With the operational drive for increased plant safety, environmental compliance
and profitability there is a clear need for owners and operators to ensure that
their methods and strategies for plant asset maintenance are optimised. Central
to this requirement is a recognised need for:
||Systematic and auditable company-wide and plant-wide management
processes which can be benchmarked against best practice
||Consistent technical approaches for assessment and subsequent
safe and economic planning of inspection and maintenance
In some cases these issues are linked such that the development of optimum
inspection and maintenance plans will be strongly influenced by the quality
and comprehensiveness of management processes. However, even good management
processes and associated manuals do not necessarily mean that the risk of failure
or plant availability loss is reduced or indeed, that there is justification
in increasing maintenance intervals. In fact, the relationship between the effectiveness
of the various management systems and the optimum inspection and maintenance
strategy is often complex and cannot always simply be factored into the risk
calculation to establish the inspection or maintenance plan. Both of the above
needs are therefore best dealt with by means of a phased approach which aims
to address each in turn. In addition it can be argued that a phased process
is more cost-efficient since findings in the initial phase can be used to prioritise
or focus efforts in the subsequent phase.
The Asset Maintenance Optimisation System (AMOS) has been developed to meet
this requirement. The AMOS program is aimed at improving plant performance by
focussing attention on the effectiveness of inspection and maintenance programmes.
Experience indicates that best practice operators generally spend less on inspection
and maintenance but still avail themselves of a good operational performance
and safety record. This emphasises the driver for the adoption of such a program.
The first step in any improvement program is to benchmark the current status
of the plant in terms of its performance and maintenance process effectiveness.
Once this has been established, programmes can be developed to address any quality,
procedural or skills deficiencies. This is followed by a focussed assessment
of plant condition related risks to safety and availability.
Accordingly therefore, the first phase of AMOS incorporates a performance benchmarking
exercise and management processes audit. The second phase draws upon the first
phase output to plan selective implementation of risk-based inspection and maintenance
planning (RBI) tools. The latter addresses failure risks and safe run lengths
on a detailed equipment basis compliant with methods set out in API
RP 580 (2002).
The AMOS program includes formal approaches for first and second phases. For
the second phase TWIs RBI software tool, RISKWISE is shown for illustrative
AMOS PHASE 1: BENCHMARKING AND MANAGEMENT PROCESSES AUDIT
Typically plant performance is influenced by the quality and effectiveness
of a companys management processes. The primary management procedures
may be developed at a corporate level but the implementation is largely dependent
on the local management. Establishing the plant safety and availability risk
will therefore require evaluation against best practice by consideration of:
||Historical performance relative to generic industry norms
||Asset management processes and programmes
||How well these programmes are implemented
These areas are detailed below:
Performance review: This first requires a plant-level or unit-level
review of plant performance including:
||Identifying existing and potential safety, availability and
reliability issues and critical plant items
||Establishing future performance requirements
Following this, a preliminary assessment of equipment failure rate relative
to industry experience needs to be conducted. For process plants generic failure
frequencies, e.g., collated by API (API RP 581, 2008).
are used. For utilities plant such as boilers and turbines, (NERC,
1995). Can provide generic failure experience. The output is used to highlight
areas of concern requiring corrective action focus if future performance targets
are to be achieved.
Management programme audit: The aim of asset management programmes is
to ensure that component integrity and plant reliability are economically maintained
over the life of the plant. This basically requires that information about the
plant, its design, how it is operated and the impact of operation and maintenance
on its condition is gathered and assessed by people with appropriate competencies
to ensure safe and reliable operation. The work process associated with each
programme should result in the correct actions being taken at the appropriate
times to meet this requirement. Each management programme should have a series
of attributes that define the core actions that need to be taken or the procedures
that should be present in order to ensure that all safety and reliability requirements
For each plant area there are a number of activities or processes that should
be active within a comprehensive best practice plant maintenance and integrity
management system. Each aspect or attribute of a particular program, activity
or process will have a role to play in controlling the condition of the plant.
The effectiveness or worth of a particular technical management program can
therefore be measured relative to a comprehensive 'best practice' programme
by considering plant area attributes and associated metrics. If for example
there are deficiencies in the programme, e.g. inadequate or omitted attributes
or lack of applicability to a plant area then clearly the likelihood of problems
arising will be higher than if all aspects of the best practice program are
Existing management programmes are therefore reviewed against best practice
programme attributes and metrics to identify any shortcomings or deficiencies.
The results are typically presented in the form of charts which portray the
'adequacy' score for each plant area or programme. The results are captured
in formal manner in order to monitor the improvements as corrective actions
Programme implementation audit: It is important that the evaluation
of the significance of inspection findings or operational deviations are taken
account of by a Competent Person i.e., someone with considerable training and
experience in that area of plant and the damage mechanisms that can affect it.
Clearly the above is what should be happening for each major component and plant
area. However in practice these procedures are frequently not comprehensively
applied or indeed can be omitted altogether. The degree of application of such
procedures will give some indication of the level of risk of a major failure
occurring on that component.
This audit will essentially involve a series of questions designed to establish
precisely what maintenance and inspection is or is not being carried out. The
results are again captured in formal manner to monitor and update the scores
as corrective actions are taken.
Phase 1 output: The output of the Phase 1 benchmarking exercise is formal
documentation detailing the performance review and management audit findings
and in particular, the quality, procedural and skills development needs as well
as specific corrective action recommendations.
|| Example of plant area attributes and metrics (Area: Engineering)
|| Example of programme implementation audit questions
|The results for each functional or plant area are recorded
and used to focus or de-focus efforts in Phase 2
The aim is to record the current status and facilitate continuous monitoring
of improvements into the future.
Recommended actions will address the priority plant areas for focussed implementation
of risk-based inspection and maintenance planning (RBI) software in Phase 2.
A Phase 1 application example for utilities plant audits given below.
Example application-utilities plant: The primary management processes
to be addressed can be divided into functional areas and plant areas:
||Functional areas include: Engineering, operations,
maintenance, performance, training
||Plant areas include: Boiler, turbine and generator,
electrical, auxiliary, civil structures
||For each area the process requires the definition of best
practice attributes and the associated metrics
||Examples for the engineering function and boiler plant are
given in Table 1 and 2, respectively
AMOS PHASE 2 - IMPLEMENTATION OF RISK-BASED INSPECTION AND MAINTENANCE PLANNING
The process of plant asset optimisation is increasingly incorporating risk
assessment followed by identification of optimum inspection and maintenance
measures to selectively mitigate risks to levels consistent with target maintenance
outage plans. This enables focussing of inspection resources on equipment items
which have the greatest impact on plant availability and safety if not managed
In this phase a detailed equipment item-by-item risk-based inspection and maintenance
(RBI) planning exercise is carried out including:
||Evaluation of inspection history
||Equipment damage mechanism audit
||Failure probability and consequence analysis
||Run-length and forward inspection/maintenance plan for each
The above is facilitated using risk-based inspection and maintenance planning
software. The implementation of Phase 2 is illustrated below using TWIs
RISKWISE software: TWIs RISKWISE software offers a management
support tool, which can be used to capture the decision making process and thereby
formalise a fully traceable and auditable consistent methodology of inspection
and maintenance planning. RISKWISE assesses the failure risk:
P(t) is the failure probability or likelihood; C is the failure consequence-safety
as well as business interruption:
p(t) is the equipment failure rate or probability of failure for each equipment
item obtained from one or more of the following: generic failure frequency for
given equipment (API RP 581, 2008); damage or remaining
life models; experienced based rules; trended damage measurements (e.g., corrosion);
ΣPfi is the sum of associated probability factors contributing to the
failure probability, e.g., current condition, effectiveness of inspection, severity
of operation, operational stability, etc.
ΣCfi is the sum of associated consequence factors including: energy release;
explosion potential; toxic release; consequential damage; effect on unit availability/production;
threat to personnel, community and environment.
RISKWISE outputs failure risk over three time frames which is used to compute
the safe run length through a run-length index (RLI) which is a risk-based indication
of the acceptable run period between inspections.
Based on the estimated remaining life, the RLI accounts for uncertainties in
equipment condition and future operation. A schematic illustrating how the RLI
relates to such uncertainties.
The software automatically outputs a risk fingerprint for each
unit in the form of a risk matrix displaying the risk of failure and computing
the associated run length indices across all equipment items. The software uses
this to deliver an optimised inspection and maintenance plan for each equipment
item to assist in planning shutdown workscopes as well as scheduling future
inspections and risk mitigation actions.
The implementation of RISKWISE includes interfacing with plant inspection and
maintenance data storage or CMMS systems. This significantly speeds up the implementation
RISKWISE comprises software suites covering oil and gas and chemicals process
plant, utility boilers and turbines, storage tanks and pipelines.
Phase 2 output: The output of Phase 2 is a 'living' risk management
software tool for optimised planning of inspection and maintenance fully integrated
with plant-wide data storage or CMMS systems.
Several implementation examples are summarised below for utility boilers, process
units and pipelines
Example application: Utility boiler: The study was performed on a boiler
with the following characteristics:
||270 MW conventional steam plant
||Benson type boiler design based on TRD 301 for cyclic operation
||Commissioned in 1980 and fuelled by natural gas
||Superheater outlet rated design 555C at 200 bar
||Started cyclic operation in 2005
The primary objectives were to extend boiler inspection interval to 30 months
and improve unit availability.
RISKWISE for Boilers was implemented using both manual and automated functions
to output risk factors and run-length indices (RLI) for all boiler equipment
Risk mitigation actions were planned on the 14 items having RLI less than 30
An outage inspection including the planned risk reduction actions was carried
out. This was followed by post-outage re-running the software to output risk
and RLI results based on all outage inspection findings.
Risk mitigation was achieved by increased inspection coverage on high risk
items, only two items remained with a RLI less than 30 months. These were related
to economiser vibration and evaporator attachments. Control and modification
actions were, respectively planned to mitigate these at a subsequent outage
to extend the overall outage interval to 30 months, which was subsequently accepted
by the regulator.
The benefits of the study centred on: extended inspection interval saving one
outage every 30 months; immediate inspection cost saving by eliminating 30%
of inspection activities within next outage through exempting components with
safe inspection interval >48 months; reducing unplanned outage rate by conducting
risk mitigation actions on high risk components (eliminating 5% availability
loss due to forced outages).
Example application: Hydrotreater unit: The example study comprised
a pilot application of RISKWISE on selected equipment items in a Naphtha Hydrotreater
Unit within an oil refinery. The unit was commissioned in the early 1980s. The
current inspection periodicity for pressure equipment was generally 48 months.
Piping however, was on a 24-month inspection cycle and storage tanks were inspected
every 84 months.
The objectives were to:
||Demonstrate the key steps in the RBI process
||Suggest ways of optimising inspection plans and
||Identify ways of reducing the risk of failure
The RLI was automatically output for each damage mechanism (DM) considered
active within each item of equipment. The DMs are based on API
RP 571 (2003). incorporated within the RISKWISE process plant software.
Where more than one DM exists then the minimum RLI value is output.
The computed RLIs vary from zero to 480 months. In view of the currently adopted
inspection periods given above and subject to process controlled shutdowns and
statutory requirements, there was clearly scope for optimisation
Details of selected equipment items, their damage mechanisms (DM), the risk
audit results, revised inspection plans and the risk mitigation recommendations
are summarised below.
Vapour condenser (Bundle): Carbon steel; 38°C; DMs: Oxygen pitting,
water side; RLI=0 mths (IP= 48 mths), Risk Class: 5A. Resulting Focus/Defocus
proposal: Replace bundle at earliest opportunity (or install air cooler); increased
RLI=48 mths (new Risk Class: 2A).
Charge heater tubes: 9Cr 1Mo steel; 357°C; DMs: Sulphidation, creep,
vanadate attack; RLI=480 mths (IP=48 mths), Risk Class: 1E. Resulting Focus/Defocus
proposal: Relax to visual inspection only at next planned shutdown; unchanged
RLI=48 mths (unchanged Risk Class: 1E).
Feed tank: Carbon steel; 25°C; DMs: general and pitting corrosion;
RLI = 84 mths (IP = 84 mths); Risk Class: 2B. Resulting Focus/Defocus proposal:
Internally coat tank floor with epoxy resin at next opportunity; increased RLI=168
mths (new Risk Class: 1B).
Reactor: P11 and 12Cr steel; 380°C; DMs: Sulphidation, creep cracking,
hydrogen attack, H+ embrittlement; RLI=90 mths; Risk Class: 2E. Resulting
Focus/Defocus proposal: Increase inspection interval for creep embrittlement
cracking (only) to 96 mths; unchanged RLI=90 mths (unchanged Risk Class: 2E).
Hot separator: Carbon steel, 101°C; DMs: general/pitting corrosion,
HIC, stress corrosion cracking; RLI=90 mths (IP=48 mths); Risk Class: 2E. Resulting
Focus/Defocus proposal: Defer next internal inspection by 48 mths; external
UT (only) at normal inspection interval (48 mths); unchanged RLI=90 mths (unchanged
Risk Class: 2E).
Feed line: Carbon steel, 24°C; DMs: general/pitting corrosion; RLI=240
mths (IP=24 mths); Risk Class: 1D. Resulting Focus/Defocus proposal: Increase
external UT interval to 48 mths; unchanged RLI=240 mths (unchanged Risk Class:
Combined feed exchanger (Bundle): Carbon steel, 170°C; DMs: General/pitting
corrosion; RLI=48 mths (IP=48 mths); Risk Class: 2E. Resulting Focus/Defocus
proposal: Replace bundle in, e.g. Type 321 SS; increased RLI=180 mths (unchanged
Risk Class: 2E).
The major findings and benefits of the study were as follows:
||There was scope for reduction in shutdown inspection for approximately
70% of equipment
||Incremental run-length extension was feasible after selected
The study highlighted areas where imminent risk mitigation was needed (e.g.,
replacement of vapour condenser bundles).
Example application: Oil and gas pipelines: The approach involves the
phased implementation of a risk management programme to provide decision support
to the client on planning inspection, repair or replacement of pipeline elements
of an ageing pipeline network. The work uses RISKWISE for Pipelines
for risk assessment and ranking of pipeline network elements based on information
available. This is followed by a focussed inspection programme, the results
of which are fed back into RISKWISE for re-assessment of risk/remaining life
distributions and risk mitigation actions. Depending on the condition data available,
high risk areas are then subject to a quantitative probabilistic evaluation
program (TWIs LIFEWISE program) which will allow future maintenance and
replacement strategies to be refined.
The assessment is carried out to the requirements of ANSI/ASME
B31.8S (2005). which covers the risk assessment, inspection and integrity
assessment of gas pipelines. NACE RP0502 (2002) will be
applied in areas not covered by ASME.
Example information required includes:
||As-built design data: pipeline data sheets, drawings, geographical
layout (GIS), etc.
||Pipeline operating conditions flow rates, global pressures
||Historical inspection data for in-service external inspection
||Results of intelligent pigging if used
||Analysis of scales and debris
||Corrosion monitoring summaries if any
||Details of cathodic protection
||Results of external UT scanning and internal cable operated
||Failure/leakage and repair history
The information is used to populate the initial RISKWISE data input followed
by segmenting the pipelines and characterising the following failure likelihood
and failure consequence factors for each segment:
||Current condition: Prior internal (pigging) and external inspection
data, age of lines, leak history
||Failure likelihood due to internal and external corrosion:
Pressure, flow conditions, coatings, coating condition, geographical location,
ground conditions, soil type, depth, cathodic protection, climatic conditions,
||Effectiveness of inspection: Comprehensiveness of pigging,
external inspection, nature of corrosion damage
||Third party damage potential
||Potential for ground movement
||Operation in relation to design limits
||Fire and explosion damage potential
||Effect of failure on distribution, time to rectify a leak
||Threat to personnel and environment
||Adequacy of safety systems
The output of the risk analysis provides a risk-focussed inspection plan.
The inspection programme should include intelligent pigging (where possible),
direct assessment methods including excavation visual examination (e.g., coating
condition) and UT thickness measurements will also be performed in selected
high criticality areas.
The overall inspection workscope includes:
||Identifying locations for cathodic protection, bell-hole excavation,
Soil resistivity assessment
||Above-ground pipeline inspection
||Effectiveness assessment of existing cathodic protection using
close interval potential survey (CIPS). Direct current voltage
gradient (DCVG) will also be used to provide an assessment of coating condition
Results of the inspection are fed back to RISKWISE to re-assess and refine
the initial risk assessment and run length index (RLI) evaluations and provide
initial output of forward inspection and maintenance plans.
High risk/low RLI areas are subject to further refinement by means of a quantitative
probabilistic analysis using TWIs LIFEWISE program which is based on the
ASME SRRA (structural reliability and risk assessment) code. The LIFEWISE program
incorporates a generic remaining life rule which accepts uncertainty distributions
in damage/thinning status, materials data/corrosion rates and operating conditions.
The distributions are integrated in a probabilistic analysis to compute failure
probability against forward time. The probability can be combined with the failure
consequence cost to give risk verses time in monetary value terms. This enables
pipeline maintenance or replacement schedules to be optimised in terms of net
present value considerations.
Elements of the above methodology are illustrated in the example study below.
The study was aimed at establishing the inspection/maintenance focus and the
remaining life of oil production, water injection and flare lines in two Oil
Fields: Field A: 180 lines (600 km); Field B: 101 lines (350 km).
The main damage mechanisms were: CO2, H2S, O2,
A quantitative probabilistic assessment was performed on some lines. This illustrates
the extension in assessed lifetime obtainable by performing inspection compared
with using corrosion modelling only.
The study enabled a pipeline inspection and replacement scheduling plan to
be formalised. Benefits included: deferred capital spend, extended inspection
intervals, minimised risk of business interruption and minimised liability uncertainties.
This study has set out a common process for establishing an optimised O and
regime for various plant types. The AMOS approach divides the process into two
distinct phases separating the benchmarking and management processes from the
equipment level failure risk assessment and maintenance planning. In this way,
the first phase allows prioritisation or focus for implementation of the full
AMOS program. This step-wise approach is considered to be a cost-efficient way
of achieving operational excellence.