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International Journal of Lean Thinking Volume 3, Issue 1 (June 2012)

Lean Thinkingjournal homepage: www.thinkinglean.com/ijlt

Lean Manufacturing: a study of application in a customary atmosphere

D. Rajenthirakumar * Department of Mechanical Engineering, PSG College of Technology, Peelamedu Coimbatore – 641 004, Tamil Nadu, India E-mail: [email protected]

R. Sridhar PSG College of Technology, Coimbatore, India E-mail: [email protected]

A.Dominic Savio PSG College of Technology, Coimbatore , India

A B S T R A C T K E Y W O R D S

A R T I C L E I N F O

Lean manufacturing, Value stream mapping (VSM), Inventory, Line balancing

Received 12 July 2011 Accepted 04 October 2011 Available online 01 December 2011

Lean Manufacturing is a technique originally developed in the automotive industry that concentrates on shortening the time between the customer’s order and shipment. Lean manufacturing has been applied very successfully in manufacturing operations, resulting in shorter production lead times, greatly reduced inventories, and significantly enhanced profitability. These techniques also promote improved flexibility, enhanced reliability and substantial cost reductions [1-4].

This work addresses the implementation of lean philosophy in a textile machinery manufacturer, with a focus on elimination of process bottle necks and optimizing the process layout. Value stream mapping was the main tool used to identify the opportunities for various lean techniques. The primary motive is to evolve and test several strategies in the elimination of bottle necks on the shop floor by the incorporation of a layout modification and a versatile automation strategy. Simulation models are built for the inherent processes and the denouements of such changes modeled and analyzed. The effects of lean and the value addition by automation are clearly demonstrated by the simulation. A noticeable reduction in lead time and work-in-process inventory level is achieved.

________________________________ * Corresponding Author

1. Introduction and literature survey

Waste elimination is one of the most effective ways to increase the profitability of any

business. Processes either add value or waste during the production of a goods or service.

Waste and its elimination form the core of the Toyota Production System [5], also known as

lean manufacturing. Lean typically targets the seven so-called deadly wastes, which are: (i)

overproduction (ii) unnecessary inventory (iii) excess motion (iv) waiting (v) transportation (vi)

inappropriate processing (vii) non-right the first time, defects. Applications of lean

S. Jerine Chrispal Prakash PSG College of Technology, Coimbatore , India

N. Srinath PSG College of Technology, Coimbatore , India

RAJENTİRAKUMAR, SRIDHAR, SAVIO, PRAKASH, SRINATH / International Journal of Lean Thinking Volume 3, Issue 1(June2012)

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manufacturing have spanned many sectors including automotive, electronics, white goods, and consumer

products manufacturing [6].

To eliminate waste, it is important to understand exactly what waste is and where it occurs. While

products differ significantly between factories, the typical wastes found in manufacturing environments

are quite similar. For each kind of waste, there is a strategy to reduce or eliminate its effect on a company,

thereby improving overall performance and quality. Discrete Event Simulation is one tool for

identification of production waste and VSM and other process modeling methods are also used in lean

manufacturing system development and analysis [7].

The textile machinery manufacturing is one of the largest capital goods segments in India. While there

are a few firms close to the international frontier in terms of product, design, capability and process

technology, the technical capabilities of several other players are limited. The capital goods industry

contributes 9 to 12 % of the total value added in manufacturing and hence the growth of this sector has a

close co-relation with industrial development. Of the Gross Domestic Investment, the capital goods

industry accounts for a share of 17 to 21%. This sector has lately demonstrated high versatility and with

the improvement in the overall economic scenario, this sector has shown a growth rate of over 12% in

2004-2005 and the momentum is continuing (Fig. 1) [8].

Fig. 1 Indian textile machinery demand trend

In order to compete with their global counterparts, the textile machinery manufacturer must prepare for a

new business world where variety and customization of products become the norm. They need to

increase their market share and differentiate from their competitors. Moreover, due to the market crisis

DEMAND FOR TEXTILE MACHINERY

44 43

3430

27 29

0500

10001500200025003000350040004500

1999-00 2000-01 2001-02 2002-03 2003-04 2004-05(E)(YEARS)

(VA

LUE

IN R

S. C

RO

RE

)

10

20

30

40

50

PRODUCTION (Minus Exports)IMPORTS (less parts imported by machinery manufacturers)TOTAL DOMESTIC DEMAND% Share of demand met by indigenous industry

Source : Directorate General of Commercial Intelligence & Statistics, Government of India


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the differences are required not only to increase market share but also to stay in business. Consumers

constantly demand better, faster, cheaper and customized goods. An important philosophy that fits these

goals is lean manufacturing.

This work intends to show a solution to improve the manufacturing processes of textile machinery with

the use of lean manufacturing tools and simulation techniques.

2. Brief Literature review

The characteristics and impacts brought by lean tools and techniques have been presented in a number of

works [9–12]. The successful application of various lean practices had a profound impact in a variety of

industries, such as aerospace, computer and electronics manufacturing, forging company, process

industry (steel), and automotive manufacturing. Their methodology is similar, using lean tools, and they

are adapted to the study variables, but the improvement point and the results achieved are different. Many

lean manufacturing tools to be used in conjunction with VSM were proposed by number of researchers

[1, 13-16]. Sullivan et al provides how value analysis time profile in conjunction with VSM methodology is

beneficial to make a change either at an intra or interfirm level. A case study of an automobile company

has been described to illustrate the methodology and to highlight the role of this tool as a simulation

device to quantify the impact of improvement activities.

One of the major challenges for manufacturing industry is to manufacture variety products with a

minimum lead time, reduced inventory and world class quality. There is a need to help the manufacturing

companies to improve their competitiveness. In this paper, a case study conducted at a textile machinery

manufacturing company is presented and some of the observations may be useful to the practitioners for

motivating their efforts in implementing lean in small and medium enterprises.

3. Problem environment

3.1 Profile of the company

The company, ABC Limited is a leading textile machinery manufacturer in India which produces a range

of spinning machinery. In 1962, the company was founded to provide the Indian textile mills with the

latest spinning technology. Today it caters to around 60% of the domestic market and has emerged as the

leader in the export of textile machinery in India.


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3.2 Product description

The name of the product selected in this work is “pressure finger” which is an integral part of a

component by name “flyer” (Fig. 2). The component is used in textile industries to produce very fine

threads. It is used to guide the thread coming out of the flyer-tube to the bobbin that is attached to the

spindle. Accurate guiding of the thread is governed by certain parameters, out of which, the radius of the

pressure finger (EN 8 steel and 300 grams weight) is the most critical. Fig. 3 shows the major operations

involved in the manufacturing of pressure finger. Cycle time for various operations are summarised in

Table 1.

Fig. 2 Three dimensional model of the “flyer” with “pressure finger”

Fig. 3 Major operations involved


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Table 1 Summary of cycle time for various operations

Sl. No. Description Time

1. Paddle polishing – batch processing 30 min

2. Paddle welding 2.6 min

3. Annealing – batch processing -

4. Grinding 2 min

5. Perpendicular bending 1.6 min

6. Radius bending 1.8 min

7. Regrinding and radius checking 3.1 min

After several brain storming and a thorough study of the shop floor, it was observed that manufacturing

operations sequence consists various forms of non-value-adding activities as follows:

Back-tracking of parts from grinding station to bending station - increased transportation distance

and time

All the operations involve batch processing in the existing layout. But, as a matter of fact, there

are certain operations in the layout viz. the perpendicular bending operation and the bending

operation which would otherwise involve single piece flow, if not for the improper arrangement

of machines

Operations like annealing and paddle polishing always involve processing in batches due to the

nature of the process

Since all the machines in the existing layout involve batch processing, the nature of inventory

involved between the machines in the form of Work-in-Process is appreciable and could be

possibly reduced to enhance the process effectiveness

The main goal is to develop different strategies to reduce the level of non value activities present in any

form by implementing the various lean tools. The work targets are as follows:

Identification of critical (bottle-neck) operation in pressure finger processing layout

Analysis and incorporation of a feasible lean solution that would serve to eliminate the waste

Elimination of back-tracking movements - demands a proper change in the physical arrangement of

parts (layout)

Establishment of flow manufacturing


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4. Implementation and results

4.1 Continuous flow

As a first step to establish continuous flow, VSM is done. The current state map presents the existing

position of the company. The critical problem areas and different kinds of non-value added activities are

identified in this stage. The next step is development of future state map. In order to develop the future

state map, the current state map was analysed using the steps and guidelines developed by Rother and

Shook [18]. The last step is analysis of the results obtained after implementing the proposed changes.

This has to be quantified in terms of lead time reduction, cycle time reduction, inventory reduction, etc.

All the data for current state map are collected according to the approach recommended by Rother and

Shook [18]. The data boxes are prepared to capture the changeover time, available time and cycle time.

The information flow is also captured. The production lead time and value-added time are noted on the

current state map. It provides the snapshot in time. Inventory storage points in between the stages are

shown in triangles. The timeline at the bottom of the current state map has two components. The first

component is the production lead time and second component is value-added time or processing time.

Value-added time is calculated by adding the processing time for each process in the value stream. The

cycle time for each is the average cycle time, which is determined by using actual data from the company.

This current state map provides a picture of existing positions and guide about the gap areas. It helps to

visualise how things would work when some improvements are incorporated. The gap area in the existing

state results in a road map for improvement. Fig. 4 shows the current state map.


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Fig. 4 Current state map


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4.1.1 Redesign of existing layout – Visual examination method

The existing layout used in the company is shown in Fig. 5. It is observed that the distance traveled by the

component before the completion of all manufacturing operations is 81 feet. This can be attributed to the

fact that there is back–tracking involved in the existing layout which suggests that there is a scope for

improvement. Emphasis is always on increasing the percentage of in–sequence movement.

Fig. 5 Existing layout

During the redesign, the layout is changed without affecting the precedence constraint in such a way that

the machines that involve batch processing are kept in cell 1 and machines involving single piece

processing are kept in cell 2. In this process, space constraint is another factor that is kept in mind and

the newly designed layout (Fig. 6) also ensured that the machines belonging to the sub-contract system

must not be brought to cell 1, which is against the best interests of the company.

Fig. 6 Redesigned layout


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4.1.2 Work-space utilisation

Work-space is an imaginary area occupied by a machine wherein the distance between successive

machines is always greater than four feet [20]. The term work-space includes the space occupied by every

machine plus some of the free space on either side of a machine (Table 2). The redesigned layout

requires annealing to be included in cell 1 in place of perpendicular bending and the latter should be

shifted to cell 2. Further, from Table 2, it is observed that both the cells occupy the same area and that;

cell 2 has lesser free space than cell 1. Hence, there is some scope for improvement which leads to a

corresponding increase in free space in cell 2.

Table 2 Summary of work-space utilisation

MACHINE WORK SPACE Cell 1 Paddle polishing machine 4x4 feet Paddle welding machine 10x5 feet Perpendicular bending 8x6 feet Total area of cell 1 40x20 feet

Free space in cell 1 15 feet (measured from perpendicular bending machine to partition wall)

Cell 2 Annealing 11x7 feet Grinding machine 6x4 feet Bending (bending to required shape) machine 8x6 feet

Regrinding and radius checking 12x6 Total area of cell 2 40x20

Free space in cell 2 less than 10 feet ( measured from radius checking machine till the end of cell 2)

Observations led to a conclusion that both annealing and perpendicular bending occupied approximately

the same space and it is viable that the former can be replaced by the latter considering the fact that there

is 15 feet of free space after accommodating the perpendicular bending machine. But in the re-designed

Layout, this free space would decrease to 12 feet which is still within the acceptable limits. Fig. 7 shows

the work space of machines in the re-designed layout and a conspicuous increase in free space in cell 2

with a corresponding decrease in free space in cell 1. Also, with annealing now being shifted to cell 1, it

provides considerable leeway which is a pre-requisite, given the nature of the process.


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Fig. 7 Work space of machines in the re-designed layout

4.1.3 Line balancing

Line balancing is a strategy used in the allocation of resources and work schedules to the workers

involved, thereby minimizing discrepancies arising from unequal service times and idle times [19]. In this

work, the Ranked Positional Weight (RPW) method [19] is used for line balancing and the methodology

followed is shown Fig. 8. The results of line balancing are given in Table 3 and Fig. 9. From the line

balancing results, it is evident that at station “D” for operation “5” the cycle time is 3.1 min which exceeds

the takt time by 0.12 min. This implies that the operation “5” in station “D” is a “critical operation” and

steps should be taken to minimize this discrepancy. Further, the results of line balancing, which are done

on this redesigned layout, yielded a result which could possibly bolster the new redesign i.e. grouping of

machines involving batch processing together in cell 1 and machines involving single piece processing in

cell 2.

Fig. 8 RPW method for line balancing

Draw PERT diagram considering the precedence constraints

Compute RPW time (time from start to finish)

Arrange operations in decreasing orders of RPW time and rank

Compute “takt time” and fix it as constraint for grouping (takt time=total working time/demand)

Assign work element to station / Higher RPW time given preference / Continue until “takt time” is violated


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Table 3 Results of RPW method – Assignments of operations to stations

Station Manufacturing operation Total station time (min)

A 1 2.6

B 2 2.0

C 3 1.6

D 4 1.8

E 5 3.1

Fig. 9 Line balancing result - Identification of critical operation

The critical operation can be eliminated by adopting either of the following two methods: (i) By

increasing the number of operators in station “D” (ii) By the adoption of suitable automation strategies to

minimize the cycle time in station “D”.

4.1.3.1 Automated measurement system

The critical operation, checking and regrinding pressure finger is eliminated by the implementation of

automated measurement system (Fig. 10). The idea of the automation system is to segregate the pressure

fingers with the correct radius from the incorrect ones. The radius of the pressure finger forms the critical

dimension and it requires checking cum hammering for the correction of radius. The automation system

enables to hasten the process and increases the flow rate of the component.


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Fig. 10 Elimination of critical operation – Automated measurement

The complete sequence of operation is as follows: (i) the conveyor is made to run at a constant speed. It

essentially forms a closed loop circuit (ii) as the pressure finger proceeds in its course, it is detected by

the proximity sensors and its signals are sent to a timer (iii) the signal from the timer stops the

component after a particular off-time delay and the component is positioned under the vertical pneumatic

cylinder (iv) a signal is sent to the solenoid valves which trigger the movement of the cylinder downwards

(v) when the cylinder head reaches the bottom position, the magnetic sensors detect them and it further

actuates the end effecter solenoids (vi) when the end effectors close, they close with a particular pressure.

If there is an irregularity in the pressure finger radius, the applied pressure causes the bend sensors to

deform accordingly (vii) the analog signals from the sensors are converted to digital signals with the help

of analog to digital converters (viii) based on the digital signals, the solenoid at the divider end of the

conveyor opens or closes (ix) the piece with the incorrect profile gets segregated into a separate bin.

4.1.3.2 Cost-benefit analysis

In order to justify the improvement initiative, a detailed cost-benefit analysis is done based on pay-back

period method. The payback method uses a simple concept that the net revenue derived from an

investment should pay back the investment within a certain period of time.

The Net Annual Cash Flow (NACF) refers to the net revenue in a given year. If the revenue exceeds costs

for the year, the NACF is positive. If costs exceed revenue, the NACF is negative. The payback period is

defined as initial cost of the investment divided by NACF. The various cost elements associated with the

automated measurement system is given in Table 4 and the payback period is calculated as 18 months.


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Table 4 Cost elements of automated measurement system

Description Amount (`)

Total number of workers 5.00

Total cost per piece 6.25

Savings per piece (in terms of labour charge) 1.25

Savings per day (for 150 pieces) 187.50

Amount saved in 24 working days 4500.00

Electricity cost per day to run the conveyor 0.61

Electricity cost per month 14.52

Net savings in running cost per month 4485.48

Net savings per year (NACF) 53500.00

Initial cost of the investment 78750.00

Payback period (78750/53500) ~ 18 months

4.2 Simulation model

To evaluate potential gains based on the implementation of the lean tools, a detailed simulation model is

developed using Arena simulation software (21). Before evaluating the future state considerable effort is

expended to verify and validate the model for the current system. Verification is the process that ensures

that the simulation model mimics the real system. A detailed animation is also used to verify that the

model sufficiently replicated the real system. Based upon the initial observations from the current state

map and discussions with managers at ABC limited it is decided to measure the two primary performance

measures (i) machine availability (ii) value added time. A snap shot of the arena simulation results is

shown in Fig. 11. It is found the magnitudes of the improvements in the two selected performance

measures are significant. Further, the results indicate that the machine availability is increased by 50% and

the value added time also improved by 70%.


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Fig. 11 Snap shot of arena simulation result showing machine availability

5. Conclusions

The textile machinery manufacturer must seek improvement alternatives as a part of their global strategy

to stay in business, to remain competitive and to increase their market share in a tougher market. Lean

manufacturing tools, as the one studied in this work, proved to be good strategies for textile machinery

manufacturer to achieve improvements that significantly outweigh the cost of the implementation. This

work gives a set of alternatives to improve the output of a productive system without incurring in major

investment.

References

1. Womack JP, Jones D, Roos D (1990) The machine that changed the world. Rawson Associates, New

York

2. Peters G, Lodge M, Goodrich BF (1999) Aerospace 717 engine nacelle. Lean Enterprise Institute,

Atlanta

3. Womack JP, Fitzpatrick D (1999) Lean thinking for aerospace: the industry that can afford its future.

Lean Enterprise Institute, Atlanta


34

4. Liker JK (1998) Becoming lean. Productivity Press, Portland

5. Monden Y (1993) Toyota Production System: An Integrated Approach to Just-in-Time. Chapman and

Hall, London

6. Womack JP, Fitzpatrick D (1999) Lean thinking for aerospace: the industry that can afford its future.

Lean Enterprise Institute, Atlanta

7. Juhain Heilala, Salla Lind, Bjorn Johansson et al (2008) Simulation based sustainable manufacturing

system design. Proceedings of the 2008 winter simulation conference

8. Textile Machinery Manufacturers' Association (India) (2011) Home page at http://www.tmmaindia.net/

9. Dyer JH, Ouchi WG (1993) Japanese-style partnerships: giving companies a competitive edge. Sloan

Manag Rev 35:51–63

10. Womack JP, Jones DT (1996) Beyond Toyota: how to root out waste and pursue perfection. Harvard

Bus Rev (September– October):140–158

11. Womack JP, Jones DT (1996) Lean thinking: banish waste and create wealth for your corporation.

Simon & Schuster, New York

12. Shah R, Ward PT (2007) Defining and developing measures of lean production. J Oper Manag

25:785–805

13. Barker R. C. (1994) The design of lean manufacturing systems using time based analysis. International

Journal of Operations and Production Management, Vol. 14, pp. 86–96

14. Hines, P. and Rich, N. (1997) The seven value stream mapping tools’, International Journal of

Operations and Production Management, Vol. 17, No. 1, pp. 46–64

15. Liker, J. K. (1998) Becoming Lean. Productivity Press


35

16. Taylor, D. and Brunt, D. (2001) Manufacturing Operations and Supply Chain Management: The Lean

Approach. Thomson Learning.

17. Sullivan, J., Hines, P., Rich, N., Bicheno, J., Brunt, D., Taylor, D. and Butterworth, C. (1998) Value

stream management. Int Jour of Logistics Management, Vol. 9, No. 1, pp. 25–42.

18. Rother, M., Shook, J. (1998) Learning to See: Value Stream Mapping to Add Value and Eliminate

Muda. The Lean Enterprise Institute.

19. Groover Mikell P (2000) Automation, Production Systems, And Computer- integrated Manufacturing.

PHI

20. Sunderesh S Heragu (2006) Facilities design. iUniverse, USA.

21. David Kelton W., Randall P. Sadowski, Nancy B. Swets (2010) Simulation with Arena. Rockwell

Automation, McGraw-Hill

http://www.infibeam.com/Books/search?author=Groover%20Mikell%20P

http://www.infibeam.com/Books/phi-publisher/

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