Availibility, Reliability
& Maintainability
EPCONSULT has extensive expertise in reliability,
availability and maintainability (RAM) analysis – including
projects that involved RAM analysis for onshore processing plants,
offshore topsides and onshore and offshore export systems.
RAM analysis is typically used to predict the performance of process
and transportation systems and to provide a basis for the optimization
of such systems. The primary performance indicator is availability,
which is the fraction of time that the system is fully functional.
In the concept phase, it can aid concept selection, and subsequently,
RAM analysis can inform front end engineering and detailed design
decisions. Generally, a complex process facility is divided into
a number of subsystems. Those facilities identified as having the
greatest influence on availability can be investigated in more detail
and design changes made to optimize performance.
We use commercial software for performing RAM analysis, using either
Monte Carlo simulations or analytical methods. Analytical methods
for RAM analysis make the simplifying assumption that failure and
repair times are exponentially distributed. Monte Carlo methods
allow any probability distributions to be used to describe failure
and repair times. Monte Carlo approaches also allow more complex
interactions between the components of the system to be considered.
The Monte Carlo approach involves repeatedly sampling times to failure
and repair from the selected failure and repair probability distributions.
The performance of the system over many lifetime cycles is simulated
to obtain a statistical estimate of system parameters such as availability.
We are able to link RAM analysis with process simulation. In this
way we deal with situations where part of a system might go down
and a reduced throughput can be calculated and taken into account
in the availability computation. The varying production profile
over the field life can also be considered.
We can model all components from the reservoir through to the delivery
point.
Fault Tree Analysis
Fault tree analysis (FTA) is a method of calculating the probability
of an event from the probabilities or frequencies of its causal
events. It can be applied in a wide variety of ways, some of which
include:
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To calculate the reliability of a system that has to operate
on demand, e.g. quick release mechanisms, emergency shutdown
systems, firewater systems and high integrity pressure protection
systems (HIPPS) |
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To calculate reliability of components such as valves and
connectors from reliability data relating to their component
parts |
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To calculate the likelihood of a particular hazardous scenario
in terms of the likelihoods of equipment failures and human
errors leading up to it |
FMEA/FMECA
EPCONSULT has in-depth experience in conducting
Failure Modes and Effects Analysis (FMEA) and FMECA (Failure Modes,
Effects and Criticality Analysis). We have applied FMEA/FMECA techniques
to the evaluation of a diverse range of hardware such as valves,
collet connectors, FlexJoints®, diverless repair systems and
tanker loading buoys.
An FMEA identifies failure modes, their causes and effects, the
safeguards already incorporated and the potential additional measures
that could be considered. In addition, an FMEA includes a qualitative
assessment of the severity and probability of occurrence of each
failure mode.
An FMECA is similar to an FMEA, except that the severity and probability
of occurrence of each failure mode are assessed quantitatively rather
than qualitatively. These analyses are presented in a spreadsheet
format. Traditionally, the spreadsheet was filled out directly,
and it was always difficult to be sure whether the study was truly
systematic. However, EPCONSULT has developed a highly structured
approach to the performance of FMEA/FMECA that increases confidence
that important issues have been captured. This is achieved by carrying
out a number of preliminary steps, including the preparation of
a component relationship diagram, a function net for each system
function and a failure net for each system failure mode. All data
are input into the relevant diagrams and finally the FMEA/FMECA
spreadsheet is generated automatically by software from the various
diagrams.
FMEA/FMECA can be applied as a precursor to a RAM/FTA Analysis
or a Quantitative Risk Assessment (QRA), or as a complete or standalone
study.
Safety Integrity Level (SIL) Verification
EPCONSULT has extensive experience in the assessment
of safety instrumented systems in accordance with international
standards IEC 61508 / 61511 and US standard ANSI/ISA S84.01. Safety
Integrity Levels (SIL) levels are identified in a SIL assessment,
performed in a team based study with a multi-disciplinary team led
by a SIL Facilitator . The SIL levels that have been identified
define the required probability of failure of the safety instrumented
functions in the system. A SIL verification assessment makes use
of different qualitative and quantitative reliability techniques
(including FMEA / FMECA, FTA, RAM) to verify that the reliability
requirements for a safety instrumented system, defined by the SIL
levels for the different safety instrumented functions of the system,
are met.
Reliability Data Processing
EPCONSULT has expertise in reliability data processing
(RDP) studies. Typically this involves developing reliable new devices
for use in the oil and gas industry including developing confidence
in the reliability of the calculated availability.
The purpose is to systematically study the recurring failures data
of a product to determine the pattern of the failures, the causes
of failures, the underlying time-to-failure distribution and the
associated stress levels. The failure data could be gathered from
field service failures or failures in a testing laboratory.
The main results from RDP include the failure rate, the mean life,
the reliability (or failure probability) of components, equipment
and systems and their associated confidence limits at desired confidence
levels. The RDP study can also assess the effectiveness of a client's
data collecting system.
Understanding the reliability performance of the product is critical
for decision making, for example, choosing the right vendor, optimizing
the life cycle cost, applying the correct burning-in strategy, etc.
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