A Review of Optimization Models and Techniques for Maintenance Decision Support Systems in Small and Medium Industries.

?h*

T**

f&*K#s$#r

Pr*f,*edlnS$

tr

nte trz*t*,*n#*

C*r*ter

**#,* *n

r?"

*"Hru *ru##SYffit

{Ptrffi$trtr*}

H il

e

*tr*csl

**gin

e

*r*n#

&

ffi

f*rff!

n*4*x

Mrffiffiffiil

ffi

ffiffi

h{

*s{J

il

u

d*irz

L}*iv

*r*ity,

M***ss#r,

I

nd

*n

*si*

N*v*m**{

}3-}4,2***

ffr#ffinlxmd

by:gr

nr1

*****

2*#&

f,

*

trt

rffilffe*

"

$p$n$sred

hy:

?T.

FLru

t?ffrSf;ft#:

rT" &ttruAru&&.

geStHG

WILAY

hM

g#tSfrLRA*AR

SULAWTSI

Fuhlixh*d

by;

#epmrfruerrut

*f

#l**tr***t

*n#tffi

e*r*n#

F*##*tV

*f

ffiru#$m*erlng

ffi

*s*

n

arddtn

tJ

mfrv*r*ifg

MICEET

2OO8

COMMITTEE

III{TERNATIONAL AI}YISORY COMMITTEE

Chair

:

Muhammad

Arief

(Indonesia)

Mernbers

:

Dadang

suryamiharja

(Indonesia)

Keigo

Watanabe

(JaPan)

Azah Mohamed

(MalaYsia)

David

V. Thiel

(Australia)

Muharnmad

Tola

(Indonesia)

ME id Al-Dabbagh (Australia)

Josaphat

Tetuko

sri

sumantyo

(Japan)

Ivan

Azis

(Indonesia)

Harnzah

Berahim

(Indonesia)

IITTERITATIOI\AL PROGRAM

C

OMMITTEE

Chair

Mernbers

:

Salama

Manjang

(Indonesia)

:

Lukito

Edi I'{ugroho

(Indonesia)

Tumiran

(Indonesia)

Eniman

Syarnsuddin (Indonesia)

Hamzah

Hilal

(Indonesia)

Rhiza

S. Sadjad (Indonesia)

Syamsir

Abduh

(Indonesia)

ZUfajri

B.

Hasanuddin (Indonesia)

Mochamad

Anshari

(Indonesia)

Rafiuddin

SYam (Indonesia)

Anton

$atria Prabuwono

(Malaysia)

Elyas Palantei (Indonesia)

Armin

Lawi

(Indonesia)

ill

ORGANIZING COMMITTEE

General

Chair

Co-Chair

Secre

tariat

Chair

\fembers

Finance

Committee

Chair

\f

embers

Nadjamuddin Harun

Zahjr

Zairntddin

Yusri

Syam

Akil

Intan

Sari

Areni

Fitrianti

Mayasari

Sri

Mawar

Said

Ansar Suyuti

Zaenaf.

Muslimin

Mukhtar

Saleh

Tahir

Ali

Rachmat Santosa

Publication Committee

Chair

:

h{ernbers

:

Local Arrangements Committee

Chair

:

A.

Toyib

Raharjo

fuIembers

:

Indrabayu

Indrajaya

Joseph

Galla

Herman Rombe

Andani

Syafruddin

Syarif

Christoforus

Yohannes

Ingrid lrlurtanio

Dewiani

Gassing

Indar

Chaerah

Gunadin

Yusran

ill-"'*l*

ldn.

Bhd,

Lingkaran Teknokrat

Timur,

63000

cyberjaya,

selangor,

Malaysia;

-Faculty of

Engineering,

Multimedia University,

Malaysia)

l\z

-'l

j'ovel

Randorn

Frequency

Generator

Methodfor

Anti-Jamming

Communication

system,

Eko Patra

T.w.t,

Arwin

D.w.

sumaril2

{lDepartment

of

Electronics,

Indonesian

Air

Force Academy, Yogyakarta,

Indonesia;

2school

of

Electrical

Engineering

and

Informatics, Bandung Institute

of

Technology,

Bandung,

Indonesia)

125

Error

Performance

Analysis

of

Cooperative Relaying

Communications

with

Fixed

Gain and

csl-Assisted Relays,

sirmayanti

{The

state

polytechnic

of

ujung

Pandang)

l3o

i' tlrl*

--"*-L

:exsion

7.

Computer Engineering

& Informatics (CEI-2)

i

:

IEI

Designing

MultiAgent-based

Information

Fusio,n

System,

Arwin

Datumaya

Wahyudi

Sumarilz,

Adang

Suwandi Ahmad2

{lDepartment

of

Electronics,

Indonesian

Air

Force

Academy, Yogyakarta

-

.55002, Indonesia;

2School

of

Electrical Engineering

and

Informatics, Bandung Institute

of

Technology,

Bandung,Indonesia)

87

-r"'9CEI

Context-Based

Information Retrieval

of

Athtetic Sport

Management

System

(ASA[S),

Nuridawati

Mustafa, Muhammad

Haziq

Lim

Abdullah, Norazlin

Mohammed,

Nur

Filzah Zainan

{Faculty

of

lnformation and

Communication

Technology,

Universiti Teknikal

Malaysia Melaka, Locked

Bag

1200, Hang Tuah

1aya,75450

Ayer

Keroh, Melaka,

Malaysia)

144

''rt.rgp1

Preliminary

Analysts

of Dynamic Fleet

Management Support

System,

Abdulah

Fajar, Anton

Satria Prabuwono, Nanna Suryana

Heiman,

Zulkifli

Tahir

{Industrial Computing

Department,

Technical University Malaysia

Malacca,

Locked Bag

1200,

Ayer KerohTs4sa,

Malacca

Malaysia)

l4g

'r-iCEI

A

Review

of

Optimization

Models

and

Techniques

for

Maintenance

Decision

Support

Systems

in

Small and Medtum

Industries,

Zulkifli

Tahir, Anton

Satria

Prabuwono,

M.A.

Burhanuddin,

Habibullah

Akbar

{Industrial

Computing

Department,

Faculty

of

Information

and Communication Technology, Technical

University

of

Malaysia Melaka,Locked

Bag

1200,

Ayer Keron,li+SO

Melaka,

Malaysia)

₁₅₃

012CEI

A

Binary

Tree

Construction

from

Its Preorder and

Inorder

Traversals,

Armin

Lawi

{Department

of

Mathematics,

Faculty

of

Mathematics

and

Natural

Science,

Hasanuddin

University,

Indonesia)

fig

013CEI

Assessing e-Government

Security

Risk:

A

Preliminary

Study,Irfan

Syamsuddin

{'State

Polytechnic

of

Ujung

Pandang, Makassar, Indonesia;

2Techno-Management

,

Economics

and

Policy

Program, College

of

Engineering,

Seoul

National

University

South

Korea)

162

014CEI

ComponenbBased,

Automatic

HDL

and

C

Code

Generation

for

Control

System

Design

Using Metamodeling

Techniques,

Andreas

Voget

{Department

of

Electrical

Engineering,

Faculty of

Engineering, Hasanuddin

Univeisity,

Indonesia)

166

Ol 1CEI

ru)irffiiuLruiiii,ai: -,: : - resia November 13-14, 2008

e\\-

of Optimrzation Models

and

Techniques

\Iaintenance Decision

Support

Systems

in

Small

and

Medium Industriss

l-jir"ili

Tahir, Anton

Satria Prabuwono,

M.A.

Burhanuddin, Habibullah Akbar

Industrial

Computing Department

Facalty

of

Information

and Communication Technologt Technical University of Malaysia Melaka

Locked Bag 1200, Ayer Keroh,

7 5 4 5 0 Melalca, MalaYsia

:.:-i:iili

ra, antonsatria,

burhanuddin,

habibullah

ralOutem.edu.my

'xrusnrn&.ir"rth is based on the fact that decision support

[image:5.595.69.532.70.475.2]

n

meeded

for

maintenance process

in

commonly

irrr||luur:-

maintenance

functions

with

varieties

mnnuuris

nnd

techniques have been proposed

for

ilmffr',ffinil$trmk The

aim

of

this

r€search was

to

identify

n

models

and

techniques

to

conduct

;ru:xi"riinn

support

system

in

small and

medium

.,

A

s1 stematic

literature

revielv w&$ performed

r: ln-fCIrmation. The results shown several trends ffiffi "frrnr,'ts area. Next. the research direction has been

mp, *d'h-S rhe svstems.

I.

IxTRonUCTION

,'*r'*

',-

oi

maintenance

functions

for

maintenance

rnly

industries has gro\#ing

rapidly.

A

r-

:;':

end

publications

in

the field

rnaintenance *, _.,,1;

'-;

and

techniques

have

_be

en

published

to

:i'rru$

tf:,;:r\"eness of

maintenance process. As a part

of

_.,rnrrrlrr:r*i

for

maintenance

decision support

system

in

r,;;

_'r*rn industries.

we

need

to

collect the

related rrrl,

:

those areas.

The

specific objectives

on

this

""''i

:r:.:dbe

_{the classifications and}

available

_literafure

llulr

tir,r

field

of

rnaintenance

decision models

and

itlltl|llt":trfl* _ilL]es.

i, n: ,:,entif1 trends

in

the

field of

maintenance decision ilt;;:l;r]a S)'Stem.

'-

I

f:;ggest directions

for

future fesearches

in

this

field'

il.

ManqTENANCE TncnxIQUES

rilrmllitfi:inence

technique

is

the

procedure

that

used by

:

r

rnanagement

for

doing

their

rnaintenance

:rocess.

It

is

expected

that the most

appropriate

:.rn;e

strategy

(such

as

predictive,

preventive,

r,

i

,Jr

corrective)

can

be

determined. There are many iln;e techniquss have been introduced. References

[1]

;;ssified

various

maintenance techniques

from

54

papers

into

tsn areas maintenance techniques as shown in Fig.

1.

Fig. t Maintenance Techniques Classification [1]

Each

classification

and available literature

of

maintenance techniques has been described as

follow:

A)

Total

Productive Maintennnce

{TPM);

it is

the

rnaintenance

theory

which has

been introduced

by

Nakajima

[2]

that identified

rnaintenance

activities

as the

five

major pillars,

and then,

now

have improved become

eight

pillars,

consists

of

health and safefy, education and

training,

autonomous

maintenance,

planned preventive

maintenance,

quality

maintenance, focused irnprovement,

support

systerns,

and

initial

phase

managernent

(t3]-[ 1 5]).

B)

Reliahility

Centered Maintenance

(RCM):

A

set

of

tasks generated on the basis

of

a systematic evaluations that are

used

to

develop

or

optirnize &

maintenancs pfogfam.

RCM

incorporates

decision

logic to

ascertain

the

safety

and operational

consequsnces

of

failures and

identifies the rnechanism responsible

for

those failures

([16]-[21]).

C)

Preventive Maintennnce

(PM):

it is

an

important

rnaintenance

activity.

Within

a maintenance organization

it

usually

accounts

for

&

major

proportion

of

the

total

sTg- _{979-18765-0-6}

Proceedings of The I"u' Makassar Infemarional Cr:nference on

Elecmical Engineering and Informarics

Hasanuddin Universiry, Makassar, Indonesia November 13 "L4,2008

maintenancc

effort, PM

may be described as the care and

servicing

by

individual involved

with

maintenance to keep

equipment/facilities

in

satisfactory operational state

by

providing

for

semantic inspection, detection,

and

correction

of

incipient failures either

prior

to

their

occulrencs

or

prior

to

their

developrnent

into

rnajor

failure.

Some

of

the main

objectives

of

TpM

are

to:

enhance capital equipment

production

life,

reduce

critical

equipment breakdowns,

allow

better

planning

and

scheduling

of

needed

maintenance

work,

minimize

production losses due

to

equipment failures, and promote health and safety

of

maintenance personnel ([BJ,

[g],

lzzJ-[41]).

D)

Conditton Based Maintennnce

(CBM);

The

pM

service is based

on

some reading,

measurernent

going

beyond

a.

predetermined

limit.

If

the

machine cannot

hold

_a

tolerance? a

CBM

is

initialized (t12l-t4Sl)"

E)

Computerized

Maintenance

Managemerct

System

(CMMS);

it

is

one

of

a

computer softwars

program

that

designed

to

assist

in

the planning,

management, and

administrative

functions required

for

effective

maintenance.

These functions include

the

_generating,

planning, and reporting

of

work

orders

(wos);

the

developrnent

of

tracery

history;

and the recording

of

parts transactions _1491.

One

of

the

research

by

t50]

propose

decision making

grid

(DMG)

to

support

the

CMMS

applications ([5 1 _]-t571)

F)

Predictive Maintenence:

it

is consists in deciding whether or not to maintenance a systern according

to

its state

{[58],

tsel).

G)

Maintewtnce Outsourcing:

this

refers

to

transferring

workload

to

consider

with

the

goals

of

getring

higher

quality

maintenance

at

faster, safer and

lower

cost. The

others

goal are

to

reduce

the

number

of

full-tirne

equivalents

(FTEs)

and concentrate organization's talent, energy and rssources

in

to areas called core competencies (t601-t621)

H)

Effectiveness Centered

Maintenance (ECM).'

it

stresses

"doing

the

right things"

instead

of "doing

things right".

This

approach focuses

on

system

functions

and customer

service,

and has

several feafures

that are practical

to enhance

the performance

of

maintenance

practices

and encompasses cors concepts

of

quality

management,

TpM

and

RCM.

The

ECM

approach is more comprehensive as

compared

with

TPM

and

RCM,

It

is

composed

of

people

participation,

qualify

improvement,

and

maintenance

strategy development and performance rneasurement _[63].

il

Str*tegic Maintenance Managenxent (SMM).'

In

the

SMM

approach, maintenance

is

viewed

as

a

multi

disciplinary

activify.

This

approach overcome$

some

of

the

the

deficiencies

of RCM

and

TPM

approaches as these do not deal

with

issues

like

operating load on the equipment and ints effect on the degradation process, long term strategic issues and outsourcing

of

maintenance,

etc.

in

addition, these approaches

to

large extent are

qualitative or at

the

most

quantitative.

The SMM

aFpsd

more

quantitative,

involving the

rffi

models

that

integrate

technicim-operational aspects

from

business

ri

SMM

views

rnaintenance

from

&

broader than that of

RCM

and

TPM

_[6S$..

J)

rtrsfr Based

Maintenilnce (RBM).'

R.BM

maintenance strategy

meeting

the

ffi

minimization

of

hazard caused bv

equipment and a cost

effectiv.

,t*r*gy

itrm"

III"

MaTNTENANCE OprnrrzATTor

Maintenance

optimization

is

the

proces$

m

balance

of

maintenance requirement

snffi

n

economic, technical

or

others.

The

goels

b

appropriate maintenance technique

for

ililib

equipment

in

the

system

and identifying

ec Wfl

the maintenance technique should be conduc@d

best

requirement,

maintenance

target

s

equipment

reliability,

and

system

References _[ 1] have presented various resouruer fr

maintenance optimization models as shown in

fq:"

AHP MCDM Gailbraith

Organization Modeling MAIC

MILP

**tr

Fuzzy Linguistic

**,'&F _{Markovian Deterioration}

Fig. 2 Maintenance Optimization Classificariom l. j

Each

classification

and available literafure

of

optinrization models has been described as follow':

A)

Analytical Hierarchy

Process

(AHP):

it

was Thoma$

L.

Saaty

[66]

a$ mathematical

decisim

model

to

solve

complex

decision making pr

there are

multiple

objectives

or criteria

consic requires the decision makers

to

provide

jud

the

relative

importance

criterion

for

each alternative

([67],

_[68]).

B)

Adultiple

Criteria

Decision

Making (MCDM):

selecting between alternates

is

a relatively

c

often

difficult

task.

MCDM

refers

to

the

decision and planning

problerns

involving

m

generally collectittg

requirements.

The

Decisiom

(DM)

one

reasonable

alternative

from

among

r

available ones

{[69],

_[70]). **'ig" Fetrinet

'!r Bayesian

[image:6.595.312.564.95.589.2]

'

)'{akassar International Conference on

- ,nci informatics

""," )uiakassar, Indonesia November 13-14, 2008

The

theory

believes

that

'othe

greater

;

r*

-,

:

f

the task, the greater amount

of

information

:

i

processsd between

decision

makers during

i,,':i : - _-:t

r,l of

the

task

to

get

&

given level of

.**

-;'

Industries can reduce

uncertainfy

through

-:::rg

and coordination, often by rules, hierarchy,

,**"-r

Modeling:

References

[72]

reviews

*

:-

_r

i

organization

models,

s.g.

_advanced

l-:

:.;sical

rnodel

(ATM),

Eindhoven {Jniversity

of

::",

model(EuT),

total

quality

managemen!

,,

:

i,ai

;*d#;;fir-i;;#-

Crir'ajl[-r?-u'riir;

:

:, ;=':jrtf--jffH;,1?j-i,l'fu

.#

x-JTl

*

-

.

:

technology

(IT)

and

showed

that

integrated

'.'rrr"r'*'

'i

_{:,-r-planfling of production}

with

_maintenance,

Aet-erences

[73]

have

presented

a

krrowled"ge-::

::slurn support system,

MAIC for

maintenance

of

"* ,

-;"

nlant.

"n?et'

Linear

Programming

(MILP);

It

is

vsry

-

;rrnervork

for

capturing problems

with

both

1r

;

r,'cislons and continuous variable.

This

_includes

;:

*

;i:

problems,

control

of

hybrids

system,

:': ii,,

,:-affine (PWA)

_system

(including

_{approxirnation}

*

_:

rer

system),

and

problems

with

_non-convex

011CEI

of

events

A

and

B

both ocsurring

can

be

written

as the

probability of

A

occurring

multiplied by probability

of

B

occurring given that

A

has occulred

([82], t83l).

This

is

written

as:

P(A

and

B)

=P(A) P(B/A)

K)

Simulation:

t84l

and

tSsl

use the Monte Carlo simulation

to

determine optimum

maintenanc€

policy

and

for

modeling

on

continuously monitored

systems.

[86]

has

used simulation

model

to

reduce

maintenance

and

inventory

cost

for

a manufacturing system

with

stochastic

itern failure,

replacement

and order lead times.

[87]

demonstrates application

of

sirnulation models to evaluate maintenance

policies

for

an automated

production line in

a steel

rolling

mill.

IV.

TnnT{DS I nENI.TIFICATION

After a brief

description

of

classific,ation

in

rnaintenance

optimization models

and

techniques,

we

have

identified

several trends that related

in

the

field of

maintenance decision support systems, each of

which

have been described as

follow:

1)

From

all

described

publications, there

are

limited

models

have been

implemented

in

industrial maintenance process.

The

data problems and

the

gap between theories and practice have always become the reason.

2)

It

seems a

lot

of

maintenance optirnization models and techniques have been published

for

this

arsa. Various

simulating

tools

and

mathematical models have been attempted.

Although

the irnprovernent

of

IT

(both

soft

and

Hardware)

can

support

to

easy develop

of

the

system

with law

cost and

systematic

modules,

it

is

limited

work

has directed toward

developing

into

operational applications such as computerized system

or

DSS.

It

can

be said that the

impact

of

decision

making

within

a

maintenance organization has

so

far been

limited.

3)

Some

of

the publications have designed the integration

of

existing

maintenance

optirnization models

and

techniques such as

DMG, ECM, SMM

and

RBM. It

can be notice that a new potential research have existed

to

irnplement

them

in

the real

CMMS

or

DSS

applications.

4)

Much

design

of CMMSs

is as a device

for

analysis and

coordination

to

storehouse

the

maintenance

information,

such

as

a

PM

tool

and

a

maintenance

work

planning

tool.

However, less

of

them

have embedded

with

decision support modules

to be

linked

in

the actual industrial maintenance process.

V.

RESSnRCH

DmpcnoN

AND AcTIvITIES

The direction is highlighting

to

emerging trends

that

have

been

identified.

The

futures

researchers

can

conduct

the

maintenance

decision support system

with

consider

the

-:'-

:.

ii4).

lurff:

-

,::Ji

istic:

_Fuzzy

logic

_{was inhoduced}

by Dr

Lofti

,,,

'

:

-

UC/Berkeley

in

1960s

as

a

superset

of

:'

-. : _"lal

or

Boolean

logic

that has been extended to

,:r;

r

: -

i

concepts of partial truth

-

truth values between

-*'

:

r::1r,

trLle"

and

"completely

false".

It

was

llliiiur,-::,:"

r'-'irl t75]. By the

term

"fuzzinsss"

Zadeh meant

;ik:

:"!

in

which

there

is

no

sharp transition

from

lllilllllln:.T : :::f Ship 1767,

'

,,

, ;

it't

Deteriorntion: Markovian

deterioration

is

a

1rlffi ; r;i'r,l

i:ient

(t77]-tB0]).

ilp:.,;,"'" r

"' Petri nets,

it

is

one

of

sevsral

mathe matical

r

rrL,, I ,:.

-::lE

languages

for

the

description

of

discrete

*fi.: 'r* :'"-;ted

system.

A

Petri net

is

a

directed

bipartite

,4r:-;:::

in

which

the

nodes represent

transitions

(i,e. '.fi':,",.*-.i events

that may occur),

places

(i.e.

conditions),

luu

j

:-rected arch (that

describe

which

places are

prs

*

, ,K

l

:

:

post conditions

for which

transitionsxS l ].

J,;-

: - .

-ut:

Bayesian

statistic

is

based

on

Bayes'

rule

or

'rj*

* _:::ronal

probability,

It

is well

larown

_that

probability

0

"s " g7g .l 9765-0.6

Proceedings of The 1" Makassar Intemational conference on

Elecrical Engineering and Informarics

Hasanuddin university, Makassar, Indonesia November 13-14, z00B

finding

trends. The

following

step is suggested to conduct the systems.

I

)

choosing

the

rnaintennnce

techniqttes:

it is

_the

fundamental steps

that

we

must

concern

to

follow

in

industrial

maintenance process.

There

are

ten

techniques

that

we

can

choose

frorn

this

papers description. Each

of

thern have

specific

characteristic.

We

can

choose

the

most

_{appropriate techniques that}

can be irnplemented

in

the

real industrial

maintenance process.

2)

Data Analysis:

it

is

a fundamental issue

in

optirnizing

maintenance decision

making. The

decision

based

on incorrect

infonnation

may be useless or

harmful.

Some

times

data

is

seerns

to

be

plentiful, by

rnay

not be

of

quality of

the

quality

expected.

3)

Maintenance

information

system

interfuce:

one

of

popular interfaces

in

industries

is

CMMS.

It

is mainly

serves as databases. The rnaintenance data

in CMMS

is

the most

important information

to

help

maintenance

departrnent

rnaking

the right

decision

for

getting

the

right

maintenance strategies.

Fig.

3 is described

bf

tggl

as prototype to get decision out

from

maintenance data in CNTMS indusrries.

internal and

externat

data) and

knowledge qi.G"

and

explicit knowledge)

available

in

various the industries or its external environment. Donisi be conduct

from identify

the related data

with

decision making models.

'.\

VI. CoNCLUsIoNS

we

have

reported

the

ongoing

research project conduct maintenance decision support systems

for

rnedium industries. The research is develnped

with

id

the

appropriate

literature

from

published

mai

optirnization

_{models and techniques. Ttre results have}

the trends that related

in

the fields arsa. Irlext, those be

definitely giving

benefit

for

assist the ressarch

proplr

to develop the system.

ACKNOWLEDCMENT

The authors

would like

to thank Faculty of

Inforrnmi

Communication Technology,

Technical

Univensmy

Malaysia Melaka

for

providing facilities and Mrnisur

science, Technology and Innovation Malaysia

for

fr*il

support.

Employee $ki[s Data PM Inspe*tion Data Repairs Parts Data Vendor Data Labor Performance Data Time and Attendance Data

Job Estimating ,.-**-*;ts

Labor Utilization **---**,*.

Lebor Ferforrnance Overall Labor Productivity lnventory Control & Management Parts Availabitity Status Purchase Requistioning & Status Vendor Performsnce Evaluation Customer Serviees Analysis PM effectiveness

Maintenance Budget Data Customer Request & Complaints Equipment Priority Data Downtime Data Equipment Data Work Order Data

Work Order Status Work Order Coeting Work Order Prioritization Backfog Summary & Anatysis Equipment Downtime & Cause Anatysis Maintenance Budgets Variance Maintenance Budget Requirements Equipment Repair Procedures Planning & Scheduting Effectiveness Overall Maintenance Effectiveness

lll

t}J

REr.nnrNCES

A.

Garg and

s- G.

Desgmukh, "Application and ca-se

maintenance management: literafure review and directions," Jr

Qrtality in Maintenilnce Engineering, vol. 12, no. 3,2006.

s.

Nakajima, Introduction to TpM; Total productive Mai Productivity Press, USA, lggg.

.,,|-!q**-* t3l

l4l

lsl t6l t7] t8l tel

t i0l

[11j

I l2l

n3l

s.

Bonris, Total Productive Mai*tenance proven stratryw

techniqttes to k*rp equipment running at peak _fficiency, McGran

Journal of operation Management, vol. 19, no. l, pp.ig-ss,2c*.;_ F. Ireland and B. G. Dale, "study of total productive mainm

usA, 2006.

F.

K,

wang,

w-

Lee, "Learning curve anarysis in total p

maintenance," Ornega, vol. Zg, no. 6, pp. 49l-g, 2001.

K. E' McKone, R. G. schroeder, and K. o. cua, "The impac nff

productive maintenance practices on manufacturing perfor:nn

implementation," _{Journal of euatity in Maintendnce Engineemry,}

7, no. 3, pp. 183-g l, Z00l.

4)

;:;,'!.:l',r.-t.i.:,...:,:;.'-ii|- -+-i_]i1i+!-.::.::;

Fig. _{3 Maintenance Decisions Out} [gg]

Choosing

optimization

models".

rt

seems

a

lot

of

maintenance

optimization rnodels

with

various

simulating'tools

_{and mathematical rnodels}

have

_been

proposed

in

our

area. Choosing

the

right

one

that rnatch

with

our

data measurement

is

one step

to

do.

A

true

maintenance

optimization process

continually

monitors

and

optimizes

the

current

maintenancs

program

to

improve

its

overall efficiency

_and

effectiveness.

Decision

out:

In

the

process

of

decision

makiirg,

decision makers

combine

difrferent fypes

of

data

(i.;.

D.

Das, "Total predictive maintenance:

a

comprehensive &aCIs

achieving excellence in operational systems," Iniustrial Ensir,w

Jourrtal, vol. 30, no. 10, pp lS-23,2001.

D.

Gupta,

Y.

Gunalay, and

M. M.

srinivasan, '*The relati

befween preventive maintenance

and

manufacfuring r

performance'', European Journat of operational Research,

v&

no. l, pp. 146-62,2001.

R-

c.

Gupta, J. sonwalker, and

A.

K. chitale, *,overall equi

effectiveness through total productive maintenance", prestige

af Adanagement and Research, vol. 5, no. L, pp. 6t -7Z,Z0Al. R. Kodali, "Qualifieation

of

TpM benefits through AHp Prodactivity, vol. 42, no. Z, pp 265-73, 2001.

R. Kadali and s, chandra, o'Analytic hierarchy process of justil of total productive maintenance" _{, production ptanning and C}

vol. I 2, no. 7, pp, 693-705. 2001.

T.

Finlow-Bates,

B.

visser, and

c.

Finlow-Bates,

"An

inr

approach to problem solving: linking K-T, TeM, and RcA to

The TQIvI Magazine, vol. 12, no. 4, pp. 2&4-9,2000.

F. L.

cooke, "Implementing

TpM

in

plant maintenance:

organizational barriers," International

iournal

of

eualitT-Reliability Managemerxt, vol lT. no. g,Z0AA.

s)

MAINTENAHCE DATA IN

[image:8.595.56.345.87.735.2]

E

=imgs of The 1" Makassar International conference on

:i c"ai Engineering and Informarics

:.:llin

university, Makassar, Incionesia November 1i-14, z00B

Ol lCEI

K. _.E. McKone, R. G. Schroeder, and K. O. Cua, "Total

productive

[37]

K. K. Lai, F. K. N. Laung, B. Tao, and S.

y.

Wang, .,practices of

rBmtenance: a contextual view," Journal in Operations

Management,

preventive maintenance and replacement for engines: a case study,',

'o1 17, no' 2, pp'

12344,1999.

European Journal of operatioial Research, vol, 124, no. z, pp.

294-.{.

Shamsuddin,

M.

H. Hassan,

T.

Zahari, *TpM can go

beyond

fOO,}OOO.

malntenanc€: excerptfromcaseinplementation,"JournalofQuatityin

i38]

M.

Ben-Daya and

A.

S. Alghamdi, ..On an imperfect preventive I{aintendnce Engineertng, vol. I 1 No. l,pp. 19-42,

2005.

maintenance model," Internatianal Journal of

guitity &

Reliability

\

B. Bloorq Reliability Centered Maintenance implementation

made

Management, vol.. lT, no. 6, pp" 661-70, 2000.

|tlaile'

McGraw-HilI, UsA'

2006.

t39l

I-. gsu, 'simultaneous dete;ination of preventive maintenance and

H' ^{' Gabbar, H' Yamashita, K' Suzuki, and Y. Shimada,

"Computer-

replacement policies in a queue-like production system with minimal

aided-RCM-based plant maintenance management systenf',

robotte

rwaa," Reli;bility Engineiring and System Safety, vol. 63, 11o.2, pp.

11d _Computer-integrated Manufacnrin/, vol. 19, no. 5, pp.

449-5g,

l6l-7,1g99.

1003.

R..W.-.Wessels, _"Cost optimized schedule maintenance interval

for

system to prevantive maintenance interruptions," production plaqing reliability centered maintenance," Proceeding Annuat Reliability

and

ind Contrit,vol. 9, no.4, pp. 349-59, 199g.

rlainninabilitySvmposiumlEEE,pp.4l2-6.2003.

t41l

_{M. Gopalakrishnan,}

l.

_S.

inite,

_{and M. D. Miller, Maximizing the}

S'

Eisinger and

U. K.

Rakowsky, "Modeling

of

uncertainty

in

effectiveness

of a

preventive maintenance system:

an

adaptive

refiability centered maintenance- a probalistic approach,"

Reliabitity

modeling approach," 'Mooogement Science, vol. 43, no. 6,pp.827-ao,

Engineering nad System Safety, vol. 71. bo. z,pp.

159-64,2001.

lgg./.

L B.

Hipkins and

C.

D.

Cock, "TQM and BPR: Iessons

for

₁₄₂₁ A. Grall, L. Dieulle, C. Berenguer, and M. Rousignol, "Conrinous time

rnaintenancemanagement,"Omega,vol.28,no.3,pp.277-92,2000, _{predictive maintenance scheJuling for deteriorating system;" lAEd}

!1.

Rausand, "Reliability

centerd

maintenance,"

Retiabitity

Transaction on Reliability, vol. 51, no. 2,pp. 1trI-SO,1}OZ.

EngineeringandSystemSafety,vol.65,no.2,pp.llg-24,1998.

₁₄₃₎

D.

_{Chen and}

K.

_S.

i.in.di,

_{"Clo."d-form analytical resulrs for}

B. S' Dhillon, Enginering Maintenonce

A

Modern Approach,

CRC

condition-based maintenance," Retiability Engineiring ancl System Press LLC, Florida,

2002.

Safety, vo1.76, no. 1 , pp. 43_sl, 2002.

-i.. Chelbi, and D- Ait-Kadi, "Analysis

of

a

production/inventory

t44j M.

Marseguerra,

E.

Zio,

and

L.

Podofillini, "Condition based

slstem with randomly failing production unit submitted to

regular

maintenance optimization by means of genetic algorithms and Monte

preventive maintenance," European Jownal of Operational

Research,

Carlo simulation," Retiability Engineeriig and Syitem Safety, vol. 77,

lol.

156, pp.

712-9,20A4.

_{no. 2, pp. tSI-6s, 2002.}

A. Charles, L. Floru, C. Azzaro-Pantel, L. Pibouleau, and S. Dbmenech,

t45l

M. A" Jamali, D. Air-Kadi, R. Cleroux, antl A. Artibq "Joint optimal "'Optimization _{of preventive maintenance strategies in}

a

multipurpose

periodic and conditional maintenance strategy", Journal of

eaiw n

batch plant: application to semiconductor manufacturing,"

Computer

MaintenanceEngineering,vol.

ll,no.2,pp.

i07-14,2005:

-tnd Chemical Engineering, vol.27, no-4, pp.

449-67,2AC6.

_W6J H. Saranga and J" Knezevic, _{'Reliabiliry irediction} for condition-based

C.

H

Qian, L Kodo, and N. Thosio, "Optimal preventive

maintenance

maintained systems," Reliability Engineering and Systen Safety, vol. policies for a shock model with given damage level," Journal

of

71,no.2,pp.zl9-24,2001.

QuolityinMaintenanceEngineering,vol

.ll,

no.3,pp.216-27,2005.

l47l

F.

Barbeia,

H.

Scheneider, and

E.

watson,

.,A

condition based

C. Chen, Y' Chen, and J. Yuan, "On dynamic preventive

maintenance

maintenance model for a two-unit series system," Erupean Journal of policy for a system under inspection," Retiability Engineering

and

OperationalResearch,vol. ll6,no.2,pp.iAf-SO,

pel.

S;st_emsafetl' vol.76,no.

l,pp.41-7,20l3.

t48l

S. Luce, "Choice criteria

in

conclitional preventive maintenance,"

S. Bloch Mercier,

"A

preventive maintenance policy with

sequential

Mechanical Systems and Signal Processing, vol. 13, no. I, pp. 163-8,

:hecking procedure for a Markov deteriorating system,"

European

lggg.

JournalofoperationalResearch,vol142,no.3,pp.

548,2002.

t49l

_{K. Bagadia, Computerizecl Maintenance Managenrcnt Systems Mcrde}

S- Sheu, R. Yeh, Y. Lin, and M. Juang, "A Bayesian approach to

an

Easy" Mc.craw Hill, usA,2006.

adaptive preventive maintenance model," Reliability Engineering

and t50]

O. Femandes, A. W. Labib, R. Walmisley, and D. J- petty,.,A decision Sistem Sa"fety, vol. 71, no- 1, pp. 19-42,

2001.

support maintenance management system: development and

\t

Juang and

G'

Anderson,

"A

Bayesian method

on

adaptive

implementation," Internationil Journal

of

euality

Ai

arliobitity preventive maintenance problem," European Journal of

Operational

Management, vol. 20, no. 8, pp.965-79, 2001.

Research, vol. 155, no. 2, pp.

453-73,2004.

_t5

l]

_{J. B. Leger and C. Movel, "lniegration ofmaintenance in the enterprise:}

Y X

Zhao,"Onpreventivemaintenancepolicyofacriticalreliabilify

_{toward an enterprise modelirig based framework compliant with} level for system subject to degradation," Reliabitity Engineering

and

proactive maintenince strategy,';Production planning and

tontol,

vol.

S7 stem Safety, vol. 79, no. 3, pp. 301 -8,

2003.

tZ, no.2,pp. 176_g7, ZOO|.

F. C. Badia, M. D. Berrade, A. C. Clemente, "Optimal inspection

and

_tS2J T. Singer, ;Are you using all the features of your CMMS? Following preventive maintenance

of

units

with

revealed and

unrevealed

thisT-stepplancanhelpuncovernewbenefits," planEngineering,vol fulures," Reliability Engineering and System Safety, vol.78, no. 2,

pp.

53. no. l, pp 324,

lggi.

157'63'2002.

t53l A. W.

Labib, "world-class rnaintenance using

a

computerized

U. Gurler and A. Kaya, "A maintenance policy for a system with

multi-

maintenance management systert', Journat of _euality in Mointmance

state componentsi an approximate solution," Reliability

Engineering

Engineeing, vol. 4, no. 1, pp. 66-75, 1998.

andSystemSafety, vol.76,no. 2,pp.

117-27,29O2.

t54l L.

Swanson, "Computeriiid maintenance manag€menr sysrems: a

S. Motta'

D.

Brandao, and

E' A.

Colosimo, "Determination

of

study

of

syslem -<lesign and use", Produetion and Inventary preventive maintenance periodicities of standby devices,"

Reliability

ManagementJournal,vol.38,no.2,pp. ll-15,1997.

EngineeringandSystemSafety,

vo1.76,no.2,pp.149-54,2002. I55l

K.

_{Jones, and S. Collins, "Compuierized maintenance management}

\1. K.

Salameh and

R.

E..Ghattas, "Optimal just-in+ime

buffer

system",PropertyMenagement,rrol. 14,no.4,pp.33-7,1gg6.

in-ventorY for regular preventive maintenance," International

Journal t56] l.

_{F{. Wictrteri, 'Opt-i.;"ing maintenance'i.rnction}

by

_ensuring

o-fProduction Economics. vol.74, no. 1, pp.

157-61,2001.

effective managementofyouriomputerized maintenance *unugr-"nt 1'' Tsai, K. Wang, and H' Teng,."Optimizing preventive

maintenance

systems', I\EE , .frtcan bon|ermce (24-27 Septenber), Steltibusch,

for

mechanical components using genetic algorithms",

Retiability

usl,pp.Tgg-95,i996.

EngineeringandSystenSafety,vol.T4,no.

l,pp.89-97,2001..

t57l

M.

_{A.^Burhanuddin, "An Apptication of}

Decision Making Grid to

T'

Dohi'

N'

Kaio' and S. osaki, "Optimal periodic

maintenance

Improve Maintenance Strategiis

in

Small and Medium Industries,,,

sfategy under an intermittently used environment,, IEE

Transaction,

pioc. the /d

IEEE

Coiyer"rr"

on

Industial

Electronic &.

vol.33, no.

l2,pp.103746,2001.

_{Apptication,pp.}

455_60,2007.

?78-97?- l 9765.0-6

Proceedings of The 1" Makassar Inremational Conference on Elecuical _{Engineering and Informarics}

Hasanuddin Universiry, Makassar, Indonesia November 13,14, 2008

t58]

K. E. McKone and E,E Weiss, "Guidelines for implementing predictive maintenance", vol. I l, no, Z, pp. t0g-24,2002.

[59]

C. Clru, J. Proth, and P Wolff, "Preditive maintenance: the one-unit replacement model," fnturnational Journal of Production Economics,

vol. 54, no. 3, pp. 285-9j, 1998.

t60l

D.

N

Murthy and E. Asgharizadeh, "Optimal decision making in

maintenance service operation,'o European Journal

of

Operational

Research, vol. I16, no. 2, pp. Z5g-73, l ggg.

[61]

H. H. Martin, "Contracting out maintenance and a plan for future

research," _{Journal of Quality} in Maintenfrnce Engineering, vol. 3, no.2, pp. 8l-90, 1997.

162]

P. S. Buczkowski, M, E. Hrtmann, and V. G. Kulkami, "Outsourcing prioritized warranty repairs", International Journal

af fuality

& Reltability iufanagement, vol. ZZ,no. T, pp. 699-714, 2005.

[63]

K. Pun, K. chin, M. chow, and H,

i. w.

Law, "An

eft'ectiveness-centered approach to maintenanco management: a cass sfudy," Journal of Quality in maintenance Engineering, vol. 8, no. 4, pp. 346-69,2002.

[64] D. N. P.

Murthy,

A.

Atrens, and

J. A.

Eccleston, "strategic

maintenance managsment,"

Journal

quality in

Matntenance Engineering, vol. 8, no.4, pp.ZB7-305, Z}Aid.

[65] F. I.

Khan and

M. M.

Haddara, "Risk based maintenance: a

quantitative approach

for

maintenance/inspection scheduling and

planningn" Journal of Loss Prevention in the Process Industrres, vol.

16, no. 6, pp. 536-73, 2003

[66]

T. L. Saafy, The Analytic Hierarchy Process, McGraw-Hill, New York,

I 980.

t67l

M. Bevilacqua and M. Braglia, "The analytic hierarchy process applied

to maintenance strategy selection," Reliability Engineering and System

Safbty, vol. 70, no. l, pp. T1-83, 2000.

t68] A. W.

Labib, "World class maintenance using

a

computerized

maintenance management systemo', Joltrnal _{of Quality in} Maintenance Engineering, vol.4o no. l, pp. 66-?5, lg9B.

169l

B. Al-Najjar and I. Alsyouf, "selecting the most efficient maintenance approach using fuzzy multiple criteria decision making," International Journal of Production Economfcs, vol. 84, no. l, 85-100, 2003.

I70]

E. Triantaphyllou, B" Kovalerchuk, L. J. Mann, and G. M. Knapp,

"Determining the most important criteria

in

maintenance decision making" , Jottrnal af Quality in Maintenance Engineering, vo[. 3, no. l,

pp" l6-28, 1997.

[71] L.

Swanson,

"An

information processing rnodel

of

maintenance

management," International Journal of Production Econonucs, vol, 83,

no. l, pp. 45-64,2003.

l72l

D. Sherwin, "Review overall model for maintenance rnanagement",

Reliability Engineering and System safety, vol. 6, no. 4, pp. l jg-64,

2000.

[73]

C- Pieri, M.R Klein and M. Milaness, "A data and knowledge-based

system

for

supporting

the

maintenance

of

chemical plant," International Journal of Production Economlcs, vol. 79, no. 2, pp.

143-59,2002.

t741

H. D. Goel, J. Grievink, and M.p.C weijnen, "Intsgrated optimal

reliable design, production, and maintenancs planning for multipurpose

process plants", Computers & Chemieal Engineering, vofl-

fi*

pp. 1543-55,2003.

t75]

L. A. Zadeh, "Fu?&y Logic", IEEE Computer Society, VoI-

li-93,1988.

t76l

C.

K.

Mechefske and

Z.

Wang, "Using fuzzy lingusmic

n

optimum maintenance

and

condition monitoring Mechanical Systems and Signal Processing, val. 15, no. 6,

m-2001.

1771

[78]

lTel

180l

t8

ll

P. Bruns, "Optimal maintenance strategies for systems

st&

A. C. Marquez, A. S. Heguedas, "Models for maintenance

J. H"

Chiang, and

J.

Yuan, "Optimal maintenance

pory

Y.

Lam,

"An

optimal maintenance model

for

a

co

twodi vol. 77. m" repair options and without assuming bounded cosB',

f;q

Joarnal of Operational Researc&, vol. 139, no.l pp. 14G65.

W*

a study for repairable systems and finite time periods", Engineering and System Safety, vol. 75, no. 3, pp.367-77.

Markovian system under periodic inspection," Reliability

and System Safety, vol. 71, no. 2, pp. 165-72,2001. secondhand-new or outdated-updated system," European

Operational Research, vol. I 19, no. 3, pp. 739-52, 1999,

Z"

Rochdi,

B.

Driss, and

T.

Mohammed, "InternationaX

maintenance modeling using Petri nets", Retiability Enginffii

System Sofety, vol. 65, no. 2, pp. I 19-24, 1999.

182]

S, Apeland, and P. A. Scarf, "A fully subjectivc approach ts

inspection maintenance," European Journal of Operational

vol. 148, ilo. 2,pp.410-25,2003.

[83]

L, L. Ho and A, F. Silva, "Unbiased estimators for a systern

fu

time

to

failure and percentiles

in a

Weibull regression

International Journal of Quality & Reliability Management,

d-3, pp. 323-39,2006.

[84]

T. Chen, and E. Popova, "Maintenance policies with warranty," Reliability Engineering and System Safety,

6l-9,2002.

t85]

J. Barata, C. C. Soares,

M.

Marseguerra, and E. Zio, '"Si

modeling of repairable multi-component deteriorating systems

condition' maintenance optimization," Reliability Enginwiry

System Sofbty,voi. 76, no.3, 256-64,2002.

[86]

R. Sarker and

A.

Haqueo "optimization

of

maintenance mc.

provisioning policy using simulation," Applied Mathematical vol.24, no. 10, pp,751-60,2000.

[87]

N. T. Balakrishnan,

"A

simulation model for maintenance p

Proceetlings Annual Reliability and Maintainability Syntposh,tn

pp.109-l 8, 1992.

l88l

R. W. Peters, Maintenence Benchmarking and Best Pracriw,

Graw Hilt, USA, 20A6,

158