Hazard and Operability Study (HAZOP) Based RAMS Plus C Using

Genetic Algorithm Optimization in Heater Naphtha Hydro Treater,

Oil Refinery Unit, Cilacap Indonesia

Ali Musyafa

, Muhammad Khamim Asy’ari, Aulia Rizka Yoranda, Imam Abadi,

Harsono Hadi and Nur Alfiani Shoffiana

Department of Engineering Physics, Institute of Technology Sepuluh Nopember, Surabaya, 60111, Indonesia

Keywords: Charge Heater, HAZOP, LCC, PFD, Reboiler Heater, SIL.

Abstract: Naphtha Hydro Treater (NHT) Plant is a process to process heavy naphtha using the hydrotreating principle

so that it will produce sufficient naphtha to go to the next process. One of the equipment contained in the

NHT is a charge heater (82-F-201) and a reboiler heater (82-F-202). In carrying out the process, it is necessary

to have a good level of safety and to know the potential hazards contained in the plant. The results of research

conducted using the HAZOP method showed that 82-F-201 had a high-risk percentage of 27.7% while 82-F-

202 was 45.45% high risk. The safety instrumented system (SIS) in actual conditions for the 82-F-201 and

82-F-202 each has SIL 0. Whereas in the SIS design for the 82-F-201 and 82-F-202 the result is SIL 2. The

design LCC scores were obtained at USD 477370 for the 82-F-201 and USD 320430 for the 82-F-202. In

each section, the optimum type of technology used is technology A with a smart transmitter and air operated

valve. As well as the most optimum architecture vote using 1oo1.

1 INTRODUCTION

Energy consumption in Indonesia from year to year

has increased in line with the increasing economic

growth in Indonesia. The average increase in energy

demand each year is 36 million barrels of oil

equivalent (BOE) from 2000 to 2014 (Handbook of

Energy & Economic Statistics of Indonesia, 2015).

Thus the demand for oil and gas energy causes

companies engaged in the oil sector to produce oil

efficiently to meet domestic consumption. Currently,

a state-owned company engaged in the oil sector,

namely PT. Pertamina, which has seven processing

units, one of which is PT. Pertamina Refinery Unit

(RU) IV Cilacap. This company processes crude oil

into fuel oil (BBM), non-fuel oil, and petrochemicals.

In the process of processing crude oil into the

finished product has several stages, one of which is

the hydrotreating stage. This stage occurs in the

hydrotreating naphtha unit. Naphtha hydrotreating

unit is one of the processing units for heavy naphtha

products using a hydrogenation reaction that will

remove substances that can interfere with the

https://orcid.org/0000-0002-4474-6571

subsequent process (Anonim, 1989). Thus, you will

get naphtha that is suitable for further processing on

the platformer. Some of the equipment contained in

the NHT unit is not completely safe. Such as the

charge heater equipment (82-F-201) and reboiler

heater (82-F-202) which have a potential hazard. If a

process failure occurs it can cause flammable

materials (naphtha) has the potential to be released

into the environment. So that if there is a process

failure at a plant it will hamper the supply of fuel in a

certain area and become an economic loss for the

company. Therefore, it is necessary to conduct a

study to determine the potential hazards to the plant

so that it can be prevented. Hazard analysis can use

the HAZOP method. This method is an activity to

ascertain the potential hazards that may occur in the

factory (Kresna et al., 2017). A safety instrumented

system protection system needs to be done to avoid

potential hazards to instrument tools. In designing the

SIS, a safety integrity level (SIL) value is required

based on the IEC 61508 standard. Factors that

influence the SIS design are RAMS + C. RAMS

affects the level of user confidence in a system

represented by the PFDavg calculation. Whereas C is

Musyafa, A., Asy’ari, M., Yoranda, A., Abadi, I., Hadi, H. and Shofﬁana, N.

Hazard and Operability Study (HAZOP) Based RAMS Plus C Using Genetic Algorithm Optimization in Heater Naphtha Hydro Treater, Oil Reﬁnery Unit, Cilacap Indonesia.

DOI: 10.5220/0012112100003680

In Proceedings of the 4th International Conference on Advanced Engineering and Technology (ICATECH 2023), pages 129-138

ISBN: 978-989-758-663-7; ISSN: 2975-948X

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

129

the cost or total cost used in an SIS which is

represented by the LCC calculation. In the best

design,optimization is carried out on the objective

variables. The optimization used is a genetic

algorithm that draws on previously successful studies

(A.C. Torres-Echeverrı et al., 2009), (D. C.

Montgomery, 2009). By using this optimization, the

best optimization results will be obtained for each

variable. So, it is necessary to analyze the potential

hazards using the HAZOP method and evaluate the

safety instrumented system on the heater naphtha

hydro Treater at Refinery Unit IV Cilacap by

considering the reliability, safety and cost factors

using the RAMS + C calculation. The purpose of this

study, among others, is to analyze the potential

hazards that occur in the Charge Heater and Reboiler

Heater Naphtha Hydrotreater Unit at PT. Pertamina

(Persero) RU IV Cilacap using the Hazard and

Operability Study (HAZOP) Method, evaluating the

Safety Instrumented System (SIS) on the Charge

Heater and Reboiler Heater Naphtha Hydrotreater

Unit at PT. Pertamina (Persero) RU IV Cilacap,

Designing a Safety Instrumented System (SIS)

system based on the calculation method with

RAMS+C on the Charge Heater and Reboiler Heater

Naphtha Hydrotreater Unit, and optimizing the cost

of the Charge Heater and Reboiler Heater Naphtha

Hydrotreater Unit using a genetic algorithm at PT.

Pertamina (Persero) RU IV Cilacap.

2 RESEARCH METHODS

2.1 Data Collection

Data collection consists of PFD, P&ID, process data

that occurs in the unit, and data on maintenance or

failure of components as well as maintenance costs.

PFD and P&ID data are used to determine the process

at the plant in addition to determining the control

nodes and loops contained therein. Process data is

used to determine the deviation that occurs, and

maintenance data is used to determine the likelihood

value and severity value of a plant. Data obtained

from service data contained in the daily report charge

heater and reboiler heater located at the Naphtha

Hydrotreating Unit Paraxylene Refinery at PT.

Pertamina (Persero) RU IV Cilacap for 2005 to 2015.

Then the cost maintenance data is used to calculate

the LCC value used when optimizing costs using a

genetic algorithm optimization.

2.2 Hazard Analysis with HAZOP

Method Determine Control Nodes

and Loops

Table 1: Node determination.

Section No Node

Furnace 82-

F-201

Heavy Naptha from FOC II to

stripper column feed bottom

exchange 82-E-203 A/B/C

and to recycle compressor

section drum 82-V-203

include injection cold

condensate through 82-V-

201, 82-P-201 A/B, 82-E-201

A-H, 82-F-201, 8-R-201, 82-

E-202, 82-V-202, 82-P-205,

included make u

Fuel gas system from header

to 82-F-201

Fuel oil system from header

to 82-F-201

MP Steam from header to

atomizing 82-F-201

Furnace 82-

F-202

Feed naphta 82-C-201 to

reboiler bottom 82-C-201unit

platformer 84

Sweet naptha tank through

82-C-201, 82-F-202, 82-P-

202 A/B, 82-E-203 A-C

Fuel gas system from header

to 82-F-202

Fuel oil system from header

to 82-F-202

ICATECH 2023 - International Conference on Advanced Engineering and Technology

130

Table 2: Control on charge heater (82-F-201).

Node

Control-

Loo

Equipment Instrument

Flow

207

82-E-201 A-H

FIC-207

FT-207

FV-207

Pressure

223

82-V-202

PIC-223

PT-223

PV-223A/B

Level

201

82-V- 201

LIC-201

LT-201

FIC-201

FT-201

FV-201

Pressure

252

82-F-201

TIC-208

TT-208

PIC-252

PT-252

PV252

Pressure

251

82-F-201

TIC-208

TT-208

PIC-251

PT-251

PV-251

Pressure

249

82-F- 201

PDIC-249

PDT-249

PDV-249

FIC-207

Table 3: Nodes and Control on a Reboiler Heater (82-F-

202).

Node

Control-

Loo

Equipment Instrument

Flow

216 A

82-F-202

FIC-216 A

FT-216 A

FV-216 A

Flow

216 B

82-F-202

FIC-216 B

FT-216 B

FV-216 B

Pressure

265

82-F-202

PDIC-238

PDT-238

PIC-265

PT-265

PV-265

Pressure

264

82-F-202

PDIC-238

PDT-238

PIC-264

PT-264

PV-264

Pressure

262

82-F-202

PDIC-262

PDT-262

PDV-262

2.3 Determine the Guideword

After determining the control nodes and loops, the

next step is to determine the deviation that occurs in

each control loop based on the analysis of the process

data plotted on the control chart.

Table 4: Standard guideword.

Guidewor

Meanin

No (not, none)

There is no parameter

objective reache

More (more of)

Quantitative increments

aramete

Less (less of, lower)

Quantitative drop on

aramete

Guidewor

Meanin

As well as (more

than

)

Qualitative increase in

arameters

Part of

Qualitative drop on

aramete

Reverse

The inverse of parameter

oals

Other than (other)

Activity changes on

aramete

Deviation that occurs is determined by parameters

and guideword. Parameters are used to determine the

type of process variable while guideword is used to

determine the type of deviation that occurs in these

parameters (Anonim, 1998), (N. Hyatt, 2003),.

Parameters and guideword using HAZOP reference at

PT. Pertamina (Persero) RU IV Cilacap. The

following are the standard guidelines used by the

company (Pertamina, 2018).

Table 5: Standard guideword.

Paramete

Meaning

Flow

High; Low; None;

Reverse

Level Hi

h; Low; Em

Pressure High; Low

Temperature High; Low

Composition Change in concentration

In Table 4, it is known that there are 7 types of

guidelines used by companies in determining changes

that occur in parameters. Whereas in Table 5, there

are 5 kinds of process variables that become

parameters.

Hazard and Operability Study (HAZOP) Based RAMS Plus C Using Genetic Algorithm Optimization in Heater Naphtha Hydro Treater, Oil

Reﬁnery Unit, Cilacap Indonesia

131

2.4 Determine the Likelihood and

Severity Value

Each guideword has a value of severity or severity

and likelihood value or the chance of a plant failure

(ISA, 2002), (Goble, 2005), (Summers, 2010). The

value of severity and likelihood value is obtained

from estimation against reference. The following is a

table to find out the severity value.

Table 6: Severity value.

Level

Decision Issue

Economics Safet

Environment

Extreme Extensive

damage

Multiple

fatalities

Massive

effect

High Major

damage

Single

fatalit

Major effect

Medium Local damage Major

Local effect

Low Mirror

dama

Minor

Minor effect

1 Ne

ible No dama

eNo in

No effect

The likelihood value is obtained by estimating the

results of the likelihood calculation with the company

reference. The calculation formula to find out the

likelihood value is as follows.

𝐿𝑖𝑘𝑒𝑙𝑖ℎ𝑜𝑜𝑑 =

 



(1)

Time interval is obtained from the time between

the first failure and the last failure. Meanwhile, the

MTTF value is obtained from the average time to

failure (TTF) (Musyafa, R.D. Noriyanti, & Novan

Yudha, 2019), (Musyafa, R.D. Noriyanti, Azizatus, et

al., 2019), (Musyafa, Z.F., & Asy’ari, 2019). Where

the likelihood calculation above uses a time interval

of 131400.

2.5 Determine the Risk Ranking Value

The last step in making the HAZOP worksheet is

determining the risk ranking value for each

guideword in the instrument (Musyafa et al., 2015).

Determination of risk ranking is obtained in the

following way.

𝑅𝑖𝑠𝑘 𝑅𝑎𝑛𝑘𝑖𝑛𝑔 = 𝐿𝑖𝑘𝑒𝑙𝑖ℎ𝑜𝑜𝑑 × 𝑆𝑒𝑣𝑒𝑟𝑖𝑡𝑦

(2)

The multiplication of likelihood and severity will

be included in the standard PT risk matrix criteria.

Pertamina (Persero) RU IV Cilacap. This criterion is

used to determine risk categories that are high,

moderate, or low. The following is a risk matrix

category based on company standards.

Table 7: Risk ranking criteria.

Likeliho

Severit

(Sm

all)

(Mi

nor)

(Mode

rate)

(Majo

(Ma

ssive)

(

)

L MH H E E

(mediu

L M MH H E

(

low

)

N L M MH H

(Negligi

)

N N L M MH

Note : E = Extreme Risk; H = High Risk; MH = Moderate

High Risk; M = Moderate Risk; L = Low Risk; N = Normal

Risk

Based on the multiplication of the likelihood

value with severity using the risk matrix criteria, the

results of the risk ranking guideword on the deviation

of each instrument are as follows Table 8.

Table 8: Determination of risk ranking.

Section

Instru

ment

Guideword L S RR

82-F-

201

FT-

207

High Flow C 1 L

Low Flow C 3 MH

PT-

223

High Pressure C 3

Low Pressure C 4 H

LT-

201

High Level C 4

Low Level C 4 H

FT-

201

High Flow C 3

Low Flow C 3 MH

LT-

206

High Level B 1

Low Level B 1 N

TT-

208

High C 2

Temperature C 2 M

ICATECH 2023 - International Conference on Advanced Engineering and Technology

132

Table 8: Determination of risk ranking(continued).

Section

Instru

ment

Guideword L S

82-F-

201

PT-

252

Low B 3 M

Temperature B 3 M

PT-

251

High Pressure C 3

Low Pressure C 3 MH

PDT-

249

High Pressure C 4

Low Pressure C 4 H

82-F-

202

FT-

216A

High Pressure C 3

Low Pressure C 3 MH

FT-

216B

High Pressure C 4

Low Pressure C 4 H

PDT-

238

High Flow D 3

Low Flow D 3 H

PT-

265

High Flow D 3 H

Low Flow D 3 H

PT-

264

High Pressure C 2

Low Pressure C 2 M

PDT-

262

High Pressure C 3

The potential danger that occurs in the Charge

Heater (82-F-201) has a percentage of 27.7% high

risk, 33.3% medium high risk, 22.3% medium risk,

5.5% low risk and 11.2% normal . In addition, the

percentage of potential hazards that occur in the

Reboiler Heater (82-F-202) is 45.45% high risk,

36.36% high risk medium and 18.19% medium risk.

2.6 Genetic Algorithm Optimization

The determination of the objective function in this

case is the life cycle cost (LCC) to a minimum. On

optimization variables that affect the value of life

cycle cost namely PFDavg, type of technology and

architecture vote from such control. There are several

properties needed for optimization, as follows:

• The number of populations is used to determine

the number of chromosomes involved in the

optimization process. The number of population

used is 50.

• The number of variables that are optimized is

three which will affect the objective function,

namely PFDavg, type of technology, and

architectural vote.

• The optimized upper and lower bounds are

intended as a range to randomize the value of the

optimization variable so that it fulfills the

objective function.

• Iteration is the number of generations that occur

in each individual by determining the rotation of

the optimization process. Variations to be used

between 100 and 250 for best results.

3 RESULT AND DISCUSSION

3.1 Potential Hazard Analysis with

HAZOP

At node 1 for the FT-207 tag instrument, high flow

and low flow deviations occur. The high flow

condition is caused by the failure of the full opening

of the FV-207 resulting in a low temperature at R-

201, thus no desulphurization process occurs in the

reactor which will cause unsolicited product results.

Meanwhile, the low flow condition was caused by the

FV-207 not opening as desired which resulted in

damage to the pump. In PT-223 there is a deviation of

high pressure and low pressure. The high pressure

condition occurs when the full opening failure of the

PV-223B and PV-223A will result in an increase in

the consumption of hydrogen make up respectively

and the potential for leakage on the V-202 which will

cause an explosion. Meanwhile, the low pressure

condition occurs when the PV-223A does not open

according to demand. This results in low pressure on

the R-201, thereby reducing the quality of the

product. For LT-201 there is a high level deviation

and a low level. In high level conditions it is caused

by malfunctioning full openings on the FV-201 which

results in an increase in pressure on the V-201.

Whereas in low level conditions it is due to failure to

close FV-201 which results in potential cavitation on

P-201. In FT-201 there is a deviation of high flow and

low flow. In high flow conditions it is caused by

malfunctioning full openings at FV-201, causing

liquid naphtha to be carried over to KOD which

causes losses down grade naphtha slope. Meanwhile,

the low flow condition is caused by the opening of the

Hazard and Operability Study (HAZOP) Based RAMS Plus C Using Genetic Algorithm Optimization in Heater Naphtha Hydro Treater, Oil

Reﬁnery Unit, Cilacap Indonesia

133

FV-201 not according to demand, which causes a low

altitude on the V-201 which will cause cavitation on

the P-201. Meanwhile, for LT-206 there is a high

level deviation and a low level deviation. In low level

conditions it is due to failure to open the LV-206

which results in reduced naphtha product.

Meanwhile, the high level condition was caused by

the failure to close on the LV-206 which resulted in

the naphtha hydrocarbon liquid being carried to the

KOD so that the compressor was damaged.

Node 2 for the instrument On the TT-208 there is

a deviation in the form of high temperature and low

temperature. The high temperature condition was

caused by the opening of steam traces which resulted

in an increase in COT 82-F-201. Meanwhile, the low

temperature condition was caused by the failure of the

steam trace which resulted in incomplete combustion

at a potential reduction in COT at 82-F-201. At PT-

252.

There is a deviation of high pressure and low

pressure. The high pressure was caused by failed

close valve PV-252 so that it could cause an

explosion. While the deviation for low pressure is due

to the valve opening of the PV-252 not being as

desired. This resulted in a lack of supply of fuel gas

flow to the F-201 which resulted in no hydrotreating

reaction.

At node 3 for the TT-208 instrument, high

temperature and low temperature deviations occur.

The high temperature condition was caused by the

opening of steam traces which resulted in an increase

in COT 82-F-201. Meanwhile, in low temperature

conditions due to failure of the steam trace. This

failure resulted in the oil drip on the F-201 fuel oil

burner tips causing unsafe conditions. Meanwhile,

PT-251 had a deviation in high pressure and low

pressure. The high pressure condition was caused by

failed close valve PV-251 so that it could cause an

explosion. The low pressure condition occurred due

to the FV-251 not opening as desired, resulting in an

increase in the consumption of fuel gas on the F-201.

Node 4 for the PDT-249 tag number occurs high

pressure and low pressure deviation. In high pressure

conditions it is due to the failure of the opening of the

PDV-249 which results in a potential for tube

explosion in the convection section which results in

an explosion (injury / death). Meanwhile, the low

pressure condition is caused by the PDV-249 opening

not as desired. This resulted in an explosion and a soot

release on the flue gas stack which had an impact on

the environment.

Node 5 for the FT-216A instrument, there is a

deviation in high flow and low flow. The high flow

condition was caused by the failure to open the FV-

216A which resulted in a potential low temperature in

the reactor which affected the resulting product.

Meanwhile, the low flow was caused by the FV-216A

not opening as requested, resulting in a trip due to the

low temperature of the stripper column. Meanwhile,

the tag number FT-216B has deviation of high flow

and low flow. The high flow condition occurs due to

failure to open FV-216B which results in a potential

low temperature in the stripper column which affects

the resulting product. Meanwhile, the low flow was

caused by not opening the FV-216B as requested,

resulting in a trip due to the low temperature of the

stripper column

Node 6 for PDT-238 tag number occurs deviation

of high pressure and low pressure. In high pressure

condition, it is because the pilot burner strainer line is

not installed which results in the potential for the pilot

burner to light off and is not in a safe condition.

Meanwhile, the low pressure condition is caused by

the installation of the pilot burner strainer line, which

causes the pilot burner to light off and is not in a safe

condition. In the PT-265 there is a deviation of high

pressure and low pressure. The high pressure

condition was caused by failed close valve PV-265 so

that it could cause an explosion. Meanwhile, in low

pressure conditions, the valve opening of the PV-265

does not open according to demand, resulting in

reduced fuel gas supply resulting in a decrease in

temperature in the stripper column.

Node 7 for the PDT-238 instrument, there is a

deviation in high pressure and low pressure. In high

pressure condition, it is because the pilot burner

strainer line is not installed which results in the

potential for the pilot burner to light off and is not in

a safe condition. Meanwhile, the low pressure is

caused by the installation conditions of the F-202

strainer line pilot burner. So that resulting in the

potential for the pilot burner to light off and not in a

safe condition. In PT-264 there is a deviation of high

pressure and low pressure. The high pressure

condition is caused by a malfunction of the PV-264

open so that there is a potential for a decrease in fuel

gas consumption. Meanwhile, the low pressure

condition has the reason that the PV-264 instrument

does not open according to demand. This resulted in

a reduction in fuel oil supply and a decrease in

temperature at the stripper column.

Node 8 for oil burner and its flow is controlled by

PDIC-262. The PDT-262 instrument occurs with a

high-pressure deviation. This condition is caused by

a failure to fully open the valve PDV-262, resulting

in a flame off of the fuel oil burner and an explosion.

ICATECH 2023 - International Conference on Advanced Engineering and Technology

134

3.2 Actual SIL Calculation

In the calculation of PFDavg the Charge Heater (82-

F-201) and Reboiler Heater (82-F-202) below using

interval test for 90 days or 2160 hours.

Table 9: Calculation of PFD SIS inlet charge heater 82

FSLL-208A.

Instru

ment

MooN

Failure

Rate

PFD SI

FSLL

-208A

1oo1

411

2.4295E-

0.026

FT-

208A

1oo1

411

2.4309E-

0.026

UV-

212

1oo1

416

2.4001E-

0.025

UV-

211A

1oo1

416

2.4008E-

0.025

UV-

211B

1oo1

411

2.4302E-

0.026

Based on the PFDavg value from the SIS in Table

9 obtained SIL value for loop 82-FSLL-208A is SIL

0. On the reboiler heater (82-F-202) a loop safety

instrumented system is determined. Here's one of the

safety loops.

Table 10: Calculation of PFD SIS inlet reboiler heater 82

FSLL-208A.

Instru

ment

MooN

Failure

Rate

PFD SIL

FSLL

-216A

1oo1

411

2.4317E

-05

0.026

SIL

FT-

216A

1oo1

411

2.4317E

-05

0.026

UV-

215

1oo1

418

2.3877E

-05

0.025

UV-

214A

1oo1

418

2.3877E

-05

0.025

UV-

214B

1oo1

412

2.4218E

-05

0.026

In Table 10, it is obtained that the PFDavg value

from SIS with the SIL value for the 82-FSLL-216A

loop is SIL 0. As for some of the PFDavg calculations

in the safety control loop, the total PFDavg value for

the charge heater (82-F-201) is 0.109778 with a SIL

value of 0. While the total PFDavg value for the

reboiler heater (82-F-202) is 0, 106419 with a SIL

value of 0. Thus, the charge heater (82-F-201) and the

reboiler heater (82-F-202) have the potential to fail

less than once in 10 years.

3.3 Calculation of the SIL and LCC

Design

Optimization was carried out to determine the

minimum design PFDavg and LCC values. In this

case, the objective function used is the LCC.

Meanwhile, PFDavg is one of the variables that

affects the objective / objective function. The charge

heater (82-F-201) and the reboiler heater (82-F-202)

have different optimization values for PFDavg and

LCC. The following is the plot of the PFDavg

optimization graph for each section with a population

of 50 and 200 iterations.

(a)

(b)

Figure 1. PFDavg optimization design for (a) 82-F-201 and

(b) 82-F-202

From Figure 1 (a), the design results of the

minimum PFDavg value for the charge heater (82-F-

201) are 0.0069. Whereas in Figure 1 (b) the reboiler

heater (82-F-202) is 0.0049. By using the criteria of

SIL value based on low demand mode, the charge

heater (82-F-201) and reboiler heater (82-F-202) have

a SIL value of 2. The design results have a lower

PFDavg value than the actual PFDavg. This is to

adjust the design targets that come from the company.

The SIL value for the design with the SIL target of

the company is the same, namely SIL 2. With a time

interval of 720 hours or one month. Then performed

Hazard and Operability Study (HAZOP) Based RAMS Plus C Using Genetic Algorithm Optimization in Heater Naphtha Hydro Treater, Oil

Reﬁnery Unit, Cilacap Indonesia

135

the optimization of the LCC value obtained by the

graph as shown in Figure 2.

(a)

(b)

Figure 2. LCC optimization design for (a) 82-F-201 and (b)

82-F-202.

Based on Figure 2 (a), the minimum LCC value is

USD 477370, while in Figure 2 (b) the LCC value is

USD 320430. Not only influenced by PFDavg, the

LCC value is also influenced by the diversity of

technology types and the SIS architectural vote. The

following is a vote for the SIS architecture and

technology types for the charge heater (82-F-201) and

the reboiler heater (82-F-202).

Table 11: Architectural vote design and technology types.

Sect

ion

Instru

ment

MooN

Technology Types

1/unit

2/un

3/unit

82-

F-

201

FT-

207

1oo2 2 0 0

PT-

223

1oo1 0 1 0

LT-

201

1oo1 1 0 0

FT-

201

1oo1 1 0 0

LT-

206

1oo3 0 3 0

TT-

208

1oo2 1 1 0

PT-

252

1oo2 0 2 0

PT-

251

1oo4 4 0 0

PDT-

249

1oo1 1 0 0

FV-

207

1oo1 1 0 0

PV-

223

1oo1 1 0 0

FV-

201

1oo3 2 1 0

LV-

206

1oo1 1 0 0

PV-

252

1oo2

Table 11: Architectural vote design and technology

types(continued).

Sec

tion

Instru

ment

MooN

Technology Types

1/unit 2/unit

3/un

82-

F-

201

PV-

251

1oo4 2 2 0

PDV-

249

1oo1 1 0 0

82-

F-

202

FT-

216A

1oo1 0 1 0

FT-

216B

1oo1 0 1 0

PDT-

238

1oo2 2 0 0

PT-

265

1oo2 1 1 0

PT-

264

1oo4 2 2 0

PDT-

262

1oo1 1 0 0

FV-

216A

1oo1 1 0 0

FV-

216B

1oo1 1 0 0

PV-

265

1oo1 0 1 0

PV-

264

1oo2 1 1 0

PDV-

262

1oo1 1 0 0

From the optimization results, it is found that the

type of technology that is generally used for

transmitters is the type A technology or smart

transmitter on the charge heater (82-F-201) with a

total of 10 instrument units. Meanwhile, the valve

uses technology type A, namely air operated, totaling

9 units. Whereas for the reboiler heater (82-F-202) the

type of technology that is generally used is

Technology A for smart transmitters with 5 units of

ICATECH 2023 - International Conference on Advanced Engineering and Technology

136

instruments and 4 units for the type of water operated

valve. Then to vote for the optimal SIS architecture is

to use 1oo1. From the design results, it can reduce the

potential risk to the plant. The following are the

potential design hazards for the plant.

Table 12: Design results of potential hazards in the plant.

Section Instrument

Likeli

hoo

Severity RR

82-F-

201

FT-207

A 1

A 3 L

PT-223 A 3 L

Table 12: Design results of potential hazards in the

plant(continued).

Section Instrument

Likeli

hoo

Severity RR

82-F-

201

FT-207

A 1 N

A 3 L

PT-223

A 3

A 4

LT-201

A 4 M

FT-201

A 3 L

LT-206

A 1

A 1 N

TT-208

A 2 N

PT-252

A 3 L

PT-251

A 3

A 3 L

PDT-249

A 4 M

82-F-

202

FT-216A

A 3

A 3 M

FT-216B

A 3

A 3 M

PDT-238

A 2

A 2 N

PT-265

A 3 L

PT-264

A 3

A 3 L

PDT-262 A 4 M

From the table above, it can be seen that there is a

decrease in the potential risk of the charge heater (82-

F-201) to 27.77% medium risk, 44.46% low risk and

27.77% normal. The same thing happened a decrease

in the potential risk of the reboiler heater (82-F-202)

to 45.45% medium risk, 36.36% low risk and 18.19%

normal.

4 CONCLUSIONS

Potential hazards that occur in the Charge Heater (82-

F- 201) has a percentage of 27.7% high risk, 33.3%

medium high risk, 22.3% medium risk, 5.5% low risk

and 11.2% normal. In addition, the percentage of

potential hazards that occur in the Reboiler Heater

(82-F-202) is 45.45% high risk, 36.36% high risk

medium and 18.19% medium risk. The SIS

evaluation on the Charge Heater (82-F-201) has a

PFDavg value of 0.109778 with an actual SIL value

of SIL 0 while the Reboiler Heater (82-F-202) has an

actual PFDavg value of 0.106419 with a SIL value of

0. The value of the design SIL on the Charge Heater

(82-F-201) is SIL 2. Then the Reboiler Heater (82-F

202) has a design SIL value, namely SIL 2. The SIS

design results in an architectural vote of 1OO1 and

type A technology, namely smart transmitters and air

operated for the entire instrument. Thus, the

percentage of potential hazards in the Charge Heater

(82-F-201) becomes 27.77% medium risk, 44.46%

low risk and 27.77% normal, as for the reboiler heater

(82-F-202) to 45.45% medium risk, 36.36% low risk

and 18.19% normal. The result of cost design

optimization using a genetic algorithm resulted in a

life cycle cost (LCC) value for the Charge Heater (82-

F-201) of USD 477,370, while for the Reboiler

Heater (82-F-202) it was USD 320,430.

Hazard and Operability Study (HAZOP) Based RAMS Plus C Using Genetic Algorithm Optimization in Heater Naphtha Hydro Treater, Oil

Reﬁnery Unit, Cilacap Indonesia

137

ACKNOWLEDGEMENTS

The authors would like to thank the Directorate for

Research and Community Service (DRPM ITS),

Institute Teknologi Sepuluh Nopember, Surabaya.

with supporting financing, the research. Also, the

authors would like to thank the anonymous referees

for their comments on the eelier version of this work.

REFERENCES

A.C. Torres-Echeverrı, S. Martorell, & H.A. Thompson.

(2009). Design optimization of a safety instrumented

system based on RAMS+C addressing IEC 61508

requirements and diverse redundancy. Reliability

Engineering and System, 94, 162–179.

Anonim. (1989). Operation Manual for 82 Naphtha

Hydrotreating Unit. JGC Corporation.

Anonim. (1998). IEC 61508 Functional safety of electrical

electronic programmable electronic safety related

system Parts 1-7.

D. C. Montgomery. (2009). Statistical Quality Control 6th

Edition. John Wiley & Sons, Inc.

Goble. (2005). Probability Failure Demand.

Handbook of Energy & Economic Statistics of Indonesia.

(2015). Kementerian Energi dan Sumber Daya Mineral.

ISA. (2002). Safety Instrumented Function (SIF)-Safety

Integrity Level (SIL) Evaluation Techniques Part 2 :

Determining the SIL of a SIF via simplified equations

in ANSI/ISA TR.84.00.02-2002-part 2. Research

Triangle.

Kresna, R., Cordova, H., & Noriyati, R. D. (2017). HAZOP

Study and Risk Assessment in Three- Phase Separator

Oil and Gas Exploration Farm - East Java , Indonesia.

Advances in Natural and Applied, 11(3), 77–85.

Musyafa, A., R.D. Noriyanti, Azizatus, & S.U. (2019).

Safety assessment base fault tree analysis for

sustainability fertilizer plant at East Java Indonesia. AIP

Conference Proceedings.

Musyafa, A., R.D. Noriyanti, & Novan Yudha. (2019).

Reliability and safety study on heat exchanger control

system: Case study in ortho xylene process-

petrochemical industry. AIP Conference Proceedings.

Musyafa, A., R.D. Noriyanti, Rozaaq, W., & A.

Soepriyanto. (2015). Hazard & Operability Study and

Determining Safety Integrity Level on Sulfur Furnace

Unit: A Case Study in Fertilizer Industry. Procedia

Manufacturing.

Musyafa, A., Z.F., N., & Asy’ari, M. K. (2019). Hazop-

Evaluation and Safety Integrity Level (SIL) “ analysis

on steam system in ammonia plant Petrokimia Gresik

Ltd. AIP Conference Proceedings.

N. Hyatt. (2003). Guidelines for Process Hazards Analysis,

Hazards Identification & Risk Analysis. CRC Press.

Pertamina. (2018). Pertamina Unit Pengolahan IV Cilacap.

https://www.pertamina.com/id/ unit-pengolahan-

iv.cilacap.

Summers. (2010). Safety Instrumented System.

ICATECH 2023 - International Conference on Advanced Engineering and Technology

138