LEAN IMPLEMENTATION IN MANUFACTURING IND (1)
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
INTERNATIONAL JOURNAL OF INDUSTRIAL
ENGINEERING RESEARCH AND DEVELOPMENT (IJIERD)
ISSN 0976 – 6979 (Print)
ISSN 0976 – 6987 (Online)
Volume 3, Issue 1, January- June (2012), pp. 13-20
© IAEME: www.iaeme.com/ijierd.html
Journal Impact Factor (2011): 0.8927 (Calculated by GISI)
www.jifactor.com
IJIERD
©IAEME
LEAN IMPLEMENTATION IN MANUFACTURING INDUSTRY: A
CASE STUDY
S.K. Gupta1, Dr. R.V. Singh2, Dr. V.K. Mahna3, Rajender Kumar4
1
Research Scholar, Department of Mechanical Engineering, FET, Manav Rachna International
University, Faridabad, India-121003
2
Head, Department of Mechanical Engineering, FET, Manav Rachna International University,
Faridabad,
India-121003
3
Professor, Department of Mechanical Engineering, FET, Manav Rachna International
University, Faridabad, India-121003
4
Asst. Prof., Department of Mechanical Engineering, FET, Manav Rachna International
University, Faridabad, India-121003
E-Mail: gupta.sarojkumar@gmail.com, rajender629@yahoo.com
ABSTRACT
In the present business environment, overproduction refers to excess of production over
demand of products being offered to the market. This leads to excessive inventory in
terms of finished and semi finished goods. Excess production is only relative to a given
demand, and insufficient demand is only relative to a given production and thus consider
overproduction and under consumption equivalent. Overproduction is the root cause of
imbalances, in production sections thereby; the men & machines are either unutilized or
being used for over production. The principles of lean manufacturing are very loud in the
subject matter and overproduction is the worst form of waste. In this present case, XYZ
Company manufacturing automotive products of the same type but in wide variety was
chosen for this comprehensive study. This company has problems in-hand regarding
movement of material on shop floor, accumulation of material on shop floor, and waiting
time in assembly line etc. The probable solution for above mentioned problems is to
apply optimization approaches on production system.
Keywords: Overproduction, Lean Manufacturing, Inventory and Waste
1.0 INTRODUCTION
Often, key questions in examining manufacturing processes are: what are the value-added
ratio of these supporting processes to the organization and the current plans of
13
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
manufacturing. The plan of manufacturing may remain internal or extend i.e. outsourced.
Principally the decision in this regard is of strategic nature therefore, the manufacturing
has to be maintained inside the plant, except any change in volumes, may constraint to
push the partial production outside and also the equipments, which have become
redundant may not be replaced.
Waste is an activity that does not add value. Overproduction is the ability to produce far
more products than can possibly be offered to the customer against the actual
requirement. This leads to a struggle for sale of the undesired products and creating a
situation wherein the marketing department need to apply all resources at their command
to recover the invested money. Look around place of work and it can be noticed that there
are excessive raw materials, excessive floor space unnecessarily occupied, excessive
material handling, and accrued profits on downside. They are just the flags that there is a
cause for these to be identified and addressed.
Therefore, symptoms and causes need to be identified and resolved. The normal
symptoms are excessive raw material, extra inventory, unregulated material flow,
excessive need of space for storage etc. This kills the efficiency and profitability of the
organization. "A more liberal and extensive reciprocity in the production and sale of
commodities is necessary, so that the overproduction of the companies can be
satisfactorily disposed off to the market.”
The root causes of over production are unleveled scheduling, unbalanced capacity of each
section, unreliable suppliers, unreliable process, misuse of automation, wide variety
redundant inspection, unreliable tooling etc. Therefore answer is in usage of ‘5S’ and
‘5WHY’ as application of these tools is to help in identifying the problems related to
over-production.
2.0 LITERATURE REVIEW
Successful lean implementation is approached from a strategic perspective and
companies seek to reach certain goals with lean initiatives. As creating a lean workplace
requires changing the corporate culture a robust change management strategy is needed
(Parks, 2002). Such abrupt policy changes require a top-down approach to decision
making (Kobayashi, 1995).
Mader (2005) emphasizes the need for strong top management leadership in the
implementation process. Carefully selected Kaizen events should support the
organization’s strategy and vision.
Only seeing lean as a quick fix, may give some employees the impression that Lean
might not work in certain environments, i.e. in low volume operations. Spear (2004) says
that at Toyota managers act as enablers and in that sense coach co-workers in solving
problems instead of just fixing them.
Womack and Jones (1998) and Moore (2006) have stated that, the organizations of many
types are implementing lean manufacturing, or lean production, practices to respond to
14
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
competitive challenges. They have mentioned that lean initiatives can be taken up in the
fields of automotive sector, aerospace, and consumer goods industries around the world.
Moore has discussed various implementation tools of Lean Manufacturing, which can be
incorporated in the industries.
Wheatley (2005) discussed five business factors for lean application. These factors are
Operational Performance, Competitive advantage in Price and service, Profit
Improvement, Shorter Lead-Times and reduction in prices. On analyzing these factors
Wheatly concluded that Operational Performance can be improved up to 90%,
Competitive advantage in Price and service up to 82%, Profit Improvement up to 80%,
Shorter Lead-Times up to 75% and reduction in prices up to 62%.
3.0 CASE STUDY
On the maiden visit to XYZ Company manufacturing automotive parts, there were many
surprises, which were not affecting the operating management. The people walk day-in
and day-out on the shop floor and are still unaware of the problems which remain hidden
and are a cost to the company. The aisles were full of trolleys loaded with WIP and
further every nook and corner was having no. of trays filled with WIP. Also, many of the
trays didn’t carry the material identification including the quantities lying therein. This
did represent the waste which was generated by the principle of inventory management
like ‘First in last out’ i.e. inventory getting dumped one above the other. This type of
planning attitude must provide for obsolescence and scrap. This further reveals that there
was good amount of overproduction which is again type of waste that is producing more
than the requirement. The principles of 5S have been used to identify, analyze and
evaluate the existing manufacturing system. The fact regarding over production has been
established as per production data: planned v/s actual. A total of 21 models were
identified for overproduction and this is 10% of the existing models. The period under
study is from Jul’2011 to Dec’2011 and model wise-month wise planned v/s actual
production data of these 21 models is as per Table 1 and graphically presented in Figure
1.
Table 1 Production Data: Planned v/s Actual
Model
No.
3220
3247
3289
3316
3601
3711
3728
3900
4315
4321
6124
6132
Jul'11
Plan
Actual
0
1560
150
150
4192
4872
1100
680
0
4050
6124
6286
8820
7554
4522
4160
270
3780
1000
920
0
0
0
0
Aug'11
Plan
Actual
1740
1296
0
0
2000
2769
0
0
200
975
7428
7650
13266
14511
5000
4416
1600
1331
2000
1950
200
144
300
216
Sep'11
Plan
Actual
84
0
0
0
4520
6334
150
0
0
3750
8278
5198
8795
9120
7234
5328
270
420
0
0
56
0
84
60
15
Oct'11
Plan
Actual
84
236
0
0
0
0
650
528
6250
7512
9000
11402
6675
7840
9306
11481
0
0
600
0
56
192
24
0
Nov'11
Plan
Actual
0
0
0
0
0
0
6
0
5800
5600
8598
9740
5680
7416
4325
4848
0
0
0
0
0
0
0
0
Dec’11
Plan
Actual
3050
3360
0
648
1000
1152
0
948
4200
4055
1858
2824
4714
5414
2627
4018
0
552
500
1368
48
192
84
476
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
1000
180
2300
5000
5000
959
3140
500
1830
220
2380
4770
3921
1077
4470
248
2040
200
920
0
0
0
8170
270
2796
0
1055
1798
2220
220
8210
543
8
200
565
0
11114
0
7460
0
0
192
619
0
20147
0
7780
0
8
8
546
12300
16167
0
5080
0
0
192
635
13099
16595
0
8280
0
0
0
1200
0
15500
0
1850
0
2080
0
0
1055
0
21560
0
3206
0
4704
0
0
745
7200
2200
1200
3244
0
0
0
0
857
11668
2789
1093
3636
0
648
44257
52928
45334
52100
48818
58948
66754
77992
45039
58129
32670
45698
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
Planned Production
Actual Production
Ju
l'1
A 1
ug
'1
1
S
ep
t'1
1
O
ct
'1
N 1
ov
'1
D 1
ec
'1
1
(In Numbers)
Month Wise Production Data:
Planned v/s Actual
Production Quantity
6133
6138
6143
6213
6226
6229
6241
6268
6288
Grand
Total
Months
Figure 1 Planned v/s Actual Production
The compiled data in Table 1 has been analyzed and incorporated in Table 2 below. It is
the application 5 Why’s which have led to establishing long setup times, unbalanced
interdepartmental production, staying busy, unbalanced scheduling, larger plans, old
machines and failure of implementation of preventive plans.
The analysis of data in Table 2 reveals that 30% of total production falls under the
category of over production. This results that there is an extra inventory to the tune of
2% of monthly production. In one of the item the over producing for 778 days that is item
not to be produced for two years. This situation is quite alarming. Therefore, the obvious
results are excessive material on shop floor, extra material requirement, additional shop
floor space, blockage in material flow and high utility course. This leads to inefficient
operations and cutting down in profitability. The slogan of staying busy has to be deleted
including improvement in redundant inspection and also reduction in setup times.
16
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
Table 2 Production Data Analysis Summery
Model No.
3220
3247
3289
3316
3601
3711
3728
3900
4315
4321
6124
6132
6133
6138
6143
6213
6226
6229
6241
6268
6288
Grand Total
Plan
4958
150
11712
1906
16450
41286
47950
33014
2140
4100
360
492
3056
588
6276
24500
49981
2159
28944
770
2080
282872
Actual
6452
798
15127
2156
25942
43100
51855
34251
6083
4238
528
752
4626
604
6601
31335
67232
2390
35582
791
5352
345795
Excess Quantity
1494
648
3415
250
9492
1814
3905
1237
3943
138
168
260
1570
16
325
6835
17251
231
6638
21
3272
62923
Monthly average
826
25
1952
318
2742
6881
7992
5502
357
683
60
82
509
98
1046
4083
8330
360
4824
128
347
Days
54
778
52
24
104
8
15
7
332
6
84
95
92
5
9
50
62
19
41
5
283
(In Days)
Overproduction Inventory
Model-Wise Overproduction Inventory
900
800
700
600
500
400
300
200
100
0
1
2 3
4
5
6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 21
Model Serial Number
Figure 2 Inventory Optimization
17
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
Table 3 confirms that, there is no relation between planned production and actual production.
The data depicted in Table 3 is covering the entire range of monthly production of XYZ
company manufacturing automotive parts. There is a wide gap between these two, this may be an
indication of projecting consistently more, which can’t be produced and henceforth the desired
objectives can’t be achieved.
Table 3 Gross average monthly production
Months
Jul'11
Aug'11
Sept'11
Oct'11
Nov'11
Dec'11
Average
Planned Production
222521
250428
266333
248845
186317
176038
225080
Actual Production
151431
156504
152994
209559
149798
150009
161716
300000
Planned
Production
250000
200000
Actual
Production
150000
100000
50000
N
ov
'1
1
D
e
c'
11
A
ve
ra
ge
O
ct
'1
1
A
ug
'1
1
S
ep
t'1
1
0
Ju
l'1
1
(In No.'s)
Production Quantity
Overall Performance: Planned v/s Actual
Months
Figure 3 Gross average monthly productions
It is concluded in Table 4 that the Production Planning and Control Department of said company
is working with no exposure to the technological advancements. It is evident that the production
data doesn’t match with the planned production. In most of the categories, it is underproduction
followed with overproduction and further very small percentage matching with the planned data.
18
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
Table 4 Actual Performance: Planned v/s Actual
Production
Data
Production at
Par
Over
Production
Under
Production
Total
Percentage:
Planned v/s Actual
10%
30%
60%
100%
Production Percentage: Planned v/s Actual
10%
Production at Par
30%
Over Production
Under Production
60%
Figure 4 Production Percentage
4.0 CONCLUSION
The strength of any business organization is related to availability of cash. Materials are the
major constituent of the products and hence lot of engagement of funds, which need to be
controlled for effective functioning. One of the biggest concerns of product manufacturers and
company employees is eliminating Lean waste. It is very important to do away with this waste
and reduced the cost of final product. The waiting time shall automatically get reduced creating a
‘Pull Production’ in place of ‘Push Production’. The processes, especially the tooling, need to be
improved to facilitate easy and positive changeover. Such controls once put in positions will
provide free flow of material including better utilization of available man power. The paper
reveals the one of important issue in organizations that is Overproduction-Inventory. The
contributions of overproduction items lead towards the excessive unutilized funds including unnarrated inefficiencies due to the wastes.
REFERENCES
1) Kobayashi, I. (1995). “20 keys to workplace improvement”, Productivity Inc., Revised
edition, Portland, OR, USA.
2) Mader, R. P. (2005). “Lean thinking works in construction too”, Contractor, February
2005.
19
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
3) Moore, R. (2006). “Selecting the right manufacturing improvement tools”, Elsevier Science
& Technology Books, ISBN: 0750679166.
4) Spear, S. J. (2004). “Learning to lead at Toyota”, Harvard Business Review, May 2004,
pp.78 – 86.
5) Parks, C. M. (2002). “Instill lean thinking”, Industrial Management, Sept.– Oct. 2002, pp.
5 – 18.
6) Wheatley, M. (2005). “Think lean for the long term”, Manufacturing Business Technology,
June 2005. pp. 36 – 38.
7) Womack, J.P., and Jones, D.T. (1998). “Lean thinking: Banish waste and create wealth in
your corporation”, Free Simon & Schuster, New York.
8) Womack, J.P., and Jones, D.T. (2005). “Lean solutions: How companies and customers can
create value and wealth together”, Free Press, New York.
AUTHORS BIBLIOGRAPHY
1
S.K.Gupta holds Bachelor in Production Engineering, Masters in Manufacturing and
Automation and persuing PhD in Mechanical. Currently, he is working as an Assistant Professor
in the Department of Mechanical Engineering at Manav Rachna International University,
Faridabad, Haryana, India. His area of interest is Productivity Improvement, Man-Management,
Lean and Green Manufacturing, and Six-Sigma etc.
2
Dr. R.V. Singh completed B.Sc. in Engg. (Mechanical) with distinction from MIT
Mujhafarpur, Masters in Engg. (Production) with distinction from D.C.E., Delhi, PhD. from IIT
Delhi. He is associated with FET, MRIU as a Professor and Head of Mechanical Engineering
Department. He has more than 16 years experience in teaching and 15 research papers to his
credit at National or International Level. His area of interest is Production Engineering, modeling
and optimization, Precision Engineering. He has guided 9 M.Tech. Dissertations and currently he
is supervising 6 research scholars. He is life member of IEI, India, ISTE, ISME, and MSI.
3
Dr. V.K. Mahana is doctorate from IIT Delhi. He is associated with FET, MRIU as a Professor
in Mechanical Engineering Department at Manav Rachna International University, Faridabad,
Haryana, India. He has more than 39 years experience in teaching. and 20 research papers to his
credit at National or International Level. His area of interest is Design, modeling and
optimization of Quality.
4
Rajender Kumar holds Diploma in Plastic and Railway Engineering, Bachelor in Mechanical
Engineering, Masters in Mechanical Engineering. Currently, he is working as an Assistant
Professor in the Department of Mechanical Engineering at Manav Rachna International
University, Faridabad, Haryana, India. He has 15 research papers to his credit at National and
International Level. His area of interest is Productivity Improvement, Quality Management, Lean
and Green Manufacturing, and Six-Sigma etc. He is also associated member of IEI, India.
20
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
INTERNATIONAL JOURNAL OF INDUSTRIAL
ENGINEERING RESEARCH AND DEVELOPMENT (IJIERD)
ISSN 0976 – 6979 (Print)
ISSN 0976 – 6987 (Online)
Volume 3, Issue 1, January- June (2012), pp. 13-20
© IAEME: www.iaeme.com/ijierd.html
Journal Impact Factor (2011): 0.8927 (Calculated by GISI)
www.jifactor.com
IJIERD
©IAEME
LEAN IMPLEMENTATION IN MANUFACTURING INDUSTRY: A
CASE STUDY
S.K. Gupta1, Dr. R.V. Singh2, Dr. V.K. Mahna3, Rajender Kumar4
1
Research Scholar, Department of Mechanical Engineering, FET, Manav Rachna International
University, Faridabad, India-121003
2
Head, Department of Mechanical Engineering, FET, Manav Rachna International University,
Faridabad,
India-121003
3
Professor, Department of Mechanical Engineering, FET, Manav Rachna International
University, Faridabad, India-121003
4
Asst. Prof., Department of Mechanical Engineering, FET, Manav Rachna International
University, Faridabad, India-121003
E-Mail: gupta.sarojkumar@gmail.com, rajender629@yahoo.com
ABSTRACT
In the present business environment, overproduction refers to excess of production over
demand of products being offered to the market. This leads to excessive inventory in
terms of finished and semi finished goods. Excess production is only relative to a given
demand, and insufficient demand is only relative to a given production and thus consider
overproduction and under consumption equivalent. Overproduction is the root cause of
imbalances, in production sections thereby; the men & machines are either unutilized or
being used for over production. The principles of lean manufacturing are very loud in the
subject matter and overproduction is the worst form of waste. In this present case, XYZ
Company manufacturing automotive products of the same type but in wide variety was
chosen for this comprehensive study. This company has problems in-hand regarding
movement of material on shop floor, accumulation of material on shop floor, and waiting
time in assembly line etc. The probable solution for above mentioned problems is to
apply optimization approaches on production system.
Keywords: Overproduction, Lean Manufacturing, Inventory and Waste
1.0 INTRODUCTION
Often, key questions in examining manufacturing processes are: what are the value-added
ratio of these supporting processes to the organization and the current plans of
13
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
manufacturing. The plan of manufacturing may remain internal or extend i.e. outsourced.
Principally the decision in this regard is of strategic nature therefore, the manufacturing
has to be maintained inside the plant, except any change in volumes, may constraint to
push the partial production outside and also the equipments, which have become
redundant may not be replaced.
Waste is an activity that does not add value. Overproduction is the ability to produce far
more products than can possibly be offered to the customer against the actual
requirement. This leads to a struggle for sale of the undesired products and creating a
situation wherein the marketing department need to apply all resources at their command
to recover the invested money. Look around place of work and it can be noticed that there
are excessive raw materials, excessive floor space unnecessarily occupied, excessive
material handling, and accrued profits on downside. They are just the flags that there is a
cause for these to be identified and addressed.
Therefore, symptoms and causes need to be identified and resolved. The normal
symptoms are excessive raw material, extra inventory, unregulated material flow,
excessive need of space for storage etc. This kills the efficiency and profitability of the
organization. "A more liberal and extensive reciprocity in the production and sale of
commodities is necessary, so that the overproduction of the companies can be
satisfactorily disposed off to the market.”
The root causes of over production are unleveled scheduling, unbalanced capacity of each
section, unreliable suppliers, unreliable process, misuse of automation, wide variety
redundant inspection, unreliable tooling etc. Therefore answer is in usage of ‘5S’ and
‘5WHY’ as application of these tools is to help in identifying the problems related to
over-production.
2.0 LITERATURE REVIEW
Successful lean implementation is approached from a strategic perspective and
companies seek to reach certain goals with lean initiatives. As creating a lean workplace
requires changing the corporate culture a robust change management strategy is needed
(Parks, 2002). Such abrupt policy changes require a top-down approach to decision
making (Kobayashi, 1995).
Mader (2005) emphasizes the need for strong top management leadership in the
implementation process. Carefully selected Kaizen events should support the
organization’s strategy and vision.
Only seeing lean as a quick fix, may give some employees the impression that Lean
might not work in certain environments, i.e. in low volume operations. Spear (2004) says
that at Toyota managers act as enablers and in that sense coach co-workers in solving
problems instead of just fixing them.
Womack and Jones (1998) and Moore (2006) have stated that, the organizations of many
types are implementing lean manufacturing, or lean production, practices to respond to
14
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
competitive challenges. They have mentioned that lean initiatives can be taken up in the
fields of automotive sector, aerospace, and consumer goods industries around the world.
Moore has discussed various implementation tools of Lean Manufacturing, which can be
incorporated in the industries.
Wheatley (2005) discussed five business factors for lean application. These factors are
Operational Performance, Competitive advantage in Price and service, Profit
Improvement, Shorter Lead-Times and reduction in prices. On analyzing these factors
Wheatly concluded that Operational Performance can be improved up to 90%,
Competitive advantage in Price and service up to 82%, Profit Improvement up to 80%,
Shorter Lead-Times up to 75% and reduction in prices up to 62%.
3.0 CASE STUDY
On the maiden visit to XYZ Company manufacturing automotive parts, there were many
surprises, which were not affecting the operating management. The people walk day-in
and day-out on the shop floor and are still unaware of the problems which remain hidden
and are a cost to the company. The aisles were full of trolleys loaded with WIP and
further every nook and corner was having no. of trays filled with WIP. Also, many of the
trays didn’t carry the material identification including the quantities lying therein. This
did represent the waste which was generated by the principle of inventory management
like ‘First in last out’ i.e. inventory getting dumped one above the other. This type of
planning attitude must provide for obsolescence and scrap. This further reveals that there
was good amount of overproduction which is again type of waste that is producing more
than the requirement. The principles of 5S have been used to identify, analyze and
evaluate the existing manufacturing system. The fact regarding over production has been
established as per production data: planned v/s actual. A total of 21 models were
identified for overproduction and this is 10% of the existing models. The period under
study is from Jul’2011 to Dec’2011 and model wise-month wise planned v/s actual
production data of these 21 models is as per Table 1 and graphically presented in Figure
1.
Table 1 Production Data: Planned v/s Actual
Model
No.
3220
3247
3289
3316
3601
3711
3728
3900
4315
4321
6124
6132
Jul'11
Plan
Actual
0
1560
150
150
4192
4872
1100
680
0
4050
6124
6286
8820
7554
4522
4160
270
3780
1000
920
0
0
0
0
Aug'11
Plan
Actual
1740
1296
0
0
2000
2769
0
0
200
975
7428
7650
13266
14511
5000
4416
1600
1331
2000
1950
200
144
300
216
Sep'11
Plan
Actual
84
0
0
0
4520
6334
150
0
0
3750
8278
5198
8795
9120
7234
5328
270
420
0
0
56
0
84
60
15
Oct'11
Plan
Actual
84
236
0
0
0
0
650
528
6250
7512
9000
11402
6675
7840
9306
11481
0
0
600
0
56
192
24
0
Nov'11
Plan
Actual
0
0
0
0
0
0
6
0
5800
5600
8598
9740
5680
7416
4325
4848
0
0
0
0
0
0
0
0
Dec’11
Plan
Actual
3050
3360
0
648
1000
1152
0
948
4200
4055
1858
2824
4714
5414
2627
4018
0
552
500
1368
48
192
84
476
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
1000
180
2300
5000
5000
959
3140
500
1830
220
2380
4770
3921
1077
4470
248
2040
200
920
0
0
0
8170
270
2796
0
1055
1798
2220
220
8210
543
8
200
565
0
11114
0
7460
0
0
192
619
0
20147
0
7780
0
8
8
546
12300
16167
0
5080
0
0
192
635
13099
16595
0
8280
0
0
0
1200
0
15500
0
1850
0
2080
0
0
1055
0
21560
0
3206
0
4704
0
0
745
7200
2200
1200
3244
0
0
0
0
857
11668
2789
1093
3636
0
648
44257
52928
45334
52100
48818
58948
66754
77992
45039
58129
32670
45698
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
Planned Production
Actual Production
Ju
l'1
A 1
ug
'1
1
S
ep
t'1
1
O
ct
'1
N 1
ov
'1
D 1
ec
'1
1
(In Numbers)
Month Wise Production Data:
Planned v/s Actual
Production Quantity
6133
6138
6143
6213
6226
6229
6241
6268
6288
Grand
Total
Months
Figure 1 Planned v/s Actual Production
The compiled data in Table 1 has been analyzed and incorporated in Table 2 below. It is
the application 5 Why’s which have led to establishing long setup times, unbalanced
interdepartmental production, staying busy, unbalanced scheduling, larger plans, old
machines and failure of implementation of preventive plans.
The analysis of data in Table 2 reveals that 30% of total production falls under the
category of over production. This results that there is an extra inventory to the tune of
2% of monthly production. In one of the item the over producing for 778 days that is item
not to be produced for two years. This situation is quite alarming. Therefore, the obvious
results are excessive material on shop floor, extra material requirement, additional shop
floor space, blockage in material flow and high utility course. This leads to inefficient
operations and cutting down in profitability. The slogan of staying busy has to be deleted
including improvement in redundant inspection and also reduction in setup times.
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International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
Table 2 Production Data Analysis Summery
Model No.
3220
3247
3289
3316
3601
3711
3728
3900
4315
4321
6124
6132
6133
6138
6143
6213
6226
6229
6241
6268
6288
Grand Total
Plan
4958
150
11712
1906
16450
41286
47950
33014
2140
4100
360
492
3056
588
6276
24500
49981
2159
28944
770
2080
282872
Actual
6452
798
15127
2156
25942
43100
51855
34251
6083
4238
528
752
4626
604
6601
31335
67232
2390
35582
791
5352
345795
Excess Quantity
1494
648
3415
250
9492
1814
3905
1237
3943
138
168
260
1570
16
325
6835
17251
231
6638
21
3272
62923
Monthly average
826
25
1952
318
2742
6881
7992
5502
357
683
60
82
509
98
1046
4083
8330
360
4824
128
347
Days
54
778
52
24
104
8
15
7
332
6
84
95
92
5
9
50
62
19
41
5
283
(In Days)
Overproduction Inventory
Model-Wise Overproduction Inventory
900
800
700
600
500
400
300
200
100
0
1
2 3
4
5
6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 21
Model Serial Number
Figure 2 Inventory Optimization
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International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
Table 3 confirms that, there is no relation between planned production and actual production.
The data depicted in Table 3 is covering the entire range of monthly production of XYZ
company manufacturing automotive parts. There is a wide gap between these two, this may be an
indication of projecting consistently more, which can’t be produced and henceforth the desired
objectives can’t be achieved.
Table 3 Gross average monthly production
Months
Jul'11
Aug'11
Sept'11
Oct'11
Nov'11
Dec'11
Average
Planned Production
222521
250428
266333
248845
186317
176038
225080
Actual Production
151431
156504
152994
209559
149798
150009
161716
300000
Planned
Production
250000
200000
Actual
Production
150000
100000
50000
N
ov
'1
1
D
e
c'
11
A
ve
ra
ge
O
ct
'1
1
A
ug
'1
1
S
ep
t'1
1
0
Ju
l'1
1
(In No.'s)
Production Quantity
Overall Performance: Planned v/s Actual
Months
Figure 3 Gross average monthly productions
It is concluded in Table 4 that the Production Planning and Control Department of said company
is working with no exposure to the technological advancements. It is evident that the production
data doesn’t match with the planned production. In most of the categories, it is underproduction
followed with overproduction and further very small percentage matching with the planned data.
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International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
Table 4 Actual Performance: Planned v/s Actual
Production
Data
Production at
Par
Over
Production
Under
Production
Total
Percentage:
Planned v/s Actual
10%
30%
60%
100%
Production Percentage: Planned v/s Actual
10%
Production at Par
30%
Over Production
Under Production
60%
Figure 4 Production Percentage
4.0 CONCLUSION
The strength of any business organization is related to availability of cash. Materials are the
major constituent of the products and hence lot of engagement of funds, which need to be
controlled for effective functioning. One of the biggest concerns of product manufacturers and
company employees is eliminating Lean waste. It is very important to do away with this waste
and reduced the cost of final product. The waiting time shall automatically get reduced creating a
‘Pull Production’ in place of ‘Push Production’. The processes, especially the tooling, need to be
improved to facilitate easy and positive changeover. Such controls once put in positions will
provide free flow of material including better utilization of available man power. The paper
reveals the one of important issue in organizations that is Overproduction-Inventory. The
contributions of overproduction items lead towards the excessive unutilized funds including unnarrated inefficiencies due to the wastes.
REFERENCES
1) Kobayashi, I. (1995). “20 keys to workplace improvement”, Productivity Inc., Revised
edition, Portland, OR, USA.
2) Mader, R. P. (2005). “Lean thinking works in construction too”, Contractor, February
2005.
19
International Journal of Industrial Engineering Research and Development (IJIERD), ISSN 0976 –
6979(Print), ISSN 0976 – 6987(Online) Volume 3, Issue 1, January - June (2012), © IAEME
3) Moore, R. (2006). “Selecting the right manufacturing improvement tools”, Elsevier Science
& Technology Books, ISBN: 0750679166.
4) Spear, S. J. (2004). “Learning to lead at Toyota”, Harvard Business Review, May 2004,
pp.78 – 86.
5) Parks, C. M. (2002). “Instill lean thinking”, Industrial Management, Sept.– Oct. 2002, pp.
5 – 18.
6) Wheatley, M. (2005). “Think lean for the long term”, Manufacturing Business Technology,
June 2005. pp. 36 – 38.
7) Womack, J.P., and Jones, D.T. (1998). “Lean thinking: Banish waste and create wealth in
your corporation”, Free Simon & Schuster, New York.
8) Womack, J.P., and Jones, D.T. (2005). “Lean solutions: How companies and customers can
create value and wealth together”, Free Press, New York.
AUTHORS BIBLIOGRAPHY
1
S.K.Gupta holds Bachelor in Production Engineering, Masters in Manufacturing and
Automation and persuing PhD in Mechanical. Currently, he is working as an Assistant Professor
in the Department of Mechanical Engineering at Manav Rachna International University,
Faridabad, Haryana, India. His area of interest is Productivity Improvement, Man-Management,
Lean and Green Manufacturing, and Six-Sigma etc.
2
Dr. R.V. Singh completed B.Sc. in Engg. (Mechanical) with distinction from MIT
Mujhafarpur, Masters in Engg. (Production) with distinction from D.C.E., Delhi, PhD. from IIT
Delhi. He is associated with FET, MRIU as a Professor and Head of Mechanical Engineering
Department. He has more than 16 years experience in teaching and 15 research papers to his
credit at National or International Level. His area of interest is Production Engineering, modeling
and optimization, Precision Engineering. He has guided 9 M.Tech. Dissertations and currently he
is supervising 6 research scholars. He is life member of IEI, India, ISTE, ISME, and MSI.
3
Dr. V.K. Mahana is doctorate from IIT Delhi. He is associated with FET, MRIU as a Professor
in Mechanical Engineering Department at Manav Rachna International University, Faridabad,
Haryana, India. He has more than 39 years experience in teaching. and 20 research papers to his
credit at National or International Level. His area of interest is Design, modeling and
optimization of Quality.
4
Rajender Kumar holds Diploma in Plastic and Railway Engineering, Bachelor in Mechanical
Engineering, Masters in Mechanical Engineering. Currently, he is working as an Assistant
Professor in the Department of Mechanical Engineering at Manav Rachna International
University, Faridabad, Haryana, India. He has 15 research papers to his credit at National and
International Level. His area of interest is Productivity Improvement, Quality Management, Lean
and Green Manufacturing, and Six-Sigma etc. He is also associated member of IEI, India.
20