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An Integrated Approach to TPM and Six Sigma Development in

the Castings Industry.

A.J. Thomasa, G.R. Jones

b, P. Vidales

c

aManufacturing Engineering Centre, Cardiff University, CF24 3AA, UK

bWall Colmonoy, Pontardawe, Swansea, SA1 3DEcEcole d'ingeniear CESI, France

Abstract

Both Total Productive Maintenance (TPM) and Six Sigma are key business process strategies which are

employed by companies to enhance their manufacturing performance. However, whilst there is significant research

information available on implementing these systems in a sequential manner, there is little information available

relating to the integration of these approaches to provide a single and highly effective strategy for change in

companies.

This paper proposes an integrated approach to TPM and Six Sigma which was developed as a result of workundertaken in the castings industry. The effectiveness of the approach is subsequently evaluated highlighting the

benefits the host organization received through this new approach by measuring the effects of implementation against

the seven Quality, Cost and Delivery (QCD) measures.

Keywords: TPM, DMAIC, QCD Measures

1. Introduction to TPM and the Six Sigma

Approach

Total Productive Maintenance (TPM) is a

maintenance program which employs a strategy for

maintaining plant and equipment to its optimum level

of operational effectiveness. Primarily the TPMapproach links into the Lean concept and aims at

reducing waste due to poorly maintained machinery

and provides for value added inputs by way ofensuring machinery remains in productive operation

for longer periods of time [1]. Maintenance procedures

and systems are designed so that they are easier to

accomplish and this is achieved through machine

redesign and modifications in order to facilitate this

process.

Six Sigmacan be considered both a business strategy

and a science that has the aim of reducing

manufacturing and service costs, and creating

significant improvements in customer satisfaction and

bottom-line savings through combining statistical and

Business Process methodologies into an integratedmodel of process, product and service improvement

[2].

Although both strategies have similar aims, those of

improving productive effectiveness, the way in which

these strategies are implemented into companies varies

greatly. Traditionally Six Sigma employs a structured

five-phased DMAIC methodology. Six Sigma teams

are created to tackle specific problems to reach Six

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Sigma levels of performance [2]. TPM implementationon the other hand is seen to be implemented in a range

of different ways, although attempts have been made to

formalise the TPM strategy [3], [4], [5], there is still no

formally defined approach that can be considered as an

industry standard approach to TPM implementation.

However, when considering TPM, it is worth notingthat the basic principles of the TPM strategy have very

close links to the Six Sigma approach. In TPM the

ultimate aim is to achieve significantly reduced

breakdown levels through developing autonomous

maintenance teams.

Employing therefore a standard operational framework

for implementing both approaches is seen as an

obvious and necessary step for companies to achieve

simultaneous benefits from the TPM and Six Sigma

strategies. To this end the DMAIC process is used as

the main operational approach for the implementation

of TPM. The following section highlights the

application of the DMAIC process in theimplementation of TPM in a castings company.

2. Introduction to Wall Colmonoy

Wall Colmonoy is a manufacturer of specialist

castings. The company is based in South Wales and

manufactures its products to a world wide market.

Over the years the company has experienced

increasing competition from the far-east where product

unit costs have been dramatically reduced. This has

brought about major changes to the company

operations and has raised the need for the company to

become leaner and more responsive to customers if

they are to remain as serious competitors in their

market.

Over the past two years the company has embarked on

a Lean manufacturing program. As part of the Lean

approach, TPM and Six Sigma are seen as essential

strategies for success. However, the company is

concerned that the separate implementation of such

approaches means the requirement of large scale

human, financial and technical resources as well as the

associated problems of running competing projects in

the company. The company requires a simple yet

effective operational framework that can be used as a

standard approach to adopting both strategies in thecompany. The company expects that worker buy in

will be easier if one common operational approach is

adopted

3. DMAIC at Wall Colmonoy

The Six Sigma strategy concentrates on a simple

five phase methodology called DMAIC. DMAIC is an

acronym of the major steps within the methodology

namely Define, Measure, Analyse, Improve, Control. It

was decided that the DMAIC process would form thebasic foundation for the TPM strategy and hence the

standard approach for adopting the major stages of the

TPM project. Each stage is explained in detail in the

following section of the paper.

3.1 Define

A benchmarking exercise was undertaken into the

major product lines operated by the company. The

product lines were benchmarked against on-time

delivery and right first time quality levels. A gauge

R+R study was undertaken in order to ensure that themeasuring equipment was suitable for measuring the

outgoing quality from the processes. From the analysis

of the key casting processes within the company, the

investment casting process was highlighted as the area

requiring greatest attention with scrap rates in excess

of 4% and on-time delivery at only 65%. The

definition stage triggered the development of a TPM

team within the company. This involved the training ofteam members in the principles of TPM as well as the

implementation of a 5S program* aimed at piloting

autonomous cleaning and teamworking prior to

specific and targeted TPM projects being undertaken

within the investment casting area.

3.2 Measure

Overall Equipment Effectiveness (OEE) was

calculated on each of the machines within the

investment casting area. Also, the company measured

parts throughput (parts per hour) through the cell in

order to identify whether the inefficiencies were due to

the machinery or to the operations surrounding the

machinery or both. As an example, OEE calculated for

one machine was calculated at 75% however partsthroughput in the cell where the machine operated in

was 43% less than the theoretical throughput for that

cell. Further analysis of the cell indicated that the

process surrounding the machine was at fault rather

than the machine itself.

One casting cell was measured as having a throughput

at 36% of its theoretical value and an OEE value of

30% for the wax making machine. A process mapping

exercise confirmed that the wax making machine was

the major cause of the low cell throughput and so thismachine became the focus of the remainder of the

project.

3.3 Analyse

The OEE value was split down to its constituent

parts namely; Availability, Performance and Quality.

* 5S A systematic process of workplace cleaning and

maintenance. Sort, Sanitize, Stabilize, Systematize, Sustain

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The results of this analysis showed that machineavailability was lowest at 34% compared to

performance at 94% and quality at 96%. This clearly

indicated that machine breakdowns and major stoppage

problems were the causal point for the poor OEEvalue. A Fault Tree Analysis (FTA) was therefore

carried out by a team of engineers from within thecompany in order to ascertain the root cause(s) of high

machinery failure. The FTA is shown in Fig 1 and lists

the failure routes identified from the brainstorming

session. Following the FTA, the engineering team

progressed to creating Failure Modes and Effects and

Criticality Analysis (FMECA) on each of the areasidentified from the failure routes on the FTA. The

FMECA allowed the company to identify the potential

causes of failure, assess its effect on the machine and

process and also, and most importantly, allow for

corrective actions to be identified. The engineering

team did not follow normal FMECA convention at this

stage and decided to employ individual FMECA sheets

for each potential failure mode. The benefit this gavethe team was that each sheet could be given to the

maintenance teams in turn in order to apply the

corrective action specified in the documents. In order

to prioritise the issuing of the FMECA sheets to the

maintenance teams, a Pareto analysis was constructed

of the Risk Priority Number (RPN) from each

FMECA study with the higher ranked RPNs being

tackled first.

3.4 Improve

Three levels of TPM were adopted in the

company in order to improve the machines reliability.

Level 1 was the introduction of shop floor autonomous

maintenance teams. These teams applied basic

maintenance practices including regular daily cleaningregimes as well as undertaking sensory maintenance

tasks (smell, sound, sight, feel etc). However, prior to

this level being undertaken, it was essential that major

machinery and equipment was completely overhauled

in order to revert the machinery to its original level of

reliability. This was considered to be Level 2 in the

TPM system and the work undertaken by the

maintenance department. Level 3 involved the

engineering department becoming more pro-active in

the development of preventive maintenance practices

including machine modification and enhancementstrategies that allow for easier maintenance etc. Level

3 work also included the monitoring of maintenance

FMECA An advanced planning technique aimed at

systematically assessing all the potential failures of a machine and

the potential impact (criticality) of the failure on a human and/or the

system.

RPN Risk Priority Number. A numerical method of analysing the

failure mode and its effect on the system. RPN = Severity x

Occurrence x Detection.

activities and concentrating primarily on approachestowards increasing Mean Time Between Failures

(MTBF) so that higher machine availability is

achieved. The aim here is to systematically extend the

mean time between failure so that the machinery can

remain productive for longer thus providing greater

return on machine performance. Table 1 shows thework undertaken at each level in the TPM system.

Table 1 TPM Levels and Work Definition

Levels of TPM Operation and Typical Activities

Level 1 Level 2 Level 3

Basic Cleaning Machine

overhaul

Machine

redesign

Machine care

plans

Major

Maintenance

MTBF analysis

& extension

Sensorymaintenance

Level 1Monitoring

Level 2Monitoring

3.5 Control

The work undertaken by the pilot TPM work wasmeasured for its effectiveness before being rolled out

through the company. Machine maintenance schedules

and plans were formalized and attached to each

machine. All operators were trained to undertake the

maintenance schedules and to report any issues to the

maintenance teams. As a control mechanism, it is the

responsibility of the maintenance department to

monitor the work of the operators and to rectify any

issues raised by the shop floor personnel.

The engineering department in turn monitored theoutputs from the maintenance department in order to

identify recurring failures and issues that could be

redesigned in order to prevent future failures. Theengineering team provided the technical and financial

support to the maintenance department in order to

facilitate the high level maintenance activities

undertaken at the level 2 stage. Fig 2 shows the

autonomous team approach at each of the TPM levels

in the organization and how each level integrate with

each other.

Fig 2 Autonomous Team Structure

TPM Autonomous teams

11

22

33

44

OperatorsOperators

Team LeaderTeam Leader

11

22

33

44

11

22

33

44

MaintenanceMaintenance

Team LeaderTeam Leader

EngineersEngineers

Team LeaderTeam Leader

Complexity of maintenance function- +

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4. Evaluation

As part of the companys approach to improving

their Quality, Cost and Delivery targets, i t was decided

to measure the QCD [6] outputs as a direct result of theTPM project. Table 2 shows the improvements made

in each QCD area.

In this case, the benefits gained from undertaking theTPM project may be considered idealistic when

comparing the large benefits gained from a relatively

small initial financial outlay. However, the costs

incurred in continuously controlling the input variables

and factors means that the monitoring costs can be

large and greater than first expected. This in turn can

affect the true savings achieved from the project. The

issue of cost analysis and control is as a key

consideration and its correct analysis and interpretation

is key to providing credibility to the TPM strategywithin the company.

5. Conclusions

A TPM pilot study was undertaken in order toimprove the Quality, Cost and Delivery measures

of the company. In all measures, the TPM project

achieved significant improvements.

This relatively simple application of TPM using astructured DMAIC technique should allow for

increased use of the methodology for tackling

many maintenance issues. Likewise, the results

can also provide the stimulus for the widerapplication of the technique to create process

improvements at relatively lower costs.

The application of the TPM approach to the waxmachine area at Wall Colmonoy achieved savings

in excess of 200,000 for an initial outlay of less

than 4,000 in experimental and project costs.

The development of the TPM approach developeda culture towards continuous improvement and the

systematic implementation of the system

throughout the organisation.

The application of the TPM approach allowed thecompany to develop advanced systems mapping

and analysis techniques and to become generally

more technical in their approach to problem

solving .

Acknowledgements

The authors would like to express their

appreciation to the following organisations for their

support during the development of the project and the

writing of this paper: Wall Colmonoy, I*PROMS,

Cardiff University Innovative Manufacturing Research

Centre.

References

[1] Jostes R S, Helms M M. Total Productive

Maintenance and Its Link to Total Quality

Management. Work Study Journal. (1994), 43,7.[2] Breyfogle, F.W. Implementing Six Sigma,

Smarter Solutions - Using Statistical Methods,

(1999).John Wiley & Sons Inc.

[3] Blanchard,B S.An enhanced approach for

implementing total productive maintenance in the

manufacturing environment, Journal of Quality in

Maintenance Engineering.(1997), 3,2.

[4] Jens,O, Riis J, Luxhj T, Thorsteinsson U. A

situational maintenance model

International Journal of Quality & ReliabilityManagement; (1997).14, 4.[5] Raouf A, Ben-Daya M. Total maintenance

management: a systematic approach,Journal of Quality in Maintenance Engineering;

(1995) 1,1.

[6] Achieving Best Practice in Your Business

QCD Measuring Manufacturing Performance.

Department of Trade and Industry Brochure,

www.dti.gov.uk.(2002).

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Fig1

AnFT

A

ofthepossiblefactorsinfluencingmachineperformance

Auto

WaxMachine1

OEE=35,5

%

SCRAP

BREAKDOWN

Partsinoil

Dipping

Parts

c

hipping

Parts

sticking

Air

entrapment

Fla

shing

Tool

jamming

Wiperarm

creeping

down

Injection

system

Hydraulic

pipes

bursting

No

regulators

Noset

variables

Wax

Temp

Back

plates

arentcold

Water

coolingnot

working

Leak

cooling

Par

tsfalling

one

achother

F

lushing

systemnot

w

orking

Pumps

notworking

S

ystem

b

locking

Water

contaminated

Tool

Sprue

T

emp

Control

Wipernot

long

enough

Patterns

notcool

Nozzle

design

Suckingin

air

Nozzle

temp

Spread

of

stirring

Seal

worn

Part

springing

Plate

cooling

Hold

time

Air

entrapment

Wear

onthe

tool

Brass

bush

wearing

Surface

Finish

Sprue

stuck

Ejector

pinsnaps

Nowax

Blockage

Waxblocked

infeedfrom

tank

Blockage

atnozzle

Stirrer

notlong

enough

Debris

intank

Temp

control

Poor

hou

sekeeping

Pouring

system

Nozzle

des

ign

Temp

control

at

nozzle

Water

heating

Handling

problem

Tool

condition

Storage

Dust

Sealsin

system

Oilin

water

AND

OR

LEGEND

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Table 2 Quality, Cost Delivery The Seven Measures

ie

60-30

30

5%1%

1% - 5%

5%

Improvement =

ie

Increase

Increase

i.e.

Increase

Number of planned deliveries - Number of not on time

deliveries

30,000 per employee

30,000

50,000 - 30,000Improvement =

Number of employees

30%

(Gross) Value Added

per Person

Basic Measure: / person Example of Improvement Measure

Previous StateOutput value - Input value New State 50,000 per employee

96% - 80%

80%

66% effective

66% - 30%

Value of (Raw material + WIP + Finished Goods)

Improvement =

Overall Equipment

Effectiveness

Basic Measure: % Example of Improvement Measure

Previous S tate 30% e ffective

i.e. Availability % x Perfomance % x Quality % New State

Improvement =

90%

Increase in Stock

Turns

Basic Measure: Number of turns Example of Improvement Measure

Previous S tate 4 S tock Turns

Sales turnover of product New State 5 Stock Turns

99% delivered on Time

Improvement = 99% - 90%

50,000 - 30,000=67%

30,000

On Time Delivery

Improvement

Basic Measure: % delivered correctly and on t ime Example of Improvement Measure

Previous State 90% del ivered on Time

New State

Number of not on time deliveries

People Productivity

Improvement

Improved Space

Utilisation

Basic Measure: per m2 Example of improvement measure

Previous S tate 30,000 per m2

Sales turnover of model area New State 50,000 per m2

Number of square metres of area

Scrap / Defect

Reduction

Basic Measure: % Example of Improvement Measure

Previous StateQuantity of defective units New State

Total quantity of units supplied Improvement =

Basic Measure: Units per direct operator hour Example of Improvement Measure

Previous S tate 30 Uni ts per Hour

Number if good units made New State 60 units per Hour

Number of direct operator hoursImprovement = 50%

i.e a 80%

reduction indefects (reported

as a positive

number

=10%

=20%

=120%

=67%