PERD
A discussion with the API Subcommittee on
Instruments and Control Systems
23 April 2012


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


AICHE

CCPS, Center for Chemical Process Safety

PERD, Process Equipment Reliability Database
• Participants
» Members and Users

A subscription-based project with CCPS.
3

•
Introduction
•
Alignment
•
Organization
•
Goal
•
The solution
•
Details
•
Results
•
Discussion
4

 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

 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

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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

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

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

 Practical approach and Consistent work processes for data collection
 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

 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
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 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
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 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.
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 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

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

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
Company 2
Database
Company n
Database
Plant 1
Data
Plant 2
Data
Plant n
Data
Inventory Data
Event Data
Inventory Data
Event Data

 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
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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

 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
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23
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

 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
Group
Pressure Relieving
Devices
Equipment System Equipment Type
Equipment Subtype
Reclosable pressure relief devices
Pressure Relief Valve
(Spring Loaded)
Non-reclosable pressure relief devices
Hydraulic accumulator
Liquid seal
Open vent
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
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 Tier 2
 All tier 1 data plus following data user chooses to enter
 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

 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

 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.

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 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

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

 Access to fundamental technical information that documents specific data user needs to:
 Filter inventory data for populations of interest
 Infer failure modes of interest
 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
 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 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

 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

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.
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o Air Products o Chevron o DNV o Dow Chemical o DuPont o FM Global
o
o
o
o
o
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 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

 PERD provides you a roadmap to improved performance whereby you can
 Improve Information Systems Effectiveness
 Create Value
 Minimize unforeseen losses
 Improve Regulatory Compliance Effectiveness
38

 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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