improving productivity of manufacturing division using lean concepts

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LeanThi
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journalhomepage: www.thi
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ean.com/i
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IMPROVING PRODUCTIVITY OF MANUFACTURING DIVISION USING LEAN
CONCEPTS AND DEVELOPMENT OF MATERIAL GRAVITY FEEDER
–A CASE STUDY
K.Hemanand
Department of Mechanical
Engineering, PSG College of
Technology,Coimbatore –
641 004, India.
D.Amuthuselvan
Department of Mechanical
Engineering, PSG College of
Technology,Coimbatore –
641 004, India.
S.Chidambara Raja*
G.Sundararaja
Department of Mechanical
Engineering, PSG College of
Technology,Coimbatore –
641 004, India.
[email protected]
Department of Mechanical
Engineering, PSG College of
Technology,Coimbatore –
641 004, India.
ABSTRACT
The automotive industry has been experiencing a competitive
environment and striving hard to find methods to reduce
manufacturing cost, waste and improve quality. Lean
manufacturing concepts are used by the industries to reduce work
in progress inventories and also to reduce the waste for competing
in the global market. The ultimate goal is to speed up the process
there by increasing productivity through a proper utilization of
man and machine. In a manufacturing industry, the layout and
material flow in the shop floor decides its productivity. Material
handling system also plays a key role in influencing productivity,
throughput time and cost of the product.
This research work has been carried out as a case study in an
automotive industry with the objective of waste reduction. Efforts
are made to reduce the motion waste in the shop floor. The
problems in the current layout are identified and analyzed through
simulation. Then the layout is modified, simulated and the results
are compared with the current layout. The results revealed an
improvement of 11.95% in productivity. A new material handling
system has been designed and developed to reduce the motion
wastes and unwanted transportation.
KEYWORDS
Layout,
Simulation,
Material,
Time,
Transportation
ARTICLE INFO
Received 30 July 2012
Accepted 07 September 2012
Available online 01 October 2012
1. Introduction
Lean manufacturing is “A systematic approach for identifying and eliminating waste
through continuous improvement by flowing the product at the pull of customer in pursuit of
perfection”.
Lean manufacturing concepts are mostly applied in industries where more repetitive
human resources are used. In these industries productivity is highly influenced by the efficiency
working people with tools or operating equipments. To eliminate waste, it is important to
understand exactly what it is and where it exists. The processes add either value or waste to the
production of goods. The seven manufacturing wastes originated in Japan, where waste knows
________________________________
as
“muda" as Author
demonstrated by Rotaru (2008).
* Corresponding
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as “muda" as demonstrated by Rotaru (2008).
The concept of Lean manufacturing first came to be more widely known with the book ‘The Machine
That Changed the World’ published by Womack et al.(1990) and later through the book ‘Lean Thinking’.
The Key points of emphasis in Lean appear to be reducing process variability, reducing system cycle times,
and above all, eliminating wastes in the manufacturing cycle as stated by Womack and Jones (1986).
Paul and Rabindra (2006) used subjective assessment through questionnaire, direct observation
method, and archival data to improve productivity, quality, increasing revenue and reducing rejection cost
of the Manual Component
Insertion (MCI) lines in a printed circuit assembly (PCA) factory. Live experiments were conducted
on production lines. The drawback of this work is that an experimental design could not be performed to
find the best insertion sequence and component bin arrangements as there was a hindrance in
conducting experiments in real-life line, i.e. the study itself might reduce line output and affect quality.
Brown and Mitchell (1988) did an investigation into operators, engineers, and managers of PCA
factories to determine the work environment parameters that inhibited their performance and they
recommended opportunities to improve productivity & quality.
Lim and Hoffmann (1997) found that improved layout of the workplace increased productivity of the
workers, through more economical use of hand movements by conducting an experiment on hacksaws
assembly.
Christopher (1998) stated that the success in any competitive context depends on having either a cost
advantage or a value advantage, or, ideally, both.
Imad Alsyouf (2007) illustrated how an effective maintenance policy could influence the productivity
and profitability of a manufacturing process and showed how changes in the productivity affect profit,
separately from the effects of changes in the uncontrollable factors, i.e. price recovery
Browning and Heath (2009) developed a revised framework that reconceptualises the effect of lean
on production costs and used it to develop eleven propositions to direct further research and illuminated
how operations managers might control key variables to draw greater benefits from lean implementation.
White et al. (1999) found that plant size had a significant effect on the implementation of lean
practices. This shows that, regardless of establishing what lean is, it remains important to establish how
best to become lean in varied contexts.
Shah and Ward (2003) empirically validated four “bundles” of inter-related and internally consistent
practices; these are just-in-time (JIT), total quality management (TQM), total preventive maintenance
(TPM), and human resource management and investigated their effects on operational performance.
Flynn et al.(1995) and McKone et al.(2001) have explored the implementation and performance
relationship with two aspects of lean.
Crute et al.(2003) discussed the key drivers for Lean in aerospace and did a Lean implementation
case comparison which examines how difficulties that arise may have more to do with individual plant
context and management than with sector specific factors.
Womack et al.(1990) developed from the massively successful Toyota Production System, focusing on
the removal of all forms of waste from a system.
Krafcik, (1998) describes the Japanese-style manufacturing process pioneered by Toyota, which uses
a range of techniques including just-in-time inventory systems, continuous improvement, and quality
circles.
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In the cited literatures, Researchers revealed the importance of lean concepts in the competitive
industries especially for improving the productivity, quality of products, profitability, and for reducing
lean wastes and inventories.
The current research aims at improving productivity, increasing revenue of the plant by the reduction
of motion wastes. In addition, the design and development of the gravity feeder for the material handling
have been done as a value addition to this research work. The methodology of the current case study is
presented in the block diagram and depicted in Figure 1.The collection of data is done by direct
observation method. The time study is conducted using stop watch. From the collected data, the
problems in the current layout are identified and rectified by redesigning the layout in two aspects. One
aspect is reducing the material handling by the design and development of new material gravity feeder
which is designed in solid edge V19 and structural analysis is done in Ansys 12. Another aspect is
conducting the simulation study to reveal the performance of current layout using WITNESS simulating
software. Based on the results, a new layout is proposed and implemented.
Figure 1: Block diagram of methodology followed in the case study
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Abbreviations
Opn - Operation
SPM - Special purpose machine
VMC - Vertical machining centre
HMC - Horizontal machining centre
RM - Raw material
FG - Finished goods
MHS - Material Handling System
M/C -Machine
No. - Number
Nomenclature
M - Bending Moment (N mm)
I - Moment of Inertia (mm4)
σ - Bending stress (N/mm2)
Y - Distance from neutral axis (mm)
2. Case study – Layout of CNC Machine shop
2.1 Current layout
A case study on machining of bearing cap has been chosen to find the working of current layout and
its performance. The Bearing cap for engine is machined using CNC and Special purpose machines. The
surfaces of bearing cap to be machined are marked by arrows in Figure 2.
Figure 2: Bearing cap machining details
The part flow and sequence of the machining processes carried out on the bearing cap from raw
material to final finished goods are shown in Figure 3. The machines used for the sequence of operations
are two Special purpose machines (SPM) and five CNC machines.
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Figure 3: Flow chart for Process sequence
2.2 Time study
Time study is defined as a work measurement technique for recording the times and rates
of working for the elements of a specified job carried out under specified conditions, and for
analyzing the data so as to obtain the time necessary for carrying out the job at a defined level
of performance [6]. A time study has been carried out for all operations on the bearing cap in
the layout by direct observation method and the observed data is listed in Table 1.
Table 1 Details of Time study
Opn.
M/C type
No.
No. of
operators
No. of
Components
10
Man working
Man idle
M/C working
M/C idle
Cycle time
Cycle time per
time
time
time
time
İn seconds
Component
in seconds
İn seconds
İn seconds
İin seconds
İn seconds
SPM
1
1
24
26
50
0
50
50
63
20
SPM
1
1
42
21
32
31
63
30-A
VMC
1
2
95
0
95
0
95
30-B
VMC
1
2
53
70
82
41
123
62
40-A
VMC
1
2
63
15
25
53
78
39
40-B
VMC
1
4
164
75
166
136
302
76
50
HMC
1
1
64
0
64
0
64
64
60
Deburring
2
1
60
0
0
0
60
60
70
Inspection
2
1
40
0
0
0
40
40
80
Washing &
2
1
10
4
4
10
14
14
Packing
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2.3 Takt time calculation
Takt time is the average time allowed to produce unit production to meet customer
demand and the process time should be less than or equal to the takt time. Takt time is
calculated based on machine available time and the required number of units. The procedure
followed to determine takt time for the current production of bearing cap is as follows:
Total available time
Customer Demand / day
Available Working time/shift
(Excluding lunch and tea break)
Available time/day
Takt Time
= 3 Shifts / day /25 working days in a month
= 1167 pieces
= 420 minutes=25200 seconds.
= 25200 x 3=75600 seconds.
= Total available time /Customer demand
= 64.78 seconds/piece ≈ 65 seconds/piece
2.4 Cycle time calculation
From the time study on current layout (Table 1), it is identified that the operations 30A
and 30B are identical and so the cycle time of one component is found to be 55 seconds by
averaging the cycle times of these two machines. Similarly, operations 40A and 40B are
identical and by taking the average, one components’ cycle time is found to be 58 seconds.
For all the operations, cycle time for a single component is estimated and listed in Table 2.
Also, the same is depicted in the bar chart as shown in Figure 4.
Table 2 Processing time calculation
Opn
No.
10
20
30
40
50
60
70
80
Process description
Top and bottom face milling
Crank ,nut & joint face roughing
Nut face milling, drilling and processing dowel
Crank boring, Notch Milling
Joint face milling, Register width finishing
Deburring
Inspection
Washing and Packing
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Cycle time
in seconds
50
63
55
58
64
60
40
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Figure 4: Bar chart depicts the takt time for one day basis
2.5 Problems Identified in the current layout
The major issues faced in the current layout are explained as follows and the current
layout is depicted in Figure 5.
Figure 5: Current Layout
2.5.1 Idle time of the operator
Idle time of the operator is found from the time study and total idle time of all operators for three
shifts in one day is found and tabulated in Table 3.
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Table 3 Idle time of the operators for three shifts in one day
Sl.No
1
2
3
Man idle time
Opn No. for one cycle Outputs/day
in Seconds
20
21
1200
3070
614
B
4075
250
B
Idle time for 3 Idle time of
shifts in one operator per
day in seconds day inhours
25200
7
43024
11.95
18775
5.22
Total
24.17
This idle time can be utilized in a better way by operating two machines simultaneously.
2.5.2 Waste in transportation by manual operation
In this layout material handling is done using wooden pallets which is transferred by trolley from one
station to another station. It consumes considerable time and results in increased manufacturing lead
time. The materials are moved from one station to another by operator causing motion waste and
transportation waste which is about 68.9 m for every batch of components as given in Table 4.
Table 4 Distance travelled by operator
Sl. No.
Stations
1
2
3
4
5
6
7
8
9
Total
RM- opn.10
opn.10-20
opn.20-30
opn.30-40
opn.40-50
opn.50-60
opn.60-70
opn.70-80
opn.80-FG
Distance travelled without MHS in
meters
1.53
3.66
12.2
13.7
10.7
18.3
4.88
0.914
3.05
68.9
The operator movement in the current layout is depicted in Figure 6. This has to be reduced with
suitable material handling device.
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Figure 6: Operator and material movement in Current layout
3. Proposed layout
Owing to the problems existing in the current layout, a new layout is proposed based on the study
and analysis of the current scenario.
The features of the new layout are listed as follows
1. All machines are connected with a new gravity feeder for carrying material from one station to
another which reduces transportation waste by the amount of 47.85 meters as shown in Table 5 and
feeder is shown in the Figure 7 as number 1.The transportation in the proposed layout is pictorially
depicted in Figure 8.
Table 5 Operator motion distance comparison
Current layout
Sl. No.
Stations
without MHS in
meters
1
RM- opn.10
1.53
2
opn.10-20
3.66
3
opn.20-30
12.2
4
opn.30-40
13.7
5
opn.40-50
10.7
6
opn.50-60
18.3
7
opn.60-70
4.88
8
opn.70-80
0.91
9
opn.80-FG
3.05
Total (meter)
68.93
Proposed layout
with MHS in meters
1.53
0
0
0
0
16
0
0.5
3.05
21.08
Difference in
distance travelled
in meters
47.85
2. Two machines are interchanged because it is identified that the idle time of the operator is more
as mentioned in the Table 3. Operation 30B and 40B having high idle times 70s and 75s respectively. In
order to reduce the idle time of operators, the machines C and D are interchanged and the orientation of
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C, E and F are altered as shown in the Figure 7 as number 2. In this new arrangement, Machines B and D
are operated by a single operator simultaneously. Similarly, machines E and F are operated by a single
operator simultaneously. This helps the operator to run two machines simultaneously by utilizing the idle
time.
3. A new window is included in the wall between deburring and inspection area to transfer the
material directly which reduces transportation and motion wastes. It is shown in the Figure 7 as number
3.
Figure 7: Proposed Layout
Figure 8: Material movements in the Proposed Layout
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4. Simulation study
The imitation of the operation of a real-world process or system over time is called simulation.
Simulation involves the generation of an artificial history of the system and the observation of that
artificial history to draw inferences concerning the operational characteristics of the real system that is
represented. The simulation is an indispensable problem-solving methodology for the solution of many
real-world problems. It is used to describe and analyze the behaviour of a system, ask what-if questions
about the real system, and aid in the design of real systems as explained by Adams et al.(1999), Jain and
Leong (2005). A simulation study is carried out using WITNESS as simulation software. Both current and
proposed systems are modelled and simulated in order to find out the optimum layout strategy.
4.1
Current layout simulation
A simulation run for 189000 seconds (one month machine available time) is done for the current
layout. The snap shot of the current layout arrangement with the operators and machines are shown in
Figure 9.
Figure 9: Simulation of Current layout
Data regarding number of activities required, uptime details of the machine, the number of operator
and their working time are given as input and the logic is based on the operation sequence and number
of workers available. The simulated results are shown in Table 6
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Opn.
No
Table 6 Simulation of current layout
Current layout simulation
Machine
Labour
Process
10
20
Top and bottom milling
Crank ,nut and joint face roughing
Nut face milling, drilling and processing
30-A
dowel
Nut face milling, drilling and processing
30-B
dowel
40-A
Crank boring, Notch Milling
40-B
Crank boring, Notch Milling
Joint face milling, Register width
50
finishing
60
Deburring
70
Inspection
80
Washing and Packing
Total Efficiency
4.2
%idle
%busy
%setup
%busy
%idle
0
52.54
67.19
100
31.81
32.80
0
15.64
0
100
15.64
32.81
0
84.36
67.19
66.48
21.47
12.03
12.03
87.96
46.13
45.06
0.70
45.56
44.81
99.29
8.307
10.11
0
8.307
10.11
99.29
91.69
89.88
0.70
0.82
33.9
60.34
37.32
99.18
66.1
23.14
56.42
0
0
16.52
6.26
99.18
66.1
16.52
46
0.82
33.9
83.48
54
Proposed layout simulation
In the proposed layout, a simulation run for 189000 seconds is done. The snap shot of the proposed
layout arrangement with the operators and machines are shown in Figure 10.
Figure 10: Simulation of proposed layout
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The simulated results are shown in Table 7.
Table 7 Simulation of proposed layout
PROPOSED LAYOUT SIMUALTION
Opn. No
PROCESS
Machine
Labour
%idle
%busy
%setup
%busy
%idle
10
Top and bottom milling
0
100
0
100
0
20
Crank ,nut and joint face roughing
52.52
31.83
15.65
33.23
66.77
Nut face milling, drilling and
30-B
66.48
21.47
12.03
processing dowel
Nut face milling, drilling
and
30-A
66.76
33.23
0
27.69
72.31
processing dowel
40-A
Crank boring, Notch Milling
43.44
45.27
11.28
21.59
78.40
40-B
Crank boring, Notch Milling
43.99
45.68
10.31
Joint face milling, Register width
50
0.70
99.29
0
99.29
0.70
finishing
60
Deburring
0.82
99.18
0
99.18
0.82
70
Inspection
33.9
66.1
0
66.1
33.9
80
Washing and Packing
60.34
23.14
16.52
16.52
83.48
Total Efficiency
36.9
56.52
6.58
57.95
42.05
From the Tables 6 and 7 the machine utilization is observed to be same in both the current and
proposed layout but the elimination of operators has increased the labour utilization. The performance
measures are Percentage of labour productivity and Percentage of machine utilization. The layout
efficiency values are given in Table 8.
Table 8 Comparison of layout results
Parameters
Machine utilization
%idle
%busy
%setup
Current Layout
37.32
56.42
6.26
Proposed Layout
36.90
56.52
6.58
%busy
46.00
57.95
%idle
54.00
42.05
Labour productivity
Improvements
No Change
Increased by
11.95
Decreased by
11.95
Figure 11 shows the performance of current and proposed layouts. From this result, it is concluded
that there is no change in the machine utilization but the labor productivity is increased by 11.95%.
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Figure 11: Comparison of layout efficiency
5. Design of Gravity operated feeder for Bearing Cap
In this bearing cap layout, a gravity operated feeder has been designed for the material handling of
bearing cap. The main aim of this gravity feeder is to reduce material handling time and transportation in
between work stations.
The feeder is made up of 3 mm steel sheet which has four supports at its ends. The shape of the
feeder to accommodate the bearing cap is shown in Figure 12. This model can carry about 29 parts per
meter in the feeder.
Figure 12: Gravity feeder model
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5.1
Structural analysis of gravity feeder
A gravity feeder is modeled using solid edge v-19 and structurally analyzed using ANSYS 12.0 with
following data, the length of feeder is 1000mm and number of components it carries in one meter is 29.
The bearing cap weight varies from minimum 3kg to maximum of 4.25kg. So the maximum weight
4.25 kg is selected and the weight of 29 components is found to be 1209.08 N
According to the theory of pure bending [14], bending moment equation is expressed as follows
(M/I) = (σ/Y) = (E/R)
(1)
2
Using the equation (1), bending stress is estimated to be 8.063N/mm . The yield strength of steel
C15 with factor of safety 6 is found to be 39.24N/mm2 [13].
The model is completely meshed with solid brick 8 node 45 and it is shown in Figure 13.
Figure 13: Meshed model
5.2
Result and Inference
From the analysis, the maximum deformation is found to be 0.001426mm which is reasonably
negligible and it is displayed in Figure 14.
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Figure 14: ANSYS result
6. Summary and Conclusions
An attempt has been made to improve the productivity and profitability of the industry. The design
and development of the gravity feeder for the material handling have been done to reduce the motion
and transportation wastes. The simulation analysis of current layout is carried out to study the
performance in lean perspective and modifications in the layout have been made. A window opening is
made between the deburring and inspecting operation which saves time by 30 minutes for 100 parts .The
machines are replaced and their orientations are changed for easy transfer of material and for sharing the
idle time of the operators with other machines. The modifications in the layout will reduce two operators
and increase the utilization of the operators by 11.95%. It saves 640 rupees per shift from the operator’s
salary. Hence it saves Rs. 5, 99,040 per year which is a considerable savings in the total revenue. Also the
implementation of gravity feeder in between the workstations reduces the motion waste and monotonous
efforts of the labours which further enhances the labours’ job satisfaction and goodwill of the
organisation.
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