CCPS PERD Reliability API Presentation_r3

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PERD

A discussion with the API Subcommittee on

Instruments and Control Systems

23 April 2012

Your Presenters

Gene Meyer

Dow Chemical, 28 years

Reliability Engineering for the last 12 years.

Hal Thomas (on the phone)

Exida (formerly Air Products)

Process Safety

Original chair of PERD

2

Alignment

AICHE

CCPS, Center for Chemical Process Safety

PERD, Process Equipment Reliability Database

• Participants

» Members and Users

A subscription-based project with CCPS.

3

Agenda

Introduction

Alignment

Organization

Goal

The solution

Details

Results

Discussion

4

Reliability Situation

Industry-specific reliability data is not available.

Quality company data is scarce.

Performance-based regulations enacted.

CPI and HPI capital intensity forces greater asset management (i.e. higher process reliability)

5

Process Safety Situation

Performance-based regulations enacted.

Lack of quality data reduces confidence & jeopardizes industry credibility with respect to quantitative analysis results

Performance-based processes require quality management systems that are auditable and defensible

Quality Assurance requires data to validate performance assumptions

6

Current Reliability Modeling Situation

7

The Vision

Readily available Maintenance and Reliability Data that:

Is generated from equipment like yours,

Is automatically loaded into a database,

Represents industry experience,

Is validated for accuracy,

Is statistically evaluated by documented methods,

Is benchmarked versus your industry

Is available for your use in:

Simulation

Process validation

Process design and troubleshooting

Reliability Growth

Quantitative Risk Assessment

8

The Solution

PERD

Process Equipment Reliability Database

A database that works with your computerized maintenance management system to upload equipment performance data, organize, validate, calculate, benchmark and make available for use with clear statistical guidance.

The database that uses company and industry equipment performance data evaluated against industry standards.

9

PERD is:

A member-led project developed by CCPS to provide equipment reliability data with the following mission :

The PERD Mission

Operation of an Equipment Reliability Database, Making

Available High Quality, Valid, and Useful Data to the HPI and CPI Enabling Analyses to Support Availability,

Reliability, and Equipment Design Improvements,

Maintenance Strategies, and Life Cycle Cost Determination

PERD Provides:

Practical collection approach and Consistent work processes for data

Sound theoretical foundation based on engineering fundamentals

Efficient software tools for data submission

S/W dedicated for use by participating companies

Quality assurance for data analysis

Identification and analysis of outliers

Defensible and auditable results

11

PERD History

During development of CCPS Chemical Process Quantitative Risk

Analysis book, committee concluded a separate guideline book was needed to address data

1989 - The result was Guidelines for Process Equipment Reliability

Data with Data Tables

Following publication, Hal Thomas and Tom Carmody attended an

OREDA meeting and concluded data mining was too expensive, but data harvesting if implemented properly was sustainable, hence the

PERD initiative was born.

1998

– Guidelines for Improving Plant Reliability Through Data

Collection and Analysis published establishing the basic foundational approach

Today

– Work processes established and documented, rolling out

2 nd generation PERD software, continuing to develop equipment taxonomies & analyze equipment data

12

Fundamental Concepts

Develop & document equipment boundary diagram

Perform rigorous “Functional Analysis” to determine and document all of the fundamental failure modes that represent complete or degraded failures as well as documenting incipient conditions for an equipment type

Reference paper by Rausand and Oin in their critique of OREDA database

13

Fundamental Concepts Continued

Engineer information systems to

Support data acquisition using a experimental design mentality, facilitating immediate data analysis

Input only facts, i.e. do not require interpretation on part of mechanic or technician

• Make use of standard pick lists to extent possible

Create event input forms that allow inference of failure modes by asking the question, ‘What data is it that would allow us to conclude a particular failure mode has occurred.

14

Fundamental Concepts Continued

Leverage existing information systems that are going to exist anyway, improving data quality with no increase in cost

Design equipment design spec data fields to be PERD compatible

Design process demand, inspection and test record data fields to be PERD compatible

15

Fundamental Concepts - The Data Farm

Quality info for use in reliability analysis, maintenance strategies, risk analysis, etc.

Events occur on a continuous basis

Electronically extract validated data

Periodic batch transfer of data

PERD Database

163Feb00_Ins urance

16

An Integrated Approach

CCPS PERD

Industry Offline Reliability

Analysis Database

Corporate PERD

In-Tools

Maintenance Module

(i.e. SAP, Maximo, etc.)

Population Data

Process Specs

Facility PERD

Operating Group

Information System(s)

Maintenance

Activities

Process Events

Process Specs

Design Specs

Purchase Order

Installation

Commissioning

Plant Operation

Inventory Data

ID Number

T ag Number

Event Data

M aintenance

Inspections

Proof T esting

Incidents

Etc.

CCPS Industry

Database

Company 1

Database

The Harvest

Company 2

Database

Company n

Database

Plant 1

Data

Plant 2

Data

Plant n

Data

Inventory Data

Event Data

Inventory Data

Event Data

Initiative Focus

Sound theoretical foundation

Practical application to plant and equipment, including software tools

Fundamentally sound engineering information available to companies to “Engineer” their information management systems

Industry database built upon the platform above

Capitalize on opportunities

Company databases adapt to the platform above

19

Fundamental Taxonomy Relationships

Inventory Record

Application Data Fields

T ag Number

Device Data Fields

Equip ID

-

Equip Descriptors

Operating

Conditions

Operating

Mode

Events

Equipment Function(s)

Failure M ode(s)

Failure

M echanism(s)

Failure

Cause(s)

Relationship Legend

M any to M any

One to M any

M any to One

One to One

The same is true for

Reliability & simulation

Built Upon a Sound Technical Foundation

PERD Has Adopted a Data Tier Structure That:

Eliminates Data Intimidation

Allows more rapid expansion of partial Equipment taxonomies and associated software development

Basic Tier Concept

Tier 1

– Whatever minimal data might exist – Gets people started; generates a useful event record. Pass/fail

Tier 2

– Begins to provide event specifics; population filtering and failure classification

Tier 3

– Top of the “PERD ladder of success”; failure modes

22

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Equipment Groups & Systems

Equipment

Groups

Equipment

Systems

Electrical Fixed Equipment

Circuit Breaker

Contactors

Motor

Relays

Transformer

Cylinder

Heat Exchanger

Piping Circuit

Pressure Vessel

Atm Storage Vessels

Instrumentation

Analyzer

Annunciator

Fire & Gas

Detection

Loop

Sensing Element

Switch

Transmitter

Signal Conditioning

Unit

Control Logic Unit

Pressure Relieving

Devices

Reclosable pressure

Relief Devices

Non-reclosable

Pressure Relief

Devices

Hydraulic

Accumulator

Liquid Seal

Open Vent

Rotating

Machinery

Valves

Agitator

Compressor

Pump

Turbine

Check Valve

Hand Valve

Self-Actuated

Solenoid Valve

Remote Actuated

Expandable

Inventory Data Tier Concept

Tier 1

Location Address (e.g. Plant, tag, etc.)

Equipment Group (e.g. Instrumentation)

Equipment System (e.g. Transmitter)

Comments *Equip Group

*Equip System

*Tag Number

*Equip ID

PL_Equip_Grp

PL_Equip_Sys

Equipment

Type & Subtype

Example

Equipment

Group

Pressure Relieving

Devices

Equipment System

Reclosable pressure relief devices

Non-reclosable pressure relief devices

Hydraulic accumulator

Liquid seal

Open vent

Equipment Type

Equipment Subtype

Pressure Relief Valve

(Spring Loaded)

Pilot Operated Relief

Valve

Conservation Vent

Self-Closing Manhole

Cover

Rupture Disk

Explosion Vent

Blow-off Man-way

Rupture Pin

Buckling Pin

Weak Gauge Hatch

Fusible plug

Weak shell to roof seam

PL_REL_SubType

Conventional

Balanced Bellows

Balanced Bellows With

Auxiliary Balanced Piston

25

Inventory Data Tier Concept

Tier 2

All tier 1 data

plus following

user chooses to enter data

Equipment Type (e.g. Differential

Pressure)

Equipment Subtype (e.g. Level)

Manufacturer

Model Number

Output Signal or Set Point (As applicable to equipment)

Transmitter Type

Transmitter

Subtype

Manufacturer

Model Number

Output Signal

Set Point

PL_Equip_Type

PL_Equip_SubType

PL_Mfr_Equip

PL_Equip_Sig_Out

PL_Equip_Set_Point

Whichever field is applicable

Inventory Data Tier Concept

Tier 3

All tier 1 data

Equipment type

Equipment subtype

Plus additional tier 2 and / or 3

data user chooses to enter

Possible to achieve level of a complete equipment specification

Event Data Tier Concept

All Events require

Linkage to tracked equipment

Event date (and time if applicable)

Tier 1

Data showing a failure has occurred

Tier 2

Data sufficient to infer whether failure was “Dangerous” or

“Safe”

Tier 3

Data sufficient to infer true failure modes

User decides what event data to track!!

Event data tracked determines what level of inference is achievable.

Relief Valve Proof Test Example

29

Getting Started

Upon Joining as a Full Participant

PERD provides the software & initial help to companies loading the software onto their company server

PERD provides initial help and guidance allowing you to

contribute whatever data you have,

enabling companies to quickly get involved and begin accruing benefits

Company data contribution means access to aggregated anonymous industry data and a path to continuous improvement

30

Helping Hand Work Process

– Getting Started

Ad Hoc Data Acquisition & Analysis

Existing CMMS or other Info Mgmt

System

Company downloads data

Company submits data to

CCPS PERD

PERD

Performs

Data Map

PERD translates data & populates PERD compatible files

PERD

Guidance

Helping Hand Work Process

PERD Imports

Data & Manages

Dataset

PERD Aggregates

Data

(Multiple Data

Subscribers)

PERD Anonymizes

Data

Data Analysis

31

Immediate Benefits

Access to work process knowledge needed to achieve company goals

Facilitates moving to data farming (low cost) work process rather than data mining (high cost) activity

Access to fundamental technical information that documents specific data user needs to:

Filter inventory data for populations of interest

Infer failure modes of interest

Enables maximization of benefits from enterprise systems (eg SAP,

Maximo, Matrikon, Meridian, etc.)

Provides pre-engineered solutions that can be implemented cost effectively

Best available info transfer between engineering and programmers

32

On-Going Work Process

On Going Data Acquisition & Analysis

Existing CMMS or other Info Mgmt

System

Company downloads data in compatible format

Company

Documents Quality

Plan

Quality Process

Company submit data to CCPS PERD per quality plan

PERD import data into industry database

PERD Aggregates data from

(Multiple Data

Subscribers)

PERD makes data anonymous

33

Long Term Benefits

Data Harvesting per Defined Quality Plans Provide:

Operating company database capable of achieving proven in use data for safety and reliability analysis

Data Contribution to PERD Facilitates

Operation of industry database

Industry benchmarking

Statistical analysis by true experts due to best data available to support their research

Data available for improved reliability and risk analysis

On going continuous improvement via reliability growth

34

Why Join PERD?

PERD enables user companies to leverage existing IT and

MI systems to collect and submit data resulting in:

Improved Reliability

Industry benchmarking

Identification of “low hanging fruit” for immediate impact

Minimization of unforeseen losses

Increased Effectiveness for

Information Systems Technology

Reliability & Quantitative Risk Assessments

Regulatory Compliance

For a small financial investment and minimal data.

35

You would join…

Full Participants

o

Air Products

o

Chevron

o

DNV

o

Dow Chemical

o

DuPont

o

FM Global

Subscribers & Volunteers

o

Exida

o

Rosemount

o

Savannah River Site

o

Sis-Tech

o

TMC

36

Getting Started.

Join as a Full Participant

Benefits of Full Participant Status:

PERD provides the software & initial help to companies loading the software onto their company server

PERD provides initial help and guidance allowing you to

contribute whatever data you have,

enabling companies to quickly get involved and begin accruing benefits

Company data contribution means access to aggregated anonymous industry data and a path to continuous improvement

Networking with industry experts involved with the PERD project.

37

In Summary

PERD provides you a roadmap to improved performance whereby you can

Improve Information Systems Effectiveness

Create Value

Minimize unforeseen losses

Improve Regulatory Compliance Effectiveness

Enroll Now!!

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For More Information Contact

Dave Belonger

– CCPS PERD Staff Consultant

609-654-4914 dbelonger@verizon.net

Gene Meyer

– Chairperson

Dow Chemical

(989) 638-4064 grmeyer@dow.com

Hal Thomas

– Technical Consultant exida

610-481-9681 thomashw@exida.com

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