8
292 HWAHAK KONGHAK Vol. 39, No. 3, June, 2001, pp. 292-299 (Journal of the Korean Institute of Chemical Engineers) HAZOP * * (2000 7 24 , 2001 3 20 ) Knowledge Framework and Algorithm for Automating HAZOP Analysis of Batch Processes Mi Young Noh, Ye Seung Lee, Bo Kyeng Hou, Dongil Shin* and Kyu Suk Hwang Dept. of Chem. Eng., Pusan National University, Pusan 609-735, Korea *School of Chemical Engineering, Seoul National University, Seoul 151-742, Korea (Received 24 July 2000; accepted 20 March 2001) time sequence HAZOP . , , , . HAZOP Latex . Abstract - The analysis of discrete variables such as time and sequence in batch process can not be explained by the method used in the HAZOP analysis of continuous processes. So in this study, we have classified the operation of batch processes into charge, reaction and discharge step, and have propagated the deviation by using propagation models of each unit. And we have developed the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables and continuous ones and then have discussed the performance of the methodology on a latex batch process to evaluate its effectiveness. Key words: HAZOP Analysis, Batch Process, Propagation Models E-mail: [email protected] 1. , HAZOP [1, 4, 12]. . Venkatasubramanian (petri net) (recipe) HAZOP . , HAZOP . charge step discharge step , reaction step HAZOP . 2. HAZOP 2-1. HAZOP . vessel vessel pipeline . step charge step, reaction step, discharge step (Table 1). Charge step discharge step . step step (pseudo continuity) step . reaction step task task

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Page 1: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

HWAHAK KONGHAK Vol. 39, No. 3, June, 2001, pp. 292-299(Journal of the Korean Institute of Chemical Engineers)

��� ��� HAZOP �� �� � ������ � ����

������������ *����†

����� �����*��� �����

(2000 7� 24� ��, 2001 3� 20� ��)

Knowledge Framework and Algorithm for Automating HAZOP Analysis of Batch Processes

Mi Young Noh, Ye Seung Lee, Bo Kyeng Hou, Dongil Shin* and Kyu Suk Hwang†

Dept. of Chem. Eng., Pusan National University, Pusan 609-735, Korea*School of Chemical Engineering, Seoul National University, Seoul 151-742, Korea

(Received 24 July 2000; accepted 20 March 2001)

� �

��� ��� time� sequence � �� ��� HAZOP � ���� ��� � ��. ��� � ����� �

�� ��� � , !", #$� % &' ()� ��* +, ,- . !" /��� 01� 2 34� 015678� 9:

;< 56=>�. ?@A 0B C�D� �� C�D� EF G�-)H AI* ��� ��� HAZOP �� J;� K�

� LM;< Latex NO ��� P:;< ? QRS� TU;V�.

Abstract − The analysis of discrete variables such as time and sequence in batch process can not be explained by the method

used in the HAZOP analysis of continuous processes. So in this study, we have classified the operation of batch processes into

charge, reaction and discharge step, and have propagated the deviation by using propagation models of each unit. And we have

developed the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables and

continuous ones and then have discussed the performance of the methodology on a latex batch process to evaluate its effectiveness.

Key words: HAZOP Analysis, Batch Process, Propagation Models

†E-mail: [email protected]

1. � �

��� ��� ��� � � ��� ���� ��� ����

�� � !��� "#��� $%& '( )* +, � !�& -

./ 01 234, 56 78 �� 39� :;< =* � !��

>? :@A BCDE�� F�G H@I7 27 GJ )K�� LM

>NOP� Q HAZOP �"� RS�& T? +U� V��7 2:

[1, 4, 12]. W XY� Z7 [\? �� �]� ^ _� `ab� [c

A�� dELe �f& >NO P� d^� g� �h� %f�i g

� jkl mn� op� ?:. Venkatasubramanian� qDr sD(petri

net)� tju(recipe)i v ]w� xO� vv yzL{ ��� ���

HAZOP� |�LM !}� �~L��� qDr sD� UOG [\

L7 ��:M ��� �37 2:.

'�� � +U&�M ��� ��� vv� ���� U�L{ �+

,O� X�? :�, ��bk� KTT�& 6�? G�%� !}�

GELM HAZOP �" %f� j��� U�L7R ?:. GJ >��

`� � �n�i �n�& ��LM charge stepl discharge step

� +, ���� �8L{ +, ��� �� G�%�}� AEL7,

reaction step� �+,O� 7.? �� G�%�}� �$L{ ���

��� HAZOP �" Y�� �jL7R ?:.

2. ��� � HAZOP ��

2-1. ���� ��

HAZOP �"� e�G �M �" �>M �7`a Q �lJ P�L

e >? �>]w Q �T�� �[� 5=�L{ �lA�� >NO

� P�  � 21¡ ¢��h ?:. � +U&�M G £¤  �

2M vessell vessel�G� pipeline� �"�>� L�:.

�+,Aa ^ xO� �37 2M ��� ��� v step� xO

l �"�>J 7.L{ charge step, reaction step, discharge step� ¥

���� U�L�:(Table 1). Charge stepl discharge step� �

�nl �n ����� ]wk� � GS4 ¦_  § ¨©G�

ª « �+,Aa p=� ¦_L3 ¬M:. G­? step&�M +, �

�& AEL�� G� %�}G AE�®? stepG¯� ��� �� °

#� +,(pseudo continuity) stepG�7 ��?:. ª­� reaction step

°&�M {­ taskbG +,A�� ����h L7 v task �� j&

292

Page 2: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

��� ��� HAZOP �� �� � ������ � ���� 293

,

±%R� ² d�� a? �7� $�  � 2�¯� d |���

step ° H ]wa ¨©e&� $�  � 2M �� �� G�l ¨©e

� H�]w ²dS�� a? �� �� G�� 7.�h ?:.

³? ¥ step k� �+,Aa G� %�J 7.Le >� charge step

l reaction step, reaction stepl discharge step �G� G� %�J ´

�)� |�L{ %��& µ¶ HAZOP �"� ��L7R ?:(Fig. 1).

2-2. �� �

G�� �OLe >��M �G·¸·(guidewords)i ����& T

? ��� opL:. �G·¸·M ����& AEL{ GK K¹J º

�»M ̀ aG �M ����� G�� UOLM No, More, Less, Reverse,

Other than, As well as, Part of ¼£�� vv& )? �½� Table 2i

¾:.

� +U&�M +,��(continuous variable)& AE �®? �G·¸

·i �+, ��(discontinuous variable)& AELM �G·¸·J U�

L{ ��L3 ¬M:. W, jk� 7.�h LM �+, ��& AEL

e >? �G·¸·�M No, Less, MoreJ ª)� �EL� LessM Early

� �½��, MoreM Late� �½�� ��?:. ¿J b� “Less Cooling-

start-time”� “Early Cooling-start-time”� �½�� cooling task� �� j

djkG �KAa �� jdjkÀ: ºÁ jdÂ� �Ã?:.

�� ��M �� ]wk� ÄÅxO� �Æ°M +,��i task&

TÇ�� 2M �+,��� U�  � 2:. +,��&M flow rate,

pressure, temperature, level, concentration� 2�È, �+,��&M �

�� ��&� �p? f�� a��M task ��j& �E�M start/

stop time ��� 2:. ¿J b�, Agitation-start-time(TAi)M ¨©e�

À ]wa agitator� djk� �ÃL7, “Less Agitation-start-time”

� “Early Agitation-start-time”�� agitator� d jkG �KAa

djkÀ: ºÁ jd�É:M G�� �Ã?:(Table 3).

3. �� � ��

� +U&�M �+,Aa xO� �37 2M ��� ��� HAZOP

�" RS�J >? %f� j�� U�Le >�� ʢ >NO P�

& op? 3�b� ��L7 GJ AËLÌ yzLMÍ op? 3�

Y�(knowledge model)� U�L�:. ��� ��� HAZOP RS�

j��� 3�ÎG�(knowledge base)M basic knowledge, unit knowledge

unit malfunction knowledge� �ÏAa U � �� 2:.

3-1. Basic knowledge

>NO P�� e�Aa ��J ÐÑL7 2M basic knowledgeM

guidewords, process variablesi definition of cause and consequence�

�Ò � 2:. ��� >Nl �7� `a Q �lJ ��Le >��

M Ê¢ ��� ��&� º�Ó � 2M �7� `al �l& T?

X�l KÔ +TT�� �ÕG opL:.

3-1-1. G� `a� 1�

G� `a� �� Q �> ]w&� $�  � 2M 5Ö� �×(root

malfunction)�� Fig. 2i ¾G G�G %��� e®GK(malfunction)

G� ����� G�� a? �7J #$jØ:.

]w� �T���� $� �®? GK� `a� £�A�� �jL

e >��M �G·¸·, ����, ]w� T�O& 6�? Y�� Ù

��h ?:. �" )Ka ]w��� GK `a� $ڠ � 7.�h

LM p=b�M :�l ¾� ÛG 2:.

(1) K�ÄÅ(upstream)& >w? ]w� <¤

(2) L�ÄÅ(downstream)& >w? ]w� <¤

(3) ]w&� $��� 8,Ü V��M rAa 7](rupture, blockage,

maintenance error, electrical failure)

(4) ]w&� $��� ��Ü V��M rAa GK(leak, gradual

Table 1. Step classification

StateStep

Charge Intermediate Reaction Intermediate Discharge

Pseudo continuity O ODiscontinuity O O O

Fig. 1. Overall propagation of deviation.

Table 2. Guidewords for HAZOP of batch process

Guidewords Description

No Negation of the design intentLess(Early) Quantitative decreaseMore(Late) Quantitative increaseReverse Local opposite of the intentOther than Complete substitutionAs well as Qualitative increasePart of Qualitative decrease

Table 3. Process variables of HAZOP in batch process

Process variables Symbol Description

Continuous variables Q Flow rateP PressureL LevelT TemperatureC Concentration

Discontinuous variables THi Heating-start-timeTHt Heating-stop-timeTCi Cooling-start-timeTCt Cooling-stop-timeTAi Agitate-start-timeTAt Agitate-stop-time

Fig. 2. Accident mechanism.

HWAHAK KONGHAK Vol. 39, No. 3, June, 2001

Page 3: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

294 ��������� !�"#�$%�

blockage, fouling)

(5) eÆ �Ý& >w? Þß� <¤(relief valve)

(6) «� zK(external heat source, external collision)

G­? `a� #1 l�&� %� l�� 1à `al 2à `a £�

� U�  � 2:.

(1) 1à `a: >NO �" �a ]w ° ����� G�

(2) 2à `a: 1à `a� hej»M ¥�Aa ]w� 7] Q ß�

K K¹ ]w

1à `al 2à `a 3�� Fig. 3l ¾:.

3-1-2. G� �l� 1�

G���� #1á � 2M �l� xO� �rLâ :�l ¾:.

(1) ]w°&� $��M �l

(2) K�ÄÅ& >w? ]w&�� �l

(3) L�ÄÅ& >w? ]w&�� �l

(4) eÆ �Ý&� $��M �l

GJ HAZOP� �Aa @Aa >N Q ^O f�� �"& T

�� ãÙ� 1à �li 2à �l� U�Lâ :�l ¾:.

(1) 1à �l: 2à �lJ #1jä � 2M More Temp., More Press.

å� ���� G�

(2) 2à �l: fire, explosion, toxic release, abnormal shutdown å

��l G�, ̀ a Q �lk� %£Aa �À%æ£�M Fig. 4i ¾

G ��  � 2:.

3-2. Unit knowledge

)K�]G �37 2M ��]wM vv� e®� �37 2� `L

M � çe >� è�� Ëà)� ����h ?:. G­? ��]

wb�M º¨A�� ¨©e, é¤ê, ëìíe ål ¾G ~% ]wJ

�«? )��� �>]wbG G& ���È, vessel, ëìíe, é¤ê

å� stationary equipmenti îïi ¾� rotating equipment� ð �3

� U�ñ:(Fig. 5).

��]wM 3� ÎG�� ò]O� À]L7 ¼£ 39A ï�ªó

ôG �®L1¡ ¼£ 39 ïtè(objected-oriented frame) U � �

� 2:. Gi ¾� ïtè U &� L�& >w? ïtè� K� ï

tè� xO(attribute)� ª)� K,I�È, op& '� K,I� x

O� õj�7 F�± xO� �{I� � 2�¯� 3�� ò] Q Ù

�� EGL:M ]�� �V:. ��]w� L�& >wLM v ¼£

(object)1 Rö� 7#? xO� � � 2:. v ïtè� e�÷

(default value)� vv� ��]w� �3M �K K¹÷G ø]�� 2

M ,O��� ÷� �Ã?:. GÛ� ��K¹� �Ka ùÊ, è��

GK�� $�  � 2M >NO� P�LMÍ 2�� �ER� v ,

O��& )L{ Yú �K K¹� ÷� �1� 3��h LM û��

ü� ý{HM �lJ �V:.

��]w� �ÝA�� �3M ,O���M service-flow, status,

failure-mode� 2:. {e�, service-flowM ��]w °�& ÄþM

GÈ, failure-modeM leak� rupturei ¾G e�A�� $�  � 2

M 7]� �Ã?:. Valvei ¾� stationary equipment&�� statusM

ÿ�� �/� #õJ �Æ°M ,O��G:. ¨â& Sn� �ELM

rotating equipment� statusM z_� ��]w� dSL7 2M3� {

�J �ưM ,O��G:. Rotating equipment� statusM power-onG�

M ÷G Öe��� 2:. GÛ� Sn� �ELM ]wbG �KAa

dSK¹&� �K SdL7 2e �fG:. ��]w� L� ¼£a

rotatingl stationary equipmentM flow, temperature, pressure ,O��

J �3Ì ñ:. Tank& ,LM ¼£M >i ¾� e�A ,O�� G

«&1 levell ¾� ,O��J �3Ì ñ:.

Fig. 3. The causal knowledge of the equipment.

Fig. 4. Overall architecture of automatic HAZOP analysis.

Fig. 5. Class hierarchy of units.

���� �39� �3� 2001� 6�

Page 4: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

��� ��� HAZOP �� �� � ������ � ���� 295

3-3. Unit malfunction knowledge

Unit malfunction knowledge&M ]w� GK& '( causei conse-

quencebG ���� 27 )K��� U i õTLÌ v ]w�� Y

���� 2� :�? ��& AE �®L:. ¿J b�, Fig. 6� îï

& )� ��Àâ, îï& ‘No flow’� G�� ̀ a� ‘No power’, ‘motor

failure’G7, ‘Less flow’i ‘No flow’M ‘pump cavitation’, ‘pump overheat’

� �lJ º�»M H`aG ñ:.

4. �� ��

)K ��� %£ taskJ charging, reaction, discharge step�� ¥�

�? , v stepl +T�� 2M +, ��i �+, ��J U�L{

G�� %�j»7 v ]wi d& �� $� �®? G�l +Tñ

+, ��� G�� %�jØ:.

4-1. � ��(pseudo continuity)

��� ��&� charge stepl discharge step� ]w� �/�nÐD

(port) Ý? ]w�G� GS4 ¦_  § ¨©G� ª « �+,Aa

p=� ¦_L3 ¬�¯� +, ��&�� G� %�}� AE  �

2�¯� G ��J #�+, ��� ��?:. '�� � +U&�M

�Ô #9ªóï&� 1�ñ %��� GEL{ ]wb �G� ���

�� G�� %�jØ:.

Charge/discharge step °&�M {­ �3� lineG ¦_  � 2

�� v � charge/discharge line °& ¦_LM �� UO ]wa

valve, pump åG �� #�L{ ]w� �[�M Û� e >� )y

Aa line4 7.?:(Fig. 7). ³? � xOK ±% � 7��7

� >NO, �$O, �O å� >NOG $�  �®OG 2M �

Charge/Discharge line& )��M xO libraryJ GEL{ ª >

NO� P�?:.

G�G %��M ��£& '� AE�M %��G ���MÍ

ÄÅ& �9� IM flow rate, level, pressure� G�� �3J �

L7, ]wb� ��â�� GSLM ë& �� �9� IM temperature

� G�� &�3 �3J � L{ �OAa %��(propagation equation)

� UO?:. ¿J b�, AE�M %��� Fig. 8l ¾�È, ª �ÃM

:�l ¾:.

(1) ��]w °� �1M ë*� �8LM #£� �1& ß�?:.

(2) #��M #£� �1M ��]w °� �1& ß�L7, ë*�

�8IM #£� �1& ß�?:.

(3) ��]w °� level� #��M #£� #,l #��M #£�

#,� à& ß�?:.

(4) #��M #£� #*� ��]w °� level, n, #��M #

£� #*& ß�?:.

(5) ��]w °� n� level, �1, #� #£� n& ß�?:.

(6) #��M #£� # � ��]w °� nl #��M #£�

n& �?:.

4-2. ����(discontinuity)

��� ��� x�a jk �½� �+,O� 7.L{ G�� %�

j»e >� � +U&�M :�l ¾� ��� 7.?:.

(1) Task ��j ±%R� ² d

(2) Reactor H� À ]w� 7] Q �Ñ

(3) Charge stepl reaction step k� �+,

(4) Reaction stepl discharge step k� �+,

4-2-1. Task ��j ±%R� ² d�� a? G� %�

Reaction step °&�� �+, ��� G�� task ��j& ±%R� ²

d�� $�LM Û�� jk �½� ��i guideword� c�� y

eLÈ, reaction step°� H ]wa ¨©e °&� $� �®? ��� G

�� table� �r? G­? ��� G���� :( ����� %G

�®? G�� �¹J database�?:. ¿J b�, 7�R �c���

reaction step °� o� taska agitate&� ² d�� a? G�� %� l

�� Àâ, :�l ¾:. {e�, TAiM agitation� jdLM time� �?:.

¿) No TAi(Agitating start time)

¿) � ¨©e ° More Temp. G� $�

Fig. 6. Unit malfunction knowledge for pump.

Fig. 7. The charge line of raw material.

Fig. 8. Propagation equations.

HWAHAK KONGHAK Vol. 39, No. 3, June, 2001

Page 5: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

296 ��������� !�"#�$%�

step

¿) � ¨©e ° More Press. G� %G

¿) � ¨©e ° �O More Conc.

¿) � More Temp.� a� Fire hazard $�

¿) Less(Early) TAi(Agitating start time)

¿) � ¨©e ° Less Temp. G� $�

¿) � ¨©e ° Less Press. G� %G

¿) � ¨©e ° �O Less Conc.

¿) More(Late) TAi(Agitating start time)

¿) � ¨©e ° More Temp. G� $�

¿) � ¨©e ° More Press. G� %G

¿) � ¨©e ° �O More Conc.

¿) � More Temp.� a� Fire hazard $�

���3� reaction step °� o� task�M 7� steamG� %e�

� #£J �ëj»M ��a heating taski coolant�� #£J cooling

j»M ��a cooling task� 2:. Gi ¾� task� �� �& dj

kl T�ñ ² d�� a� reactor °&� $� �®? �� ���

G�� $ël �먩& '� U�L{ table�Lâ Table 4i ¾:.

4-2-2. Reactor H� À ]w� 7] Q �Ñ& �? G� %�

Reaction step&� ¨©e °� ¨©G ~%LÌ ���7 �;� �

G `�LÌ �e >� ¨©e H�&M {­ À ]wbG ¦_?

:. ª Í G­? H� ]wb� e®G �)� ���3 ¬� �M �

K K¹� ¦_L� ¨©e °� ����b& G�G $�?:.

¿J b�, À ]wa cooling system� Àâ coolant tank, valve,

pump å :�? ]wbG ¦_LMÍ 4º G­? ]w �&� �!

L�� ]w& 7]G $�  ùÊ, ¨©e °� ����& G�G $

�?:(Fig. 9).

4-2-3. Charge stepl reaction step k� �+,O& �? G� %�

��� G� %�M ��Aa e®� LM ]w(cooling unit, heating

unit, agitation unit å)i TÇG "� ùÊ, Yú G�� `ó� G�

ª)� %�ñ:. ��� G� %�j v ��� KÔ T�& �� :

�l ¾� Ù#�   � 2:.

- � - : �®

+ � + : �®

+ � - : ��®

- � + : ��®

¿J b�, è�� ]w& ‘More Temp.’G� G�� %�jä ùÊ,

cooling task� ��� 7.L3 ¬�â :� ]w� ‘More Temp.’� ª

)� %�ñ:.

Charge stepl reaction step k� �+,Aa �� �� G� %�J

>� ]w �$� G� %�}� AEL{ charge step� �3 ]w

a pipe °� �� �� G�� reaction step� H ]wa ¨©e °�

Table 4. Deviation resulted from operator's maloperation

Reaction typeProcess variable(operating time)

GuidewordThe transition toward the process variable deviation in the reactor of the reaction

Temp. Press. Conc. Other

Exothermic TCi(cooling-start-time) LessMore

LessMore

LessMore

LessMore Fire

TCt(cooling-stop-time) LessMore

MoreLess

MoreLess

MoreLess

Fire

Endothermic THi(heating-start-time) LessMore

MoreLess

MoreLess

MoreLess

Fire

THt(heating-stop-time) LessMore

LessMore

LessMore

LessMore Fire

Fig. 9. Equipment malfunction(reaction step).

Table 5. The transition table of the process variable deviation between charge step and reaction step

The process variable in the pipe of the end of the charge line

GuidewordThe transition toward the process variable deviation in the reactor

Level Press. Temp. Conc.

Flow rate Hot material line NoLessMore

NoLessMore

LessLessMore

LessLessMore

NoLessMore

Cold material line NoLessMore

NoLessMore

LessLessMore

MoreMoreLess

NoLessMore

Temp.LessMore

LessMore

LessMore

LessMore

Conc.NoLessMore

LessLessMore

LessLessMore

NoLessMore

���� �39� �3� 2001� 6�

Page 6: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

��� ��� HAZOP �� �� � ������ � ���� 297

ral

al

e

�� �� G�� %�jØ:(Table 5). G� pipe� {­ ���� �&

� Q, T, C4� 7.L7, ¨©eM L, T, P, C4� 7.?:.

Table3&� ÀM Ûl ¾G ̈ ©e� %��M {­ �&� ßìA

7�� G 2M charge line °&� ‘More Flow rate’� G�G $� 

ùÊ, ̈ ©e °&M ‘More Level’� G�G $�LÌ �7 %£ ̈ © �

&� 7� � #,G �K #,À: Z¯� &�3 �3& �� ̈ ©

e °&M ‘More Temp.’� G�G $�L{ ̈ ©e ° �1M �K �1À

: &Ì á ÛG7, G� aL{ ‘More Press.’� G�G %G�Ì ñ:.

4-2-4. Reaction stepl discharge step k� �+,O& �? G� %�

'&� (8? charge stepl reaction step k� �+,Aa ��� G

� %�i ���3� reaction step&�� H ]wa ¨©ei TÇ 2

M ����(L, T, P, C) G�� discharge step°� ) ]wa pipei T

Ç 2M �� ��(Q, T, C) G�� %�jä � 2�È ª T�M Table

6l ¾:. ¿J b�, reaction step&� ¨©e°� ‘More Temp.’� G�

G $�  ùÊ, discharge step� ) ]wa pipe ° �O� �1M ‘More

Temp.’� G�G $�LÌ ñ:.

5. �� �� ��� ���

��� ��� HAZOP �" %f� j��� �$ @A� HAZOP

�"& T? ºÇ� l�� RS�L{ G�� `al �lJ �ER

&Ì �jLM ÛG:. W, ¢�ñ step, line, ]w&�� �* G�G

�ER& �� �n�â, ¢�ñ G�G :( ]w� %�ñ , Ù#

+V& �? �"� �, data-base��� 2M ]w� GK 3�l +

��� `al �l� 1�ñ:(Fig. 10).

j��� U M user interface, plant specific knowledge, plant gene

knowledge, HAZOP inference engine�� UO�� 2:(Fig. 11).

User interfaceM �ER� j��& -� �6LM ���� �ER

� L{. G�� ¢�L1¡ º�? frame� �jL7 ¢�ñ G�&

)? HAZOP �"� ��L{ Ù#ñ `al �lJ �ER&Ì �n

�HM / � ?:.

Knowledge baseM º¨Aa ��3�(plant general knowledge)l �

�� xO 3�(plant specific knowledge)�� �0� Tr��� :

( ��� AE& �Ê #EL:. º¨Aa ��3�� ]w�� �r

ñ º¨Aa GK 3�l ]w ,O 3�, `a/�l 12}, �G·¸

·, �� �� åG 27, ��� xO 3�&M O data, P&ID åG

2:. Knowledge baseJ º¨ 3�l xO 3��� �0� �rÑ�

�� TÇ 2M 3�4 ��, 3�, Ù�  � 2� j��G �Ê #+

� § 45� knowledge base� ZeJ ýº � 2:.

HAZOP inference engine� matching e}�� G�G $�? line�

X�L{ G�� %�jØ , if-then rule� �EL{ %�ñ G��

�"L7 ]w GK 3� �G�­ri )K ��� +� U J 7.

L{ �� G�& )? `al �lJ Ù#?:.

6. Case Study

� +U&� �ELM Latex � ��� z ^£&� �E�7 2

M %�Aa ��� ���� ±% 678& '� monomer Q chemical

b� reactor& charging? , ��� #� �c ¨©�� �;� �

?:(Fig. 12).

#� �c ̈ ©� styrene, butadiene å� monomer& #��, �c�

j�, %�, �R* Ë� å� %�L{ º�? �1 L&� º�

jk ì¨L{ #�j9 radical �c� LM !}G:. AN(acrylonitride),

ST(styrene), BD(butadiene)i ¾� monomerbl ª «� :�? che-

micalbG #� �c ¨©� >? b� GE�7, liquid NH3��

�1J ��?:. ̈ © ×�� �1M 85oC GL, n� 5.0 kg/cm2G

GL� #3��:h ?:.

Latex ��� ±%Ëà& '� monomer/chemical storage step, chemic

Table 6. The transition table of the process variable deviation between reaction step and discharge step

Process variable deviation in the reactor during reaction step

GuidewordThe transition toward the process variable deviation in the pipe of the end of the discharge lin

Flow Temp. Conc.

Level NoLessMore

NoLessMore

Press. LessMore

LessMore

LessMore

Temp. LessMore

LessMore

Conc. NoLessMore

NoLessMore

Fig. 10. Batch HAZOP analysis procedure.

Fig. 11. Basic architecture of the HAZOP System.

HWAHAK KONGHAK Vol. 39, No. 3, June, 2001

Page 7: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

298 ��������� !�"#�$%�

ep

preparation step, charge/polymerization step, monomer recovery step, latex

storage & ending step, finishing step� {; �� ���� UO��

2�È, � +U&�M charge/polymerization step �$�� �"� �

�  ÛG:.

Charging/polymerization step� ¥�A�� Àâ monomer/chemical

charging stepl reaction step�� U�ñ:. £¤� �®? vessel

l vessel k� pipeline� �"��� L{ v �"� °& ¦_LM è

�� ]w& �� �� G�� $�jØ , ÄÅ !9� +� ]

w� G�� %�j»7 v ]w&� $�? �� �� G�l ]wb

� unit malfunction knowledgeJ GEL{ 5< �lJ 1�?:.

Ê¢, +, �� flow ratei �G·¸· NoJ cL{ G� ‘No Flow

rate’J �OjØ:. GÛ� Fig. 12i ¾G reaction step&� ¨©e�

�1 ��& T? À taskJ ��LM line 7� �� ]wa pump p4-

1& AEjØ:. G�G $�? ]w� G� �lJ <e >� plant

generic knowledge �&� unit malfunction knowledgeJ GEL{ ‘No

Flow rate’� $� �®? �li ‘No Flow rate’J º�Ø `a� <7

G�G $�? ]w& )? G� $� `al �lJ �"? , :�

]wa pipe� G�� %�jØ:. G�� %�M propagation equation

� GEL{ pipe& $� �®? G�� Ù#L� pipei TÇ 2M �

� ��a flow rate, temperature, concentration �&� z_ 7. �a

�� flow ratei -� TÇG 2M �� ��a flow rate4 7.?:.

Propagation equation&� Qout = f(L, P, Qin)� GE  �, G�� $�

j9 �" �a L�� �� ��J �«? �=3 �� ��M �K

K¹J #3L¯� > propagation equation� ��a level, pressureM

G� %�j 7.L3 ¬M:. '�� �n�M �� �� flow rateM

�n�M �� �� flow rate& ���4 �9� I�¯� pipeJ ÝL

{ �n�M �� ��a flow rateM ª)� ‘No Flow rate’� G��

#3?:. G� line °� ��]wa control valveM �KA�� dS

?:7 ��?:.

¨©e� À systema cooling system °&�M ]w 7]G�

dR� ²dS å�� a? G�� $�jä � 2MÍ G­? G��

a� -�Aa �9� IM Û� reaction step °& 2M ¨©eG:.

Reaction step °� H ]wa ¨©e� K¹& -�Aa �9� ÃwM

��Aa task, ²dS, ªr7 ¨©e °� K¹ ��i� T�J Yú

ùÊ& '� table� ? , knowledge baseJ � L{ G�� �li

`a� 1�?:(Table 7).

�� ��� G�& �? Û §4 45� reaction step� cooling system

d �& ±%R� -�Aa d�� a? G�G 2� � 2:. ¿

J b�, �+, �� cooling-start-time(TCi)i �G·¸· Less(early)

� c�� G� ‘Less cooling-start-time’G $�  ùÊ, G� a� ̈

©e °� K¹ ��� %� �®? �� ��� G�� ‘Less Temp.’

GÈ, ³? ‘Less Temp.’� a� %G �®? �� �� G�� ‘Less

Press.’G:. G­? !}�� Ù#ñ �lM ]w� GK 3�� � L

{ G�� a? 5<Aa �lJ 1�?:(Fig. 13).

7. � �

��� ��� HAZOP �" l�� RS�Le >�� ¼£39 ï

tè e¨ U i X> e¨ %f�j��� Ù# !}� GE? 3�

e¨U J �$L{ �"& op? 3�� �?A�� yzL7 G�

� `al �lJ �ER&Ì �j� HM j��� U�L�:.

��� ��� HAZOP �"� +,� ��lM ær d jk, ´

� å& �? G�l ±%R� ² d& �? G�� 7.�h ñ:. W,

��� ��� Hp step� charging step, reaction step, discharging st

�� �¤  � 2:. {e�M � �/�n& T? charging step,

Fig. 12. Study process(Latex process).

Table 7. The causal table of the deviation(coolant in the reaction step)

Cause Deviation Consequence

Line pluggedpump stroke too shortvalve insufficiently opencoolant tank level lessoperator miss operator

No Flow rate More Temp.(in the reactor)More Press.(in the reactor)Less Product

Fig. 13. The study of the support equipment malfunction.

���� �39� �3� 2001� 6�

Page 8: HAZOP Knowledge Framework and Algorithm for · PDF filedeveloped the methodology for HAZOP analysis of batch processes by using the causal relationship between discrete variables

��� ��� HAZOP �� �� � ������ � ���� 299

discharging step� +, ��l Sº? propagation equation� �EL

{ G�� %�j9 �"L7, reaction step&�M ±%R� �+,A

d� 7.L{ v task �� j& $�LM ² dG� reactor� À

]w ° equipment� 7]�� a� $� �®? Yú +, �� G

�� ë�L{ table�? , charging step, discharging stepl ¾G +

,Aa â� 7.L{ ]wk� G�� %�jØ:.

G­? ��� HAZOP �" j��� Þ� l�&�� ~%O @A

Q Gà �E�7 2M ��� >NO �"& �E  � 2:. 9&

{­ �3� RS�j��l Plant SHEMAi ¾� e¦� +35��

ÍG� ÎG�i� �?A +�� GB�3â À: �C± ��� �

�� HAZOP �"G �®Lr�7 ��ñ:.

����

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HWAHAK KONGHAK Vol. 39, No. 3, June, 2001