State of the Art - Precautionary Maintenace

7/30/2019 State of the Art - Precautionary Maintenace

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Precautionary maintenance

Stat e of th e Ar t

Javier Snchez Qu iros and Gerald Frank M ercieca

09 /11 /2012


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2 Precaut ionary maintenance - Design M ethods

1 Index

1 Ind ex ............................................................................................................................. 22 Figure s and Tables ......................................................................................................... 2

3 Abst ract ........................................................................................................................ 3

4 Intr od uctio n: an Overv iew of M aint enance ................................................................... 3

5 Stat e of t he Art on M aint enance ................................................................................... 4

5.1 Pred ict ive .............................................................................................................. 4

5.2 Proact ive ............................................................................................................... 6

5.3 Self -m aint enan ce ................................................................................................... 8

6 Com par ison s ............................................................................................................... 10

7 Conclu sion ................................................................................................................... 11

8 Refer en ce .................................................................................................................... 12

2 Figure s an d Tab les

Figure 1 - The developm ent of m aintenance t echnologies (M urt hy, et a l . , 2007) .. . .. . .. . .. . .. . .. . .. . .. . . 4

Figure 2 - Integrat ed system em ploying thr ee categories of techniq ues for p redict ive

m aintenance o f in dustr ia l sensors and equ ipm ent (Hashem ian & Bean, 2011) . . .. . .. . .. . .. . .. . .. . .. . .. . . 5

Figure 3 - Integrated system of pro act ive m aintenance (M uller, Suhner et a l . , 2008) . . .. . .. . .. . .. . .. . .. 7

Figur e 4 - Str uct ure of self-m aint enance system s (Wan g, Zhou et al., 201 0)................................. 9

Figur e 5 - The pr ocess of deve lop ing self-m aint enance (W ang, Zhou et al., 2010) ........................ 9

Figure 6 - Failur e Cur ves (Hashem ian & Bean, 201 1) .................................................................. 10

Table 1 - Act ion / Pol icy m aintenace types (personal com pilat ion based on the d ocum ent) .. . .. . . 11


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3 AbstractDuring the last decades maintenance has evolved from a simple part of product ion process

to an essent ia l strategic element with in a business. Organizat ions try to survive in a more

compet i t ive environment, in th is way processes and systems have became highly complex,

consequent ly new approaches for maintenances has been carr ied out in order to fu l f i l th is

need. The essay wi l l go th rough f rom a qu ick rev iew o f the more bas ic / t rad i t iona l

m ain tenance to a w ider exp lanat ion o f the s ta te o f t he ar t system s, the la test r esearch on th is

f ie ld and i ts conclusion. Final ly a comparison between the dif ferent types avai lable wi l l be

carr ied out in order to jus t i fy the n eed to keep invest iga t ing wi t h in th is area.

4 In t roduct ion: an O verview of M aintenanceTaking into account the importance of maintenance on business i t is assumed that the

cho ice o f the type o f main tenance is based not on techn ica l bu t techno-economic

considerat ion. Depending on the condit io n of the system dif f erent pol ic ies are appl ied. A

correct ive m ain tenance (CM ) is de f ined as the repara t ion or restor ing t ha t is done a f te r a

breakdown or fa i lure, that is, the act ion on th is pol icy is react ive. I t is stated to be a good

cho ice fo r system s wi th a constant f a i lu re ra te and a low breakdow n cost (M urthy, Kobbacy, &

Dawsonera , 2007), in v iew o f the fact tha t any o ther main tenance po l icy does not he lp toreduce the fa i lu re pr obab i l i ty . However, o ther p o l icies are app l ied to o ther system s, wh ere a

m easurable condit ion is avai lable to signal the p rob abi l i ty of a fa i lure and used to redu ce i t . It

is a lso imp ort ant to consider system s w here the fa i lure can lead to a dangerous situat ion or

disaster (H. W ang, 2002), wh ere in these cases a corr ect ive m aintenance is not a choice.

As i t is stated in th e previo us paragraph ot her kind s of m aintenance are essent ia l , these are

a l l embraced w i th t he nam e o f p recaut ionary m ain tenance (PM ) (M urthy, e t a l ., 2007), also

named prevent ive maintenance (Patton Joseph, 1983) depending on the author. PM act ions

are fa i r ly mo re com plex than the fo rm er. These cou ld be pr event ive , p red ic t ive , p roact ive or

passive and have one goal com m on, tha t o f reduc ing the fa i lu re probab i l i ty and/ or an t ic ipa t ingth e consequences of a fa i lure.

Prevent ive main tenance is based on act ions carr ied out in equ ipment a t p redetermined

in terva ls o f t im e, no t cons ider ing i ts cond i t ion or equ ipm ent s ta tus a t tha t t im e, in o ther w ay,

th e m aintenance act ions take place either in a certa in age T or in fa i lure w hichever occurs f i rst .

Accord ing to Hashemian & Bean (2011) i t is the m ost comm on m ain tenance po l icy , how ever

this technique is ineff ic ient and unrel iable: In 2007, Emerson/Rosemount Company publ ished

data on the per formance h is tory o f the i r p ressure , leve l , and f low t ransmit te rs in var ious

industr ies . The data showed that during periodic maintenance act ions, technicians found

t ransmit t e rs to be exper iencing no prob lems 70% of the t im e. By cont rast , in nuc lear pow er


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malfunct ioning of a system. This would result in a robust system that is consistent

(Chal i foux Alan, 1999; M arm ier, 2009).

Figure 3 Inte grated system of proactive maintena nce (M uller , Suhner et al . , 2008)

Case Stu dy: Qu ay cranes

Quay cranes are a good example where proact ive maintenance was brought into pract ice.

This is m ainly because in th is industry, i t is not only t im e that is very valuable, but th e parts to

replace or repair the cranes are very expensive. Up t i l l a couple of years ago, t radit ional

m aintenance m etho ds w ere used such as correct ive, scheduled and pr edict ive but as the w orld

became more indust r ia l ized and t ime even more va luab le , the need for be t te r mach ine

ef f ic iency was fe l t . A lso , wi th the use o f p roact ive main tenance, more l i fe t ime cou ld be

obta ined f rom the par ts and there fore i t wou ld be cheaper because the par ts wou ld be

changed just be fore fa i lu re and not a t a random t im e when they w ou ld s t i ll be qu i te good (as

the case in scheduled maintenance). This proact ive maintenance helps ident i fy ing the best

m aintenance procedur e as seen in th e graph below .(Lung, M orel, & Leger, 2003)

Figure 4 - Decreasing of fai lure rate (and coast) by m eans of proactive mainte nance (Lung, et al . , 200 3)


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5 .3 Sel f -maintenanceSelf maintenance systems are inspired by nature, how the b io logical immune

system works. The fact that the human body as a system can self mainta in when i t is

having problem s ( i llness) w ithou t t he need of m edic inal produ ct has led to an in t erest

in creat in g sm art system s that can self m ainta in. Due to t he ever increasing comp lexityof manufactur ing systems and processes i t is important to have a system that can

predict f a i lures and pr events such fa i lures so as to save t im e, mo ney and on t he ot her

hand, increasing safety and re l iab i l i ty . The tr adit ion al manuf actu r ing industry w orks on

a fa il and f ix system but w i th t he he lp o f these sta te o f the a r t system s, the t rend is

sh i f t ing to a p red ict and prevent system thanks to m odern t echno logy such as sm ar t

a lgor i th m s ( fuzzy logic, mat ch m atr ix , e tc) and ot her instrum ent s (sensors, cont ro l lers,

etc). This 4 t h genera t ion o f m a in tenance techno logy is a im ed in zero ing dow nt im e o f a

system , o r be t t e r , the a im is no t to avo id the fa i lu re o f a system but to avo id t he cost

o f b reakdow n, avo id t he t im e loss.

W hat self m aintenance does as a system integrated in a machine is th at i t m onit ors

i tse l f regular ly and when needed, repairs i tse l f by us ing spare parts that had been

already p laced in t he m achine as a sto ck. A s im ple example o f t h is could be a m i l l ing

m ach ine tha t changes i ts too l au tom at ica l ly w hen t he o lder too l is w orn ou t and hence

is tak ing longer for the same funct ion and g iv ing a worse surface f in ish. In th is way,

there is a drast ic decrease in down t ime of the machine and therefore the machine

would work even more eff ic ient. In general, se l f maintenance is a funct ional

maintenance type. This means that i t does maintenance by a l ter ing the or ig inalfunc t ion w i th o t her func t ions the m ach ine cou ld do bu t st i l l end ing up wi t h the sam e

f ina l p roduc t and a l lowing fo r the mach ine to keep work ing wi th what is func t ion ing

whi le at the same t ime f ix ing the fault . For th is to take p lace, the machine must be

smart, and therefore th is means that a sel f-mainta ined machine needs to have an

inbui l t reasoning system. This is d i f ferent to t radit ional maintenance because in

tradit ional, the machine is s topped and repairs or replacement of the faulty parts are

done w hi le the m achine is dow n (Lee, Ghaffar i , & Elmel igy, 2011 ).

In general, a sel f maintenance machine should be able to get the data from them achine ( ie observe how i t is wor k ing w ith t he use of h igh tec. sensors), th en i t should

be c lever enough t o spot t he faults in the system and c lassi fy them depend ing on w hat

type o f fau l t i t is . By th is , the mach ine wou ld know the cur ren t l i fe t ime le f t un t i l a

part icu lar fa i lure occurs and therefore i t can start p lanning the repair so as to avoid

downtime, and then, the execut ion of the repair procedure fo l lows (Lee, et a l . ) . Also,

th ese machines need to be self- learn ing so th at w hen faced wit h a problem t hat i t h ad

a lready encountered , it cou ld improve on th e m ethod i t had used to repa ir tha t fau l t

and be even mo re eff ic ient b y tak ing a short er t im e and obta in ing a bet ter f ina l result

(Labib, 2006).


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A dif ferent w ay that se lf m aintenance could be in t rodu ced in a m achine is by having

a m ach ine tha t w ou ld m on i to r i tse l f fo r any possib le fa ilu res tha t cou ld occur and then

imm ediate ly g ives a de ta iled repor t o f w hat is requ ired t o be don e or o f w hat is go ing

to fa i l or has a lready fa i led. In th is way, there would st i l l be the need of human

intervent ions but the cost would be decreased because there would be less t imeneeded to iden t i fy the p rob lem due t o i t be ing addressed be fore i t actua l ly crops ou t

(M .-H. W ang, Zhou, Chuan, & Zhao, 2010).

Figure 4 Structure of self -maintena nce system s (W ang, Zhou et al . , 2010 )

As seen in t he f igure abo ve, self m aintenance system s is sub divid ed int o th ree subsystem s.

This new technology of self maintenance could detect d if ferent kinds of fa i lures, (not only

mechanical faults as ment ioned previously) but a lso health management, data processing,

art i f ic ia l inte l l igence and network technology (both wireless and non-wireless). The most

im port ant part in self maint enance is the d etect io n system , th is needs to be as fast as possible

in gather ing in format ion about t he ent i re system at rea l t im e so th a t the ana lysis system cou ld

evaluate th e situat ion second by second (M .-H. Wang, et a l . , 2010). To do th is, advanced

integrated systems are used; these general ly are a number of sensors together with complex

a lgor i thms.

Figure 5 The process of developing self -maintena nce (W ang, Zhou e t al . , 201 0)

In the f igure above, the work f low of a self maintenance system is i l lustrated. A system is

rel iable i f each of i ts sub systems are rel iable, and therefore i t is of v i ta l importance that thesystem s that m ake up self m aintenance are consistent .


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Case Stu dy: Self-M ainta ined Robot ic System s

Due to self -maintenance being such a new technology, a concept of self -maintenance is

being presented. In th is case, a proposal of self maintained robot ic system is done. Currentrob ot ic system s w ork good as long as w hen th ere is a fault in t he system , hum an pow er is used

to repa i r /main ta in the system, but creat ing se l f main ta ined robots wou ld resu l t in a longer

l i fet ime for these systems. This could be done by creat ing a robot that adapts to the ever-

chang ing envi ronm ent surround ing i t and t he changes the happen w i th in th e same r obot due

to ag ing. Now a lo t o f R& D have al ready taken p lace on the adaptab i l i ty o f t he rob ot s change

in env i ronm ent , bu t l i t t le have been done on the changes w i th in the ro bot i tse l f .

Th is cou ld be done by teach ing the se l f m ain ta in ing robot to adapt i ts so f tw are depend ing

on w hat changes i t have in i ts hardw are (robot str uctu re in general). This is done by gatherin g

informat ion using highly advanced sensor systems and then behaving accordingly using i t sactuators. This could be do ne using com plex algori t hm s. (Sekiguchi, 2005)

6 ComparisonsAlthough Correct ive maintenance and Time-Based maintenance have been showed to not

be th e best opt ion they are st i l l th e norm in t radit ional industry. I llustrat ion 3 show s six fa ilure

models for any industr ia l equipment. According to Hashemian & Bean (2011) only 11% of

fa i lu res are determ ined by a cer ta in amount o f t im e, so a t im e based m ain tenance approach is

val id.

Figure 6 Failure Curves (Hashem ian & Bean, 2011)


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However, near ly 90% of fa i lu res are not re la ted wi th a per iod o f t ime work ing, bu t the

per iod o f a dev ice work ing is never f ixed and w i l l vary f rom one to another , depend ing on the

circum stances of using. In consequence, predict ive m aintenance or self -maint enance might be

th e best approach. W hiles predict ive m aintenance uses technolo gy to for ecast an imm inent

f law the decision and knowledge st i l l remains on the maintenance crew; in comparison in self -

m aintenance approach, the system takes the responsibi l i ty of decision w heth er carrying out an

act ion or no t .

Group Action Policy Description Focus on Degree ofdeve lopment

Drawback

Correct ive Correct ive

(CM)

Failure-

based (FBM )

Carr ied out only

af ter a breakdown

Fai lure old pract ice High

breakdownt i m e

Precaut ionary Prevent ive(PM)

Time/Used-based

(T/UBM)

Carr ied out af ter aspeci f ied amount of

t i m e

Time wel l developed,mo st appl ied

Inef f icient

State-of-

the-art

Predict ive

(PdM)

Condit ion-

based (CBM)

Car r ied out when a

given systemparameter exceedsa value

Mon i t o r i ng /

Sensors

developed/

increasingimplementat ionon market

High ini t ial

investment

Proact ive(PaM)

Design-out( DOM)

Improving of design M anagement/ De sign

develop ed Affect ing toall the aspecto f a

organizat ion

Self-

M aintenance

--- The m achine

decides when the

maintenanceoccurs

System

Intel l igence

on

development

I mmat ur e

technology

Table 1 Action / Policy maintenace types (personal compilat ion based on the d ocument)

Nonetheless, further research must be done to achieve the self -maintenance technology

and im plem ent i t in t he industry. On the ot her hand, m any case of studies and researches have

been found related to predict ive maintenance, since th is technology has became affordable

and the benef i ts just i fy th e cost and com plex i ty o f im p lement ing i t (M obley, 2002).

7 ConclusionAs one can conclude, m aintenance is an ever ending pro cess in industry and t herefo re a lot

must be done in th is sector so tha t th is area wou ld become more e f f ic ien t and hence more

pro f i tab le to a comp any. Impr ovem ents have been done in th is sector b u t m ore needs to be

done so as to a lways t ry to m axim ize the up t im e o f a system and hence decreasing the dow n

t im e of m achines. Latest techno logies (such as self m aintenance) m ight st i l l be to o r isky for a

company to imp lement them because they are very complex, expensive , and new, but as

fur ther research on opt imiz ing th is system is done, the main tenance sector wi l l soon be

sh i f t ing tow ards th is new techno logy.


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8 ReferenceChalifoux Alan, B. J. (1999). Rel iabi l i t y Centered M aintenan ce Guide: Operat ing a M ore

Ef fec t ive M aintenance Program. U SA.

Hashem ian, H. M ., & Bean, W . C. (2011). State-of -the-Art Predict ive M aintenance Techniqu es.Ieee Transact ions On Ins t rum entat ion And M easurement , 60(10).

Labib, A. W. (2006). Next Generat io n M aintenance System s: Toward s the Design of a Self-

m aintenance M achine (pp. 213-217). 4th IEEE Intern at ional Conference on Industr ia l

In format ics .Lee, J., Ghaff ari, M ., & Elm eligy (2011), S. Self- m aintenance and engineer ing im m une system s:

Towards smarter machines and manufacturing systems. Annual Reviews in Control ,

2011, Vol.35(1), pp.111-122, 35(1).

Liggan, P., & Lyon s, D. (2011). App lying Predictive M ainten ance Techniq ues to Ut il it y System s.Pharm aceut ical Engin eering, 31(6), 1-7.

Lung, B., M orel, G., & Leger, J. B. (2003). Proact ive m aintenance strategy f or harbou r crane

ope rat ion im provemen t . Robo t ica, 21 , 313-324 .M arm ier, F. (2009). Proact ive, dynamic and m ult i-cr i ter ia schedul ing of m aintenance act iv i t ies.Intern at ional Journ al of Product io n Research, 47(8), 2185-2201.

M obley, R. (2002). An int rod uct ion to predic t ive ma intenance [ Internet resource] . Am sterdam ;

New York: Amsterdam ; New York : But t e rw orth-He inem ann.

M uller, A., Suhner , M .-C., & Iung, B. (2008). Form alisat ion o f a new pro gnosis m odel for

support ing proact ive main tenance implementa t ion on indust r ia l system. Reliabil ity

Eng ineering and System Safet y, 93(2), 234-253 .

M ur th y, D. N. P., Kobbacy, K. A. H., & Daw sonera. (2007). Complex system maintenance

handbook . Berl in ; Londo n: Berl in ; Londo n : Springer.Patto n Joseph, D. (1983). Prevent ive m aintenance. Englew ood Cliffs, N.J: Englew ood Cliff s, N.J.

Prent ice-Hall for the Instrum ent Society of Am erica.

Sekiguchi, N. (2005). Learning of body sense and body image for mobile robot with visual

sensors. Advanced Int el l igent M echatr onics. Proceedings, 2005 IEEE/ ASM E

Internat ional Conference on;pp. 1269-1274.

W ang, H. (2002). A survey of m aintenance pol ic ies of det erior at ing system s. Europ ean Jour nal

of Op erat io nal Research, Vol.139(3), pp.469-48 9, 139(3).

W ang, M .-H., Zhou, D., Chu an, L. V., & Zhao, M . (2010). A discussion o f using self-m aint enance

technolo gy to achieve high rel iabi l i ty o f equip m ent. ( IEEE Com put er Society).

State of the Art - Precautionary Maintenace

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