Antony, Jiju (2006) Implementing the Lean Sigma Framework in an Indian SME

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Production Planning & Control
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Implementing the Lean Sigma framework in an Indian
SME: a case study
M. Kumar a , J. Antony b , R. K. Singh c , M. K. Tiwari d & D. Perry a
a Division of Management, Caledonian Business School, Glasgow Caledonian University,
Cowcaddens, Glasgow G4 0JF, UK
b Centre for Research in Six Sigma and Process Improvement (CRISSPI), Caledonian Business
School, Glasgow Caledonian University, Cowcaddens, Glasgow G4 0BA, UK
c Department of Production Engineering, Birla Institute of Technology, Mesra, Ranchi-835
215, India
d Department of Forge Technology, National Institute of Foundry and Forge Technology,
Ranchi-834 003, India
Available online: 21 Feb 2007
To cite this article: M. Kumar, J. Antony, R. K. Singh, M. K. Tiwari & D. Perry (2006): Implementing the Lean Sigma
framework in an Indian SME: a case study, Production Planning & Control, 17:4, 407-423
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ProductionPlanning&Control,
Vol.17,No.4,June2006,407–423
Implementing the Lean Sigma framework in an
Indian SME: a case study
M. KUMARy, J. ANTONY*z, R. K. SINGHx, M. K. TIWARI{ and D. PERRYy
yDivision of Management, Caledonian Business School, Glasgow Caledonian University,
Cowcaddens, Glasgow G4 0JF, UK
zCentre for Research in Six Sigma and Process Improvement (CRISSPI), Caledonian Business School,
1 Glasgow Caledonian University, Cowcaddens, Glasgow G4 0BA, UK
1
0 xDepartment of Production Engineering, Birla Institute of Technology, Mesra, Ranchi-835 215, India
2
er {Department of Forge Technology, National Institute of Foundry and Forge Technology,
b
m Ranchi-834 003, India
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N
5
2
9
5
6: Lean and Six Sigma are two widely acknowledged business process improvement strategies
0
at available to organisations today for achieving dramatic results in cost, quality and time by
] focusingonprocessperformance.Lately,LeanandSixSigmapractitionersareintegratingthe
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d twostrategiesintoamorepowerfulandeffectivehybrid,addressingmanyoftheweaknesses
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cl and retaining most of the strengths of each strategy. Lean Sigma combines the variability
h
at reduction tools and techniques from Six Sigma with the waste and non-value added
Str elimination tools and techniques from Lean Manufacturing, to generate savings to the
f bottom-line of an organisation. This paper proposes a Lean Sigma framework to reduce
o
y the defect occurring in the final product (automobile accessories) manufactured by a
sit die-casting process. The proposed framework integrates Lean tools (current state map, 5S
er System, and TotalProductive Maintenance (TPM))within Six Sigma DMAIC methodology
v
ni toenhancethebottom-lineresultsandwincustomerloyalty.Implementationoftheproposed
U framework shows dramatic improvement in the key metrics (defect per unit (DPU), process
[
y capabilityindex,meanandstandarddeviationofcastingdensity,yield,andoverallequipment
b
d effectiveness (OEE))and asubstantial financial savings isgenerated bythe organisation.
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d
a
o Keywords: Six Sigma; Lean;Case study;Framework; SME
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1. Introduction the market share and maximise profit. All the large
companies such as Toyota, Danaher Corporation,
The last two decades has witnessed an increased General Electric, Motorola, Honeywell, and many
pressure from customers and competitors for greater others, have achieved dramatic results by implementing
value from their purchase whether based on quality, either Lean or Six Sigma methodologies in their
faster delivery, or lower cost (or combination of both) organisation (Womack and Jones 1996, Harry 1998,
in both manufacturing and service sector (Basu 2001, Basu2001,Murmanetal.2002,Sharma2003,Arnheiter
George 2002). This has encouraged many industries to and Maleyeff 2005).
adopt either Six Sigma (as their process improvement ShahandWard(2003)accentuatedtheimportanceof
and problem solving approach) or Lean Manufacturing plant size, plant age, and union status on the likelihood
(for improving speed to respond to customer needs and ofimplementing22manufacturingpracticesthatarekey
overallcost)aspartofmanagementstrategytoincrease facetsoftheLeanproductionsystem.Thecorethrustof
Leanproductionisthatitworkssynergisticallytocreate
*Corresponding author.Email: [email protected] a streamlined, high quality system that produces
ProductionPlanningandControl
ISSN0953–7287print/ISSN1366–5871online(cid:1)2006Taylor&Francis
http://www.tandf.co.uk/journals
DOI:10.1080/09537280500483350
408 M. Kumar et al.
finished products at the pace of customer demand with theintegratedapproachofLeanandSixSigmabusiness
little or no waste. Lean strategy brings a set of proven strategies is delineated in figure 1. Figure 1 is based on
tools and techniques to reduce lead times, inventories, the previous works of experts in Lean and Six Sigma
set up times, equipment downtime, scrap, rework and (Womack and Jones 1996, James-Moore and Gibbons
other wastes of the hidden factory. 1997, Hoerl 1998, Rother 1998, Breyfogle III 1999,
The statistically based problem solving methodology Harry and Schroeder 1999, Emiliani 2000, Hines and
of Six Sigma delivers data to drive solutions, delivering Taylore 2000, Pyzdek 2000, Antony et al. 2003, Snee
dramatic bottom-line results. Linderman et al. (2003) and Hoerl 2003). The use of the comprehensive set of
accentuated the importance of social and psychological tools mentioned above can help to reduce all kinds of
considerations in understanding Six Sigma phenomena waste (rework, over production, waiting, material,
and how effective use of goals helps alter the behaviour human skills, transportation and unnecessary move-
of organised members and their perceptions about how ment)fromtheorganisation(Ohno1988,Womacketal.
muchchangeispossible.Authorsfurtheremphasisedon 1990, Shingo 1992, Hines et al. 1998, Liker 1998).
the understanding of the technical aspect as well as This paper presents a case study undertaken by
behavioural insight for successful deployment of Six implementing a Lean Sigma framework into an Indian
1 Sigma. Sodhi and Sodhi (2005) illustrated how a global small- to medium-sized enterprise (SME) in order to
1
20 manufacturerofindustrialequipmentappliedSixSigma reduce the defects which occur in the final product
er to its price setting process for one product line. In this manufactured by the company and thus satisfy their
b
m study, Six Sigma has transformed the tenor of the customers. The company was regularly receiving com-
e
v relationship between the pricing and sales staffs from plaints from its customers on crack propagation in the
o
N adversitytorelativeharmonyformakingjointdecisions automobile accessories manufactured by the company.
5
2 thatarealignedwithstrategicobjectivesofthebusiness. This was the major cause of customer dissatisfaction
9
5 Each methodology proposes a set of attributes that and was putting customer loyalty at risk. To retain its
6:
0 are prerequisites for effective implementation of the customers, the management realised the importance of
at respective program: top management commitment, removing operational inefficiencies and wastes from the
]
de cultural change in organisations, good communication organisation.Thegoaloftheorganisationwastoreduce
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cl down the hierarchy, new approaches to production and the defects in the product, work-in-process inventory,
h
at to servicing customers and a higher degree of training scrap and rework cost.
r
St and education of employees (Salzman et al. 2002, Therestofthepaperisarrangedasfollows:Section2
of Antony et al. 2003). providesaninsightintothedie-castingprocess,theprob-
sity Companies across the spectrum have found the most lem encountered by the company and the rationale
er effective way to eliminate the flaws that lead to rework behind selecting Lean Sigma methodology to tackle
v
ni and scrap, and create one unified idea of continuous the problem. The reasons for using Lean Sigma as a
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improvement, is the integration of Lean Manufacturing continuous improvement methodology for this case
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by and Six Sigma (Smith 2003). The integration of the two study is cited in section 3. Section 4 elucidates the
ed systems can achieve much better results than either stepsinvolvedinimplementingtheproposedframework
d
a systemcanachievealone.While,Leanstrategiesplayan to identify the root cause of the problem and propose
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nl important role in eliminating waste and non-value- correctiveactionto minimise theimpactof theproblem
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o added activities across the organisation, Six Sigma, on customer satisfaction. The effectiveness of proposed
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throughtheuseofstatisticaltoolsandtechniques,takes Lean Sigma framework is discussed in section 5.
an organisation to an improved level of process perfor- Section 6 throws light on some of the difficulties
mance and capability. The two methodologies empha- encountered while implementing the proposed frame-
sisetheunfathomableinvolvementoftopexecutivesand work. The paper is concluded in section 7.
communication with the bottom line to develop robust
products and processes in their organisation.
Most companies using the integrated approach apply 2. Company background
basicLeantoolsandtechniquesatthebeginningoftheir
program,suchascurrentstatemap,basichousekeeping Thedie-castingunitunderstudywasestablishedin1978
using 5S practice, standardised work, etc. After imple- with 150 employees, which comes under the category of
menting the above tools and techniques some wastes SME as per the classification given by Indian Trade
are eliminated from the system. Now, the tools and Industry. The organisation is engaged in designing and
techniques of Six Sigma are used to offer powerful manufacturing various types of precision machined
solutionstochronicproblems.Thecomprehensivesetof components using pressure and gravity die-casting
tools,techniquesandprinciplesthatcanbeemployedin processes. The main customers of the company are
Implementing the Lean Sigma framework in an Indian SME 409
Kanban DMAIC methodology
Workplace management Variability reduction
Set-up reduction time
Statistical process control
Total productive maintenance 5 why
Process capability analysis
Cause and effect
Mistake proofing 5S practice Belt system (MB, GB, BB, YB)
Pareto analysis
Measurement system analysis
Visual management
Change management
tools Design of experiment Robust design
Value stream mapping Histograms Quality function deployment
Control charts
11 Take time analysis Scatter diagram Failure mode and effects analysis
0
r 2 Just-in-time Project management
e
b
m Production flow balancing Regression analysis
e
ov Kaizen
N Analysis of means and variance
5 Cellular manufacturing
2
9 Hypothesis testing
5 LEAN SIX SIGMA
6:
0
] at Figure1. The toolsand techniques ofLean andSix Sigma.
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at
r ordinancefactories,theautomobileindustry,andtextile from where it is sent to the customer according to an
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f machine manufacturers. The company manufactures agreed schedule. Customer orders are taken care of
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y around250000units ofdiecastingproductsperyearto on the basis of first come first serve (FCFS). Quick
sit caterfortheneedsofitscustomers.Theemployeeswork turnaround orders (QTA) are taken care of by
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v inthreeshiftsperday,eachshiftof8hours,andsixdays rescheduling the batch processing as decided by the
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U a week to meet the market demand. production manager.
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y The die-casting process starts with placing Al-alloy
b
ed (AlSi9Cu13)ingotsinthefurnaceandheatingthemfora
ad sufficientduration.Whenthemetalmeltsandachievesa 3. Rationale for implementing Lean Sigma
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nl suitabletemperatureinthecastingfurnace,itisinserted
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o intothediesbyplungerpressure.Asthemetalsolidifies The application of different quality programmes to
D the cast product is taken out with the help of an ejector reducetheoperationalinefficienciesandwastesrequires
pinandplacedinatrolley.Thecastproductthengoesto topmanagementinvolvementandcommitmentinorder
the trimming and fettling shop where extra projections to provide appropriate resources and training. The top
are removed. The trimmed product is moved to the levelmanagementintheSMEwereproponentsofLean
drilling section (MC1) where the different holes and andusedtopracticeTPM,Kaisen,and5Ssystemsinthe
grooves are made as per the dimensions in the drawing. organisation. Management showed confidence at the
In the next step, semi-finished products go to the beginningoftheinitiativeandsupportedthequalityand
de-burring unit (MC2) where the external and internal production managers with the variety of resources and
holes are cleaned and burrs are removed. It is then training required for successful deployment of Lean
moved to the chamfering and threading unit (MC3) principles. As a result, there was less work-in-process
where fine cutting at different angles along the surface inventory with reduced scrap and rework cost.
and the making of external and internal threads are Management interest in the quality initiatives under-
performed. Cleaning and polishing operations are per- taken started waning as the demand from its customers
formed subsequently in the next stage. Finally, the increased. The wish to maximise return on investment
finished product is stored in the dispatch department and the fear of not meeting the customer demand
410 M. Kumar et al.
compelled the management to concentrate more on overall complexity, and helps to uncover the value-
productionthanonqualityoftheproduct.Thisresulted added activities of a process, Six Sigma can solve
in an increase in work-in-process inventory, scrap and complex cross functional problems where the root
rework cost, and more defects (external and internal causes of a problem (in this case, crack propagation)
casting defects like foliation, cracks, cold shut, pinhole are unknown and help to reduce undesirable variations
porosity, etc.) in the final product. There were many in processes. The integration of two approaches elimi-
hidden wastes embedded in the manufacturing process nates the limitations of individual approach. The team
that were ignored by the company because their membersdecidedtoadoptSixSigmaoverTQMbecause
manufacturing capacity was higher than their produc- of the following reasons:
tion requirements. Problems were tackled by increasing
. TQM focuses on long-term results and expected
the work-in-process inventory leading to higher inven-
pay-off is not well defined. Six Sigma creates a
torycarryingcost.Inthelastsixyears,demandfortheir
sense of urgency by emphasising rapid project
productbecamehighduetoglobalisationandtheboom
completion within 6 months.
intheautomobilesector.Inordertomeetthecustomers’
. Improvement results from TQM initiatives are
demand, production of automobile accessories was
small and do not bring rapid changes. The die-
1 giventoppriority,irrespectiveofthequalityofproduct.
1 casting company under investigation is an SME
20 The management was able to meet the customer
er demands by putting the quality of product at risk. and cannot afford to visualise tangible benefits
b after a period of 1 year.
m This resulted in a number of customer complaints from
e . TQM provides a vast set of tools and techniques
v different parts of the country.
o withnoclearframeworkforusingthemeffectively,
N Thisintimidatingsituationledmanagementtoponder
5 whereas Six Sigma uses DMAIC methodology for
2 over redeploying the quality initiatives taken at the
9 problem solving which successfully integrates a set
5 beginning. As most of the customer complaints were
6: of tools and techniques in a disciplined fashion.
0 related to crack propagation in the final die-casting
at product (resulting in improper functioning of the . TQM is motivated by quality idealism, whereas
] Six Sigma is driven by tangible benefits for all
de automobile engine), management formed a team to
y major stakeholders (customers, shareholders, and
hcl identifytherootcauseofproblems.Moreover,therewas employees).
at a constant increase in in-process inventory, machine
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St downtime,idletimeatdifferentworkstations,andthere It was decided that Lean would be used to create a
of was also concern about the health and safety issues of foundation that allows the tools of Six Sigma to yield
sity theemployeesastheaveragenumberofaccidentsonthe greater benefits, faster. Similar work was carried out
er shop floor were increasing each year. by Cua et al. (2001), who investigated the practice of
v
ni The management, after a thorough brainstorming TQM and Lean simultaneously and the results revealed
U
session with the senior managers of different depart- that that manufacturing performance is associated
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by ments,generatedalistof15possibleprojectsthatcould with the level of implementation of both socially-
ed enhance customer satisfaction. Multi-voting was then andtechnically-orientedpracticesoftheaforementioned
d
a used among its cross-functional team to narrow down programs. After a number of discussion sessions a
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nl theprojectslisttoasmallerlistofthetopprioritiesorto framework was developed between the team members
w
o a final selection. Multi-voting allows the item that is and the facilitators, the latter being the authors of this
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favouredbyall,butnotthetopchoiceofany,toriseto article.Thedetailsoftheframeworkarediscussedinthe
the top (Tague 2004). In order to ensure greater next section.
decision-accuracy, the voting was done by weighting
the relative importance of each choice. Further, the
outcomes from the multi-voting was debated by team 4. Framework for Lean Sigma implementation:
members to avoid errors from incorrect information or a case study
understanding about each project. One of the questions
raised during brainstorming was related to the selection A model or framework is proposed by authors to
of a continuous improvement method from a range of implement Lean Sigma in the organisation and is
existing quality improvement programmes. The team delineated in figure 2. The framework is developed by
decided to implement the Lean Sigma methodology to authorsafteranumberofmeetingswithtopandmiddle
eliminatedefects,reducevariationandreduceinventory level management. The facilitators meticulously studied
and overall complexity from the system. While Lean the whole die-casting process, met up with the employ-
streamlines processes and eliminates waste (idle time, ees working on the shop floor and enquired about
machine downtime, in-process-inventory), reduces the key parameters associated with each process,
Implementing the Lean Sigma framework in an Indian SME 411
Steps in define phase
(cid:127) Management initiatives
(cid:127) Problem definition
(cid:127) Brainstorming
(cid:127) Develop big picture map
(cid:127) Project charter Steps in measure phase
(cid:127) Define performance standards
(cid:127) Measurement system analysis
DEFINE (cid:127) Monitoring the process
(cid:127) Establish process capability
Steps in control phase
(cid:127) Control chart plotting CONTROL
(cid:127) Share the lessons learnt MEASURE
(cid:127) Mistake proofing exercise
(cid:127) Sustainability plan
ANALYSE
1
1 IMPROVE
0
2
er Steps in improve phase Steps in analyse phase
mb (cid:127) Design of experiment (cid:127) Pareto analysis
e (cid:127) Screen potential causes (cid:127) Select CTQ characteristics
ov (cid:127) Discover variable relationships (cid:127) Cause and effect diagram
25 N (cid:127)(cid:127) EEssttaabblliisshh ionpge 5raSt isnygs tteomlerances (cid:127)(cid:127) BIdreanintisftyo rvmariinagtion sources
59 (cid:127) Implementing TPM
6:
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at Figure2. Proposedframework for Lean Sigmaimplementation in the organisation.
]
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at scrupulously studied the documents of the production spent many hours on the shop floor observing, in order
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St and quality departments to check on the defective to collect data and understand the different processes
of products manufactured each day. This helped develop associated with the die-casting unit.
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sit the Lean Sigma framework for implementation on the
er shop floor. In the proposed framework, Lean tools are 4.1.2. Problem definition. A number of brainstorming
v
ni used within the Six Sigma (DMAIC) problem-solving sessions of team members were conducted to identify
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[ methodologytoreducethedefectsoccurringinthefinal critical to quality (CTQ) characteristics based on the
by product. voice of customer (VOC) input. In the meeting the
ed problem of the die-casting unit, the size of the problem,
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a the impact of the problem, etc., were discussed among
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nl 4.1. Define the team members and it was apparent that most of the
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o customercomplaintsrelatedtocrackpropagationinthe
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4.1.1. Management initiatives. An emergency meeting automobile accessories manufactured by the company.
was called by top level management with operators, The goal of the team members was to identify the root
engineers and senior managers of different departments cause of problem and reduce the defects occur in the
to discuss the restructuring required in the current product.
practices for enhancing the market share and customer
satisfaction. In order to instigate enthusiasm and 4.1.3. Current state map. In order to have an insight
motivation among employees for bringing about the into the current state of the die-casting unit, a current
required changes, senior management decided to com- state map is developed which gives a closer look at the
municate not only the successes but also the problems process so that opportunities for improvement can be
encountered while implementing Lean Sigma frame- identified.Themovementofmaterialsthroughdifferent
work.Thishelpedinidentifyingthemistakescommitted processes/facilitiesduringmanufacturingisshowninthe
in other projects and learning from such mistakes. current state map (figure 3).
A cross-functional team was formed consisting of Asshowninthecurrentstatemap,themanufacturing
the operators, engineers from production, quality, and process starts with die casting and extends all the way
marketing department, and senior managers. This team through to shipping. Below each process, process cycle
412 M. Kumar et al.
ar
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mer es/ 14
Custo 250 000 piec Tray of Weekly/monthly PATCH 7 days
S
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0.4 day
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011 Forecast ping sched POLISH-ING/cleaning CT = 13 sec C/O = 6 m U/T = 90% NO. OF SHIFTS = 2DEFECT =0.2% 13 sec 101sec.
mber 2 Ship 0.5 day ¼time
e d
59 25 Nov Chamferingandthreadingunit CT = 14 sec C/O = 6 min U/T = 90% NO. OFSHIFTS = 3DEFECT =1% 14 sec Valueadde
at 06: n 1 day days,
sity of Strathclyde] Productiocontrol Weekly schedule De-burringunit CT = 17 sec C/O = 6 min U/T = 85NO. OF SHIFTS = 3DEFECT =0.5% 0.5 day 17 sec ¼p.Leadtime5.76
r a
by [Unive Drillingunit CT= 14 sec C/O = 4 min U/T= 85% NO. OFSHIFTS = 3DEFECT = 2% 14 sec ntstatem
d re
ade 1 day Cur
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nl 3.
Dow 3 monthforecast Monthlyorder FETLING/Trimmingpress CT = 11 sec C/O = 20m U/T = 85%NO. OFSHIFTS = 3DEFECT =1.3% 11 sec Figure
2.36 days
DIECASTING CT = 32 secC/O = 20 U/T = 90%NO. OFSHIFTS = 3DEFECT = 5% 32 sec
er
ur h y
manufact Ingot ne mont Monthl ORE
Al O ST
Implementing the Lean Sigma framework in an Indian SME 413
time (CT), machine uptime (U/T), the number of shifts, 4.3. Analyse phase
the changeover time (C/O), and the percentage defect
Theobjectiveoftheteammemberswastodeterminethe
are listed. It should be noted that data are collected
rootcausesofdefectsandidentifythesignificantprocess
basedoninteractionswiththeworkersatdifferentwork
parameterscausingthedefect.Outofsixcastingdefects,
stations. During the development of these state maps
air inclusion, shrink holes, and gas holes porosity are
it was found that the defect rate was high and was
internal defects whereas cold shut, foliations, and
unacceptable.
soldering are surface defects. The internal defects are
formedduringthecastingprocessasthemetalsolidifies.
Themicroholescreatedinsidethecastingareduetoair
4.2. Measure phase or gas entrapment and result in crack propagation
due to differential pressure and force created inside
The team was divided into small groups to monitor
the casting. This crack propagation impedes the proper
the defects occurring in each process involved in the
functioning of the final product and thus is very
manufacturing of die-casting product. The team had
significant to overall performance of the machinery
been collecting data of defective products for the last
11 2 years and had identified the critical processes where where die-casting parts are fitted. The Pareto chart
0 showninfigure4illustratesthepercentagecontribution
2 maximum defects were occurring, but no action was
r of internal and external defects in the process. It can be
be taken. In order to validate the historic data, the team
m concludedfromtable1andfigure4thatinternaldefects
membersdecidedtocollectthedataofdefectiveproduct
e
v are the result of poor casting density and amounts to
o for the following 6 days of production from their
N 67% of total defects in the process. Other defects occur
5 respective work stations. The collected data was ana-
2 in the de-burring, chamfering and threading operations
9 lysed and it was found to match with the historic data,
5 due to tooling and clamping problems.
06: showing that the maximum numbers of defects were All the defects mentioned above decrease the sound-
at coming from the die-casting machine, de-burring oper- ness of the casting, i.e. decrease the density of the
] ation (MC2), and chamfering and threading operation
yde (MC3). casting. After conducting several brainstorming ses-
hcl The next step was to determine a performance sions, the team members concluded that the density of
rat standard based on customer requirements. A data the casting is the most important critical quality
St characteristic in the die-casting process as it was related
of collection plan was established to focus on the project to many internal defects (air entrapment, gas holes
y output and also to carry out the standard setting
sit exercise for the same. A Gauge repeatability and porosity, shrink holes, etc.). The objective of the die-
er casting process was to achieve ‘better casting density’
v reproducibility (R&R) study was conducted to identify
ni while minimising the effect of uncontrollable param-
U the sources of variation in the measurement system and
[ eters. To have a clear picture of the process parameters
y to determine whether it was accurate or not. A study
b
d was performed to check the accuracy of gauges used
e
d for the measurement of characteristics as well as the
a
nlo reproducibility of the worker in performing operations Pareto Chart for Internal and External Casting Defects
w on the machine. The Gauge R&R study performed on
Do the system showed a variation of 8.01%, which implied 100 100
thatthemeasurementsystemwasacceptable.Usinghigh
80 80
performance and accurate equipment, we were able to
secure the correct measurements of the die-casting
parameter values and react in time for the necessary unts 60 60 cent
correctiveactionsfortheexperimentalprocedure.What Co Per
40 40
the customers want is a sound casting with measurable
characteristics, such as the density of the casting.
20 20
Therefore the ultimate goal of the team was to increase
casting density.
0 0
Thecompanywasoperatingatabaselinecapabilityof Type of Defects Internal Defect Cold ShutFoliationSoldering Other Defects
Count 67 20 7 3 3
0.12withdefectsperunit(DPU)being0.18.Thedesired Percent 67.0 87.0 7.0 3.0 3.0
Cum% 67.0 20.0 94.0 97.0 100.0
specification limit of casting density was 2.73–2.78g/cc
and the casting produced before the implementation of
Figure 4. Pareto chart for the internal and external casting
Lean Sigma had an average density of 2.45g/cc. defects.
414 M. Kumar et al.
Table 1. Classificationof defects andtheir contribution to totaldefect.
Totaldefects from 5/01/04–10/01/04
De-burringunit—195 Chamfering andthreading unit—81
Casting—177(allcasting defects) Castingdefects—160 Other defects—35 Castingdefects—65 Other defects—16
Defects dueto poor casting—402(outof 523)
Internal defect External defect
Airinclusion 50 Cold shut 10
Shrinkholes 80 Foliations 20
Gas holes 130 Soldering 12
Porosity 90 Other defect 10
Total 350 52
Percentage ofinternal defect—67% oftotal defect
1
1
0
2
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e SHOT SLEEVE
v
o MACHINE
N
5
2
9 Filling timing
5
6: Length
0 Fast shot set point
] at Plunger velocity (2nd) Diameter
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cl Plunger velocity (1st) Filling level
h
at Pressure Lubricant
r
St Casting
f
o density
y Gate
rsit Lubricant Temperature
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ni Cooling system
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y [ Venting system Composition
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Figure 5. Cause andeffectdiagram.
affecting the density of casting, a ‘cause and effect’ At this stage, it was essential to identify significant
diagram was constructed and is shown in figure 5. parameters so that they are tuned properly to achieve
The cause and effect diagram shows that the most the desired range of casting density.
important process parameters that affect the casting
density are: piston velocity at first stage, piston velocity
at second stage, metal temperature, filling time and 4.4. Improve phase
hydraulic pressure. From experience, it was revealed
that non-linear behaviour of the parameters of the die- 4.4.1. Design ofexperiment. Intheimprovephase,the
castingprocesscanonlybedeterminedifmorethantwo team decided to carry out a designed experiment to
levelsareused.Theparametersalongwiththeirsettings identify the significant process parameters affecting the
are given in table 2. casting density. The most appropriate orthogonal array
Implementing the Lean Sigma framework in an Indian SME 415
Table 2. Process parameters withtheir rangesandvaluesat threelevels.
Parameter destination Process parameters Range Level 1 Level 2 Level 3
A Metal temperature((cid:2)C) 610–730 610 670 730
B Pistonvelocity 1ststage (m/s) 0.02–0.34 0.02 0.18 0.34
C Pistonvelocity 2ndstage (m/s) 1.2–3.8 1.2 2.5 3.8
D Filling time(ms) 40–130 40 85 130
E Hydraulicpressure (bar) 120–280 120 200 280
Table3. Results of L OA.
27
Trial no. A B C D E A(cid:3)B A(cid:3)C B(cid:3)C R1 R2 R3 Average S/N
1 1 1 1 1 1 1 1 1 2.336 2.338 2.441 2.372 7.500
2 1 1 2 2 2 1 2 2 2.339 2.442 2.447 2.409 7.637
1 3 1 1 3 3 3 1 3 3 2.442 2.505 2.448 2.465 7.839
1
0 4 1 2 1 2 2 2 1 2 2.427 2.444 2.416 2.429 7.713
2
r 5 1 2 2 3 3 2 2 3 2.545 2.577 2.595 2.572 8.210
e
b 6 1 2 3 1 1 2 3 1 2.435 2.336 2.374 2.382 7.538
m
e 7 1 3 1 3 3 3 1 3 2.716 2.728 2.701 2.715 8.680
v
o 8 1 3 2 1 1 3 2 1 2.346 2.429 2.392 2.389 7.566
N 9 1 3 3 2 2 3 3 2 2.439 2.442 2.445 2.442 7.759
5
2 10 2 1 1 2 3 2 2 1 2.445 2.501 2.487 2.478 7.884
9 11 2 1 2 3 1 2 3 2 2.439 2.441 2.398 2.426 7.701
5
6: 12 2 1 3 1 2 2 1 3 2.418 2.381 2.443 2.414 7.658
] at 0 1134 22 22 12 31 12 33 23 23 22..544529 22..541633 22..540445 22..542506 87..083018
de 15 2 2 3 2 3 3 1 1 2.543 2.585 2.591 2.573 8.212
cly 16 2 3 1 1 2 1 2 3 2.441 2.493 2.502 2.479 7.887
h 17 2 3 2 2 3 1 3 1 2.594 2.588 2.591 2.591 8.274
rat 18 2 3 3 3 1 1 1 2 2.539 2.542 2.545 2.542 8.108
St 19 3 1 1 3 2 3 3 1 2.474 2.495 2.489 2.486 7.914
f
o 20 3 1 2 1 3 3 1 2 2.603 2.595 2.588 2.595 8.288
y
rsit 2212 33 12 31 21 13 31 23 32 22..473084 22..467835 22..465922 22..465944 78..860131
e
v 23 3 2 2 2 1 1 1 3 2.640 2.682 2.654 2.659 8.497
Uni 24 3 2 3 3 2 1 2 1 2.703 2.698 2.691 2.697 8.623
y [ 25 3 3 1 2 1 2 3 3 2.671 2.679 2.685 2.678 8.562
b 26 3 3 2 3 2 2 1 1 2.726 2.717 2.720 2.721 8.699
ed 27 3 3 3 1 3 2 2 2 2.745 2.747 2.752 2.748 8.785
d
a
o
nl
w
o
D
(OA) design to meet the experimental requirement trial conditions. The average values of the S/N ratios
is a 27-trial experiment (L OA) and the exper- foreachparameteratdifferentlevelsforallthetrialsare
27
imental layout is depicted in table 3. The company listed in table 4 and plotted in figure 6. The influence
was initially operating with the following settings: of interactions on the casting density was negligible
A , B , C , D , E . based on the analysis and was thus omitted from
1 1 1 2 3
The casting density is a ‘larger the better’ type the table and figure.
of quality characteristic. Thus, the S/N ratio used is From figure 6, it is clear that casting density is at
given by: maximum when the process parameters A, B, D and E
are kept at level 3 and parameter C at level 1. Once the
" #
1Xn (cid:1)1(cid:2) optimum settings of process parameters were identified,
S=Nratio¼(cid:1)10 log ð1Þ
n y2 the team members decided to implement 5S system and
i¼1 i
totalproductivemaintenance(TPM)toestablishaclean
wherey isthecastingdensityforatrialcondition.Each environment within the shop floor and also to reduce
i
trail condition was repeated three times (i.e. n¼3). the idle time of machine and employees on the shop
The S/N ratios are computed for each of the 27 floor.