RISK ASSESSMENT AND RISK-BASED INSPECTION...

RISK ASSESSMENT AND RISKRISK ASSESSMENT AND RISK--BASED BASED INSPECTION FORINSPECTION FOR

PETROCHEMICAL UNIT:PETROCHEMICAL UNIT:A PRACTICAL APPLICATIONA PRACTICAL APPLICATIONSong-Chun Choi, Je-Chang Ha, Kyosik Park

October, 28, 2008

Mary Kay O’Connor Process Safety Center, 2008 International Symposium& World Conference on Safety of Oil & Gas Industry

Mary Kay O’Connor Process Safety Center, 2008 International Symposium& World Conference on Safety of Oil & Gas Industry

�� IntroductionIntroduction

ContentsContentsContents

�� Development of KGS-RBITM

program for petrochemical plant

Development of KGS-RBITM

program for petrochemical plant

�� Application of KGS-RBITM

program on the NCC System in Petrochemical Plant

Application of KGS-RBITM

program on the NCC System in Petrochemical Plant

�� Results and DiscussionResults and Discussion

�� ConclusionConclusion

�� What is RBI

(Risk-Based Inspection)?What is RBI

(Risk-Based Inspection)?

�. Introduction (1)�. Introduction (1)

• Many refinery and petrochemical plants are being operated in Korea.

• Due to improvements of industrial technologies, the relevant equipment are

getting complex to allow operation in higher temperature and pressure

conditions.

• Thus continuous operation while sustaining their integrity through good mainte

nance practices becomes an important issue.

0

50

100

150

200

Previous of 1979 1980-1989 1989-2003

The number of petrochemical plants in KoreaThe examples of petrochemical facilities


• The possibilities of accidents owing to aging equipment have increased in

refinery and petrochemical industries.

• Unanticipated accidents may cause significant social and economic losses.

• To reduce the possibility of such incidents, maintenance activities such as

inspection, repair or replacement of aging equipment has to be carried out.

• Thus, a risk-based inspection (RBI) methodology for refinery and petrochemical

plants should be established.

Unknown18%

Process Upset8%

Natural Hazard6%

Design Error4% Sabotage/Aroson

3%

Operating Error20% Mechanical

Failure41%

The cause classification of major industrial accidents

Piping systems

TanksReactors

DrumsPumps/Comp.

H/ETowers

Heaters/BoilersOthers/Unknown

00 2020 2525 3030 35351515101055Number of Failures

-Abroad (1992-2001) From NBBI Annual Report

Equipment Failure Category in Hydrocarbon-Chemical IndustryEquipment Failure Category in Hydrocarbon-Chemical Industry

Over 80% of the Equipment- Caused by the Failure

to Pressurized equipment


�. RBI (1)�. RBI (1)

• RBI is a method for using risk as a basis to prioritize and manage the efforts of an inspection activity.

- Risk = LOF (likelihood of failure) × COF (consequence of failure)

• An effective risk based inspection activity results in reduced risk level for a given inspection level.

• In an operating plant, a relatively large percentage of the risk is usually associated with a small percentage of equipment.

• A RBI methodology permits the shift of inspection and maintenance resources to provide a higher level of coverage on the high risk items and an appropriate effort on lower risk equipment.

• For example, API 581 guideline- Level 1 (Qualitative RBI)- Level 2 (Semi-quantitative RBI)- Level 3 (Quantitative RBI)

Damageconsequence

category

Likelihoodcategory

Healthconsequence

category

Choose the highest from two

consequenc e

categories

Qualitative RBI

Start

Plant databaseSelect a set of hole size

Plant database

Estimate likelihood of leak

Estimate consequence

Risk = LOF × COF

Semi-quantitative RBI Quantitative RBI

Convert to a risk matrix using likelihood category and consequence category

Suggest each equipment risks after sum of all

scenarios

Semi-quantitative RBIor

Quantitative RBI

Start

Risk matrix

Qualitative RBI process Semi-quantitative and Quantitative RBI processes

�. RBI (2)�. RBI (2)

• Risk Evaluation Process based on API 581

Plant DB

DatabaseManagement

System

DatabaseManagement

System RBI DB

Material DB

ADOConnection

ADOConnection

Risk AssessmentProgram

Risk AssessmentProgram

MaterialManagement

Program

MaterialManagement

Program

DataData

PicturePicture

AssessmentResult

AssessmentResult

DocumentDocumentGraphic

UserInterface

GraphicUser

Interface

Presentation Layer Application Layer Database Layer

- Window Environment

- Visual C++, Visual Basic

- Microsoft Access 2000- Visual Basic

�. Development of RBI program (1)�. Development of RBI program (1)

• The 3-tier structure of proposed RBI program


• List of input data for using the KGS-RBITM

P&ID No.PFD No.Stream No.Inventory Group NameMaterialService Start DateDesign Life (yr)

P&ID No.PFD No.Stream No.Inventory Group NameMaterialService Start DateDesign Life (yr)

Length (mm)Diameter (mm)Thickness (mm)Operating Pressure (kg/cm2)Operating Temp(C.)Design Pressure (kg/cm2)Design Temp (.C)Insulation (Y/N)Lining TypePWHT (Y/N)

Length (mm)Diameter (mm)Thickness (mm)Operating Pressure (kg/cm2)Operating Temp(C.)Design Pressure (kg/cm2)Design Temp (.C)Insulation (Y/N)Lining TypePWHT (Y/N)

No. of ValvesNo. of BranchesNo. of Injection PointsNo. of ConnectionsNo. of NozzlesConstruction CodeVibration MonitoringPlanned ShutdownUnplanned ShutdownStability RankingRV MaintenanceFouling TendencyCorrosive Service (Y/N)Very Clean Service (Y/N)

No. of ValvesNo. of BranchesNo. of Injection PointsNo. of ConnectionsNo. of NozzlesConstruction CodeVibration MonitoringPlanned ShutdownUnplanned ShutdownStability RankingRV MaintenanceFouling TendencyCorrosive Service (Y/N)Very Clean Service (Y/N)

Rep. MaterialInitial fluid stateToxic MaterialToxic PercentDetection RatingIsolation RatingMitigation SystemsLiquid PercentGas Density (kg/m3)Inventory Input TypeInventory (User input)

Rep. MaterialInitial fluid stateToxic MaterialToxic PercentDetection RatingIsolation RatingMitigation SystemsLiquid PercentGas Density (kg/m3)Inventory Input TypeInventory (User input)

Include Environmental Cleanup cost % Released from Diked areaRelease TypeType of FoundationMethod of DetectionDetection Times

Include Environmental Cleanup cost % Released from Diked areaRelease TypeType of FoundationMethod of DetectionDetection Times

Input Data(Excel File)Input Data(Excel File)

Equipment InformationEquipment Data Likelihood Data

Consequence Data

Financial Data


• Material management program


• Qualitative RBI module


• Semi-Quantitative RBI module

API 581 method Proposed RBI method


• Quantitative RBI module

API 581 method Proposed RBI method

�. Application of proposed RBI program�. Application of proposed RBI program

• To verify the applicability of the proposed RBI program, proposed RBI program apply to Naphtha Cracking Center.

• The NCC system in this study has been operated for 14 years since it started to produce in 1992.

• The NCC process can largely be divided into four phases

• In the NCC plant to construct RBI; assessment was made on 742 fixed equipments and 1,258 piping systems except utility unit.

Quenching

Cracking Heater

Compression

Distillation

NCC Plant

NCC Plant

5 39 5 15 47 21

4 142 11 109 310 135

3 46 3 38 76 98

2 260 7 195 204 237

1 1 0 1 0 0

A B C D E

Like

lihoo

d of

Fai

lure

Consequence of Failure

NCC Plant Risk DistributionHigh15%

Medium30%

MediumHigh39%

Low16%

�. Result of RBI for NCC plant (1)�. Result of RBI for NCC plant (1)

• RISK Distribution of NCC Plant

A-(Cracking Heater) ProcessHigh3%

Low22%

Medium39%

MediumHigh36%

B-(Quenching) ProcessHigh8% Low

57%

Medium19%

MediumHigh16%

C-(Compressing) ProcessHigh4%

Low14%

Medium54%

MediumHigh28%

D-(Distillation) ProcessHigh26%

Low5% Medium

20%

MediumHigh49%


• RISK Distribution for processes

PipeHigh20%

Low5%

MediumHigh45%

Medium30%

ColumnHigh6% Low

31%Medium

High29%

Medium34%

DrumHigh7% Low

38%

MediumHigh19%

Medium36%


• RISK Distribution of NCC Plant

Heat ExchangerHigh8% Low

34%

MediumHigh35%

Medium23%

FilterHigh0%

Low75%

MediumHigh6%

Medium19%

Tank

Medium49%

MediumHigh33%

Low18%

High0%

1

10

100

1000

10000

1000001000000

Sum

mat

ion

of T

MSF

COLUMN

DRUMEXCHANGER

HEATER

PIPE

Total : Thinning

Total : SCCTotal : HTHA

Total :Brittle Fracture

Total : External Damage(CUI)

Total : ThinningTotal : SCCTotal : HTHATotal :Brittle FractureTotal : External Damage(CUI)


• Analysis of damage factor for equipments and pipes by high risk

D. Process (d)

1

10

100

1000

10000

NCC-8B-P

-4104

-BA8-R

NCC-8B-P

-4133

-BA8-R

NCC-8B-P

-4134

-BA8-R

NCC-8B-P

-4135

-BA8-R

NCC-8B-P

-4277

-BA1

NCC-E-D

A402-B

TM

NCC-E-D

A403-B

TM

NCC-E-E

A403A-T

S

NCC-E-E

A403B-T

SNCC-E

-EA40

4

NCC-E-E

A436-T

S

NCC-E-E

A437-T

S

NCC-E-E

A603-T

SNCC-E

-EA604

NCC-E-FA40

3NCC-E

-FF301A

NCC-E-FF30

1B

NCC-2B-P

-3076

-BK2-R

Equipments

CoF

(m2)

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

LoF

(yea

r)

Consequence of Failure

Likelihood of Failure

36

Inventory No.

PipesPipes

ExchangerColumn


• CoF & LoF Results with High Risk


• Inspection interval by Risk

Inspection Interval (yr) Total (%)

1 262 13.10 4 593 29.65 6 827 41.35 8 318 15.90

Total 2000 100.00 262

593

827

318

0 200 400 600 800 1000

1 year

4 year

6 year

8 year

Inspection Interval

�. Conclusion�. Conclusion

• Based on risk ranking for the whole NCC plant, High Risk areas which need urgent risk-relieving measures formed about 15 percent, with piping system forming the largest part by equipments.

• Based on risk assessment for each unit process of the NCC plant,

piping systems and the heat exchanger in the distillation process operated at low temperature showed remarkable brittle fracture and SCC, requiring special attention for them.

• Among equipments, risk was highest for pipe, followed by heat exchanger, drum, and column; in particular, the heat exchanger showed high risk due to significantly low inspection efficiency and inspection methodology in internal test.

• Based on management systems assessment from interviews with relevant workers, training, emergency response, and incident investigation got generally low scores in operating the NCC plant, which recommends complementary measures in the future.

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