1: For each task identify those tasks which immediately follow it in precedence
orders.
 STEP 2: Place in LIST A for each task in the assembly, the total number of tasks which
immediately precede it in the precedence diagram.
 STEP 3: From LIST A, create LIST B composed of the tasks which have zero predecessors. If
no tasks remain unassigned to stations, then stop
 STEP 4: From LIST B, create LIST C composed of the tasks whose performance times are no
greater than the available time at the station. If LIST C is empty, open a new station with
the full cycle time available and go through STEP 4 again.
 STEP 5: Randomly select from LIST C a task for assignment to the station.
 STEP 6: Update the time available at the station and LIST B to reflect the time consumed
and the completed predecessors at this stage. If LIST B is empty update LIST A and return
to STEP 3 otherwise return to STEP 4.
2.3 RPW:
It combines the strategies of largest candidate rule and Kilbridge and Wester’s method. It is a
rapid approximate method which has been shown to provide acceptable good solution more
quickly than many alternative methods. It is capable of dealing with both precedence and zoning
constraints.
This is another popular heuristic approach to solving line balancing problems for assembly lines.
The basic idea is to allot tasks to stations based on their priority. The priority is determined by
the total time needed by the task and its successors.
The logic is simple: If we have a large number of tasks from which we can choose to assign to a
station, we are more likely to find a (combination) that will minimize the idle time.
From the above, it follows that if we minimize idle time at each station, we should end up with
the minimum number of stations.
2.3.1 ALGORITHM:
The RPW program proceeds in 7 steps as follows:
 STEP 1: For each task identify those tasks which immediately follow it in precedence
orders.
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)






STEP 2: Place in P (j) for position of tasks.
STEP 3: Create all predecessors composed of the tasks which have zero predecessors.
STEP 4: From all predecessors, Create S (j) all the successors of the tasks.
STEP 5: From successors, Create PW (j) by adding all the times in the Successor tasks.
STEP 6: From PW (j) , Create the rank list by giving the rank in descending order.
STEP 7: From the rank, the stations are assigned in the ascending order of the rank. In each
station specified time will be given. If the work goes beyond the specified time then the
new station will be introduced for the further work and repeat STEP 7 again.
3. SCOPE OF THE PROJECT
Due to implementation of batch production method, productivity depreciation and other
certain problems will arise. So in order to improve our productivity we are going to implement
and analysis continuous production technique by using Line Balancing method.
3.1 INPUT VARIABLES
In order to determine a proper line balancing, assembly or fabrication, the following information
is needed.
 Production Volume
 List of operations and their sequence
 Time required completing each operation as well as the elemental time value
The production volume should be determined by sales or marketing group. Of course the
production line output must satisfy the demand. A fixed production rate is determined with the
production volume and the time period involved. The list of operations and their sequence
should be established prior to considering the line-balancing problem. The time for various
operations, constitute probably the most important piece of information of all in the linebalancing problem.
3.2 REQUIREMENTS
 Material shortage should not occur.
 Availability of the worker should be 100 %.
 The employee should work to his full potential.
 All the required accessories should be within the worker’s reach
3.3 CONSTRAINTS USED IN ALBP
 Task Grouping and Task splitting
 Resource Dependent Task Times
 Incompatible Task Assignments
 Temporary tasks with unknown durations
 Work Zone (line side) related constraints
 Operator related constraints
 Ergonomic constraints
 Reduction of work overload
 Reduction of task dispersion
 Throughput improvement and scrap reduction
 Dynamic line balancing (DLB)
3.4 CYCLE TIME CALCULATION
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
 12 Machines per shift.2 Shift per day (8 Hours per shift).
 Efficiency of the worker is taken as 70%.
 Production time = hours per shift * efficiency of worker
= 8*70%
= 5.6 Hours.
= 336 Minutes.
 Production volume = number of machine per shift.
 Cycle time = production time / production volume
= 336 /12
= 28 Minutes.
4. TIME STUDY FOR CHASSIS ASSEMBLY UNIT
In this section, they are assembling the basic supporting materials of the mixer such as, fixing
of Base chasses on the fixture, front and rear pedestal fixing, Engine frame fixing, welding work
(tag welding).
Time study table includes various activities required for finishing the particular Chassis
assembly unit and time required for implementing each activity is given as follows.
Table 1: Time study for Chassis assembly unit
4.1 FLOW DIAGRAM
The flow diagram of above specified time study table and it represents flow of activities to be
done for Chassis assembly unit.
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
Fig. 1: Flow diagram for Chassis assembly unit
4.2 COMSOAL APPROACH
As a solution method, COMSOAL quickly generates multiple feasible solutions and uses the best
solution as its final reported result. To appear on this list, activities must have met all precedence
requirements and there must be enough resources available to assign to the activity. The next
activity to be scheduled is randomly chosen from this availability list and a new availability list is
generated.
They found the COMSOAL approach to give better results for large sample sizes than other,
more traditional, resource allocation heuristics. Whitehouse discusses the application of
COMSOAL to resource allocation and finds the COMSOAL results at each iteration to be fairly
stable even though only random sampling.is used to choose the next activity to be scheduled.
As mentioned previously, since fast, inexpensive computers have become readily available,
COMSOAL should be reexamined as a possible solution methodology for the constrained
resource allocation problem.
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Table 2: COMSOAL Algorithm used in Chasses Assembly Unit
4.2.1 PROPOSSED LAYOUT
The proposed layout of activities which are carried out in each and every station is given
below.
Fig. 2: Proposed Layout diagram
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
4.2.2 IDLE TIME CALCULATION:
Number of Stations: 4
Idle Time:
Station 1
: 05 Minutes
Station 2
: 04 Minutes
Station 3
: 01 Minutes
Station 4
: 12 Minutes
Total : 22 Minutes
% Idle TIME
= 22 Min / 4 Station * 28 Minutes
= 19.6 %
The best solution must have (K) number of stations,
Where,
K = Total time of all tasks / cycle time
= 90/28
= 3.21
=3
Therefore 3 is the Minimum Number of Station
4.3 RPW APPROACH
It combines the strategies of largest candidate rule and Kilbridge and Wester’s method. This is
another popular heuristic approach to solving line balancing problems for assembly lines. The
basic idea is to allot tasks to stations based on their priority. The priority is determined by the total
time needed by the task and its successors.
It combines the strategies of largest candidate rule and Kilbridge and Wester’s method. From the
above, it follows that if we minimize idle time at each station, we should end up with the minimum
number of stations.
Table 3: RPW Algorithm used in Chassis Assembly Unit
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M.Mohan Prasad, K.Ganesan, R.K.Suresh / International Journal of Lean Thinking Volume 4, Issue 2 (December 2013)
The following table shows station assigning by RPW method.
Table 4: Station assigning table
4.3.1 PROPOSED LAYOUT:
The proposed layout of activities which are carried out in each and every station is given below.
Fig. 3: Proposed Layout diagram
4.3.2 IDLE TIME CALCULATION
Total Idle time per cycle equals sum of station idle time
 Idle time For the 4 stations = 5+ 4+ 1+ 12 = 22 min
 % Idle time
= 22min / (4 stations)(28 min/station)
= 19.64%
 The theoretical lower bound is sum of process times divided by the required cycle
time (Tc)
= 80/28
= 2.85
= 3 station
 Therefore 3 is the minimum number of station
5. CONCULSION AND FUTURE WORK:
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Company was assembling 6 machines per shift. Now it has been increased to 12 machines per
shift, this is done by high utilization of the idle time. In future number of machines getting
assembled can be extended to company need. Currently products are getting assembled by
manually; In future it can be achieved by using automatic robots.
Thus the production is increased by changing the assemble line system which is proposed to be a
continuous production system. The time study and cycle time calculations are carried out such
that the production rate is increased to 24 machines per day. In order to overcome the problems
of depreciation in productivity, idle time, improper working schedule and lagging of material
handling equipments due to implementation of batch production system, the continuous
production is proposed to be implemented. The continuous production system is implemented
by using the optimal line balancing method. Algorithm provides the better solution, thereby
reducing idle time, reducing unnecessary movements of worker within the station, and also the
productivity improvement.
REFERENCES:
Journals:
Arcus, A.L., “COMSOAL: A Computer Method of Sequencing Operations for Assembly Lines,”
International Journal of Production Research, Vol. 4, No. 4, 1966
Amen, M. “Heuristic methods for cost-oriented assembly line balancing: A comparison on
solution quality and computing time”. Int. Journal of Production Economics, vol. 69, 255-264,
2001.
Anderson, E. J. and Ferris, M. C., 1993, “Genetic Algorithms for Combinatorial Optimization:
The Assembly Line Balancing Problem”, University of Cambridge, Cambridge, England.
Dr. Robert Graves, “A Review of Line Balancing for Flow Lines”, Perspectives on Material
Handling Practice, 1992
Books:
Martand Telsang, “Industrial Engineering and Production Management”, S. Chand and
Company, 1998.
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Samson Eilon, “Elements of production planning and control”, Universal Book Corpn.1984
K.C.Jain&L.N.Aggarwal, “Production Planning Control and Industrial Management”, Khanna
Publishers, 1990.
S.K. Hajra Choudhury, and A.K. Hajra Choudhury, “Production Management”, Media
Promoters and Publishers Pvt. Ltd., 1998.
N.G. Nair, “Production and Operations Management”, Tata McGraw Hill, 1996.
S.N.Chary, “Theory and Problems in Production & Operations Management”, Tata McGraw
Hill, 1995.
Roberta S. and Bernard W. Taylor III, “Operations Management”, New Jersey: Prentice Hall,
2003.
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