Equipment Reliability Data Guide

Overview

NeqSim’s risk framework uses equipment reliability data to calculate failure probabilities, availability, and risk metrics. This guide explains:

  1. Available built-in data sources
  2. CSV format specification
  3. How to import your own data (including OREDA)
  4. Data source selection guidance

Built-in Data Sources

NeqSim includes three public domain data sources that can be freely used:

1. IEEE 493 (Gold Book) - ieee493_equipment.csv

Source: IEEE Std 493-2007 “Recommended Practice for the Design of Reliable Industrial and Commercial Power Systems”

Scope: Primarily electrical and utility equipment

~100 equipment records

2. IOGP/OGP Data - iogp_equipment.csv

Source: IOGP Reports 434-series, UK HSE Offshore Statistics, SINTEF summaries

Scope: Oil & gas specific equipment and safety systems

~150 equipment records

3. Generic Literature - generic_literature.csv

Source: Lees’ Loss Prevention, CCPS Guidelines, MIL-HDBK-217F, DNV-RP-G101

Scope: Comprehensive process equipment coverage

~180 equipment records

4. Representative OREDA Data - oreda_equipment.csv

Source: Representative values based on OREDA Handbook categories

Scope: Offshore equipment reliability

~120 equipment records

Note: These are representative values for demonstration. For actual projects, obtain official OREDA data from www.oreda.com

CSV Format Specification

Required Columns

Column Type Description
EquipmentType String General equipment category (e.g., “Pump”, “Valve”)
EquipmentClass String Specific type/subclass (e.g., “Centrifugal”, “Ball”)
FailureMode String Failure mode description (e.g., “All modes”, “Leak”, “Fail to close”)
FailureRate Double Failures per hour (e.g., 1.14e-5)
MTBF_hours Double Mean Time Between Failures in hours
MTTR_hours Double Mean Time To Repair in hours
DataSource String Data source identifier (e.g., “OREDA-2015”, “IEEE493-2007”)
Confidence String Data quality: “High”, “Medium”, or “Low”

Example Records

EquipmentType,EquipmentClass,FailureMode,FailureRate,MTBF_hours,MTTR_hours,DataSource,Confidence
Pump,Centrifugal,All modes,1.83e-4,5464,24,OREDA-2015,High
Pump,Centrifugal,Seal failure,5.71e-5,17513,8,CCPS-1989,High
Valve,Ball,Fail to close,2.85e-6,350880,4,OREDA-2015,High
Compressor,Reciprocating,Critical,5.71e-5,17513,120,IEEE493-2007,High

Comments and Headers

Units

Parameter Unit
FailureRate failures per hour
MTBF_hours hours
MTTR_hours hours

Relationship

The following relationship should hold:

FailureRate ≈ 1 / MTBF_hours

Importing Your Own Data

import neqsim.process.safety.risk.data.OREDADataImporter;

// Load from custom CSV file
OREDADataImporter importer = new OREDADataImporter();
importer.loadFromCSV("path/to/your/reliability_data.csv");

// Query failure data
double failureRate = importer.getFailureRate("Pump", "Centrifugal", "All modes");
double mtbf = importer.getMTBF("Compressor", "Reciprocating", "Critical");
double mttr = importer.getMTTR("Valve", "Safety/Relief", "Fail to open");

// Get full equipment record
EquipmentReliabilityData data = importer.getEquipmentData("Separator", "Three-phase");

Method 2: Programmatic Data Entry

import neqsim.process.safety.risk.data.OREDADataImporter;

OREDADataImporter importer = new OREDADataImporter();

// Add individual records
importer.addEquipmentData(
    "Pump",                    // EquipmentType
    "Centrifugal",            // EquipmentClass
    "Seal failure",           // FailureMode
    5.71e-5,                  // FailureRate (per hour)
    17513,                    // MTBF (hours)
    8,                        // MTTR (hours)
    "MyCompanyData",          // DataSource
    "High"                    // Confidence
);

Method 3: Using ProcessEquipmentReliability

import neqsim.process.safety.risk.ProcessEquipmentReliability;

// Create reliability data object
ProcessEquipmentReliability reliability = new ProcessEquipmentReliability("HP Pump");
reliability.setFailureRate(1.83e-4);  // failures per hour
reliability.setMTBF(5464);            // hours
reliability.setMTTR(24);              // hours
reliability.setDataSource("OREDA-2015");

// Attach to process equipment
pump.setReliabilityData(reliability);

Importing Official OREDA Data

If your organization has access to the official OREDA Handbook, you can import that data:

Step 1: Create CSV from OREDA Tables

Convert OREDA tables to CSV format:

# My Company OREDA Data Import
# Source: OREDA Handbook 6th Edition (2015)
# Converted by: [Your Name]
# Date: [Conversion Date]
EquipmentType,EquipmentClass,FailureMode,FailureRate,MTBF_hours,MTTR_hours,DataSource,Confidence
Pump,Centrifugal (single stage),All modes,1.92e-4,5208,26,OREDA-2015-Vol1-Ch4,High
Pump,Centrifugal (single stage),Critical,4.81e-5,20800,52,OREDA-2015-Vol1-Ch4,High

Step 2: Place File in Appropriate Location

# For project-specific use
<project>/src/main/resources/reliabilitydata/my_oreda_data.csv

# For system-wide use
${user.home}/.neqsim/reliabilitydata/oreda_data.csv

Step 3: Load Data

// Load official OREDA data
OREDADataImporter importer = new OREDADataImporter();
importer.loadFromCSV("reliabilitydata/my_oreda_data.csv");

// Or load from multiple sources
importer.loadFromCSV("reliabilitydata/oreda_equipment.csv");      // Built-in representative
importer.loadFromCSV("reliabilitydata/my_oreda_data.csv");        // Your official OREDA
// Later loaded data takes precedence for matching equipment

OREDA Data Structure Reference

The official OREDA Handbook organizes data into:

Volume Content
Volume 1 Topside Equipment (pumps, compressors, valves, etc.)
Volume 2 Subsea Equipment (trees, manifolds, umbilicals, etc.)

Each equipment entry includes:

Data Source Selection Guidance

Which data source to use?

Scenario Recommended Source
Electrical power systems IEEE 493
Oil & gas offshore topside OREDA or IOGP
Subsea systems OREDA or IOGP
Safety systems (ESD, F&G) IOGP
Process piping and vessels Generic Literature / CCPS
Generic industrial equipment IEEE 493 + Generic Literature
Fire/explosion risk assessment IOGP

Combining Data Sources

// Create combined importer
OREDADataImporter importer = new OREDADataImporter();

// Load in priority order (later files override earlier)
importer.loadFromCSV("reliabilitydata/generic_literature.csv");  // Generic base
importer.loadFromCSV("reliabilitydata/ieee493_equipment.csv");   // Electrical focus
importer.loadFromCSV("reliabilitydata/iogp_equipment.csv");      // O&G specific
importer.loadFromCSV("reliabilitydata/oreda_equipment.csv");     // OREDA data (highest priority)

// Query will return best available data
double pumpFailureRate = importer.getFailureRate("Pump", "Centrifugal", "All modes");

Failure Rate Conversions

Common Conversion Factors

// Failures per year to failures per hour
double failuresPerHour = failuresPerYear / 8760.0;

// Failures per 10^6 hours to failures per hour
double failuresPerHour = failuresPer10e6hours / 1e6;

// MTBF (hours) to failure rate
double failureRate = 1.0 / mtbfHours;

// Availability calculation
double availability = mtbf / (mtbf + mttr);

OREDA Rate Conversion

OREDA reports failure rates per 10^6 hours. To convert:

// OREDA typically reports as "failures per 10^6 hours"
double oredaRate = 183.0;  // From OREDA table
double failuresPerHour = oredaRate * 1e-6;  // = 1.83e-4

Data Quality and Confidence

Confidence Levels

Level Description Typical Use
High Well-established data from large populations Final design, risk assessment
Medium Reasonable data but limited population Preliminary design, screening
Low Expert judgment or sparse data Conceptual studies only

Uncertainty Handling

// OREDA provides uncertainty bounds
// Use mean for expected values
// Use 95th percentile for conservative estimates

double meanRate = importer.getFailureRate("Pump", "Centrifugal", "All modes");
double conservativeRate = meanRate * 3.0;  // Typical factor for 95th percentile

API Reference

OREDADataImporter Class

public class OREDADataImporter {
    // Loading methods
    void loadFromCSV(String filepath);
    void loadFromResource(String resourcePath);
    void addEquipmentData(String type, String class, String mode, 
                         double rate, double mtbf, double mttr,
                         String source, String confidence);
    
    // Query methods
    double getFailureRate(String type, String equipClass, String mode);
    double getMTBF(String type, String equipClass, String mode);
    double getMTTR(String type, String equipClass, String mode);
    String getDataSource(String type, String equipClass, String mode);
    String getConfidence(String type, String equipClass, String mode);
    EquipmentReliabilityData getEquipmentData(String type, String equipClass);
    
    // Listing methods
    List<String> getEquipmentTypes();
    List<String> getEquipmentClasses(String type);
    List<String> getFailureModes(String type, String equipClass);
}

Users are responsible for ensuring they have appropriate licenses for any proprietary data used in their projects.

References

  1. IEEE Std 493-2007, “IEEE Recommended Practice for the Design of Reliable Industrial and Commercial Power Systems (Gold Book)”
  2. OREDA Handbook 6th Edition (2015), SINTEF/DNV/OREDA Participants
  3. IOGP Report 434-series, “Safety Performance Indicators”
  4. CCPS, “Guidelines for Process Equipment Reliability Data” (1989)
  5. Lees’ Loss Prevention in the Process Industries, 4th Edition (2012)
  6. MIL-HDBK-217F, “Reliability Prediction of Electronic Equipment”
  7. DNV-RP-G101, “Risk Based Inspection of Offshore Topsides Static Mechanical Equipment”