scholarly journals Assuring the Probability of Failure on Demand of a Safety Instrumented System without Full Proof Testing

2016 ◽  
Vol 49 (9) ◽  
pp. 279-285 ◽  
Author(s):  
John Rielly
Keyword(s):  
Probability Of Failure ◽  
On Demand ◽  
Proof Testing ◽  
Full Proof

The Effects of Maintenance Actions on the Average Probability of Failure on Demand of Spring Operated Pressure Relief Valves

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
Julia V. Bukowski ◽  
William M. Goble ◽  
Robert E. Gross ◽  
Stephen P. Harris
Keyword(s):  
Probability Of Failure ◽  
Pressure Relief ◽  
Periodic Inspection ◽  
On Demand ◽  
Plant Safety ◽  
Safety Integrity Level ◽  
Proof Testing ◽  
Average Probability ◽  
Pressure Relief Valves ◽  
Inspection And Maintenance

The safety integrity level (SIL) of equipment used in safety instrumented functions is determined by the average probability of failure on demand (PFDavg) computed at the time of periodic inspection and maintenance, i.e., the time of proof testing. The computation of PFDavg is generally based solely on predictions or estimates of the assumed constant failure rate of the equipment. However, PFDavg is also affected by maintenance actions (or lack thereof) taken by the end user. This paper shows how maintenance actions can affect the PFDavg of spring operated pressure relief valves (SOPRV) and how these maintenance actions may be accounted for in the computation of the PFDavg metric. The method provides a means for quantifying the effects of changes in maintenance practices and shows how these changes impact plant safety.

scholarly journals Genetic Algorithm Optimization Model for Determining the Probability of Failure on Demand of the Safety Instrumented System

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Ahmed H. Aburawwash ◽  
Moustafa Mohammed Eissa ◽  
Azza F. Barakat ◽  
Hossam M. Hafez
Keyword(s):  
Genetic Algorithm ◽  
Accurate Determination ◽  
Probability Of Failure ◽  
System Structure ◽  
Control Element ◽  
Algorithm Optimization ◽  
On Demand ◽  
Uncertainty Sources ◽  
Iec 61508 ◽  
Proposed Model

A more accurate determination for the Probability of Failure on Demand (PFD) of the Safety Instrumented System (SIS) contributes to more SIS realiability, thereby ensuring more safety and lower cost. IEC 61508 and ISA TR.84.02 provide the PFD detemination formulas. However, these formulas suffer from an uncertaity issue due to the inclusion of uncertainty sources, which, including high redundant systems architectures, cannot be assessed, have perfect proof test assumption, and are neglegted in partial stroke testing (PST) of impact on the system PFD. On the other hand, determining the values of PFD variables to achieve the target risk reduction involves daunting efforts and consumes time. This paper proposes a new approach for system PFD determination and PFD variables optimization that contributes to reduce the uncertainty problem. A higher redundant system can be assessed by generalizing the PFD formula into KooN architecture without neglecting the diagnostic coverage factor (DC) and common cause failures (CCF). In order to simulate the proof test effectiveness, the Proof Test Coverage (PTC) factor has been incorporated into the formula. Additionally, the system PFD value has been improved by incorporating PST for the final control element into the formula. The new developed formula is modelled using the Genetic Algorithm (GA) artificial technique. The GA model saves time and effort to examine system PFD and estimate near optimal values for PFD variables. The proposed model has been applicated on SIS design for crude oil test separator using MATLAB. The comparison between the proposed model and PFD formulas provided by IEC 61508 and ISA TR.84.02 showed that the proposed GA model can assess any system structure and simulate industrial reality. Furthermore, the cost and associated implementation testing activities are reduced.

Probability of failure on demand of safety systems: impact of partial test distribution

2012 ◽  
Vol 226 (4) ◽  
pp. 426-436 ◽  
Author(s):  
Florent Brissaud ◽  
Anne Barros ◽  
Christophe Bérenguer
Keyword(s):  
Probability Of Failure ◽  
Test Time ◽  
Time Interval ◽  
System Failures ◽  
On Demand ◽  
Component Failure Rates ◽  
Safety Systems ◽  
The Impact ◽  
Architecture Component ◽  
Approximate Equations

In accordance with the IEC  61508 functional safety standard, safety-related systems operating in a low demand mode need to be proof tested to reveal any ‘dangerous undetected failures’. Proof tests may be full (i.e. complete) or partial (i.e. incomplete), depending on their ability to detect all the system failures or only a part of them. Following a partial test, some failures may then be left latent until the full test, whereas after a full test (and overhaul), the system is restored to an as-good-as-new condition. A partial-test policy is defined by the efficiency of the partial tests, and the number and distribution (periodic or non-periodic) of the partial tests in the full test time interval. Non-approximate equations are introduced for probability of failure on demand (PFD) assessment of a Moo N architecture (i.e. k-out-of- n: G) systems subject to partial and full tests. Partial tests may occur at different time instants (periodic or not) until the full test. The time-dependent, average, and maximum system unavailability (PFD(t), PFDavg, and PFDmax) are investigated, and the impact of the partial test distribution on average and maximum system unavailability are analysed, according to system architecture, component failure rates, and partial test efficiency.

scholarly journals Unavailability of K-out-of-N: G Systems with non-identical Components Based on Markov Model

2019 ◽  
Vol 2 (1) ◽  
pp. 25-35
Author(s):  
Ayodeji Akinsoji Okubanjo ◽  
Olasunkami oriola Akinyemi ◽  
Oluwadamilola Kehinde Oyetola ◽  
Olawale omopariola Olaluwoye ◽  
Olufemi Peter Alao
Keyword(s):  
Markov Model ◽  
Probability Of Failure ◽  
Process Industry ◽  
Redundant System ◽  
System Architectures ◽  
On Demand ◽  
Proposed Model ◽  
Challenging Tasks ◽  
Average Probability ◽  
Analytical Formulas

The process industry has always been faced with the challenging tasks of determining the overall unavailability of safety instrumented systems (SISs). The unavailability of the safety instrumented system is quantified by considering the average probability of failure on demand. To mitigate these challenges, the IEC 61508 has established analytical formulas for estimating the average probability of failure on demand for K-out-of-N (KooN) architectures. However, these formulas are limited to the system with identical components and this limitation has not been addressed in many researches. Hence, this paper proposes an unavailability model based on Markov Model for different redundant system architectures with non-identical components and generalised formulas are established for non-identical k-out-of-n and n-out-of-n configurations. Furthermore, the proposed model incorporates undetected failure rate and evaluates its impact on the unavailability quantification of SIS. The accuracy of the proposed model is verified with the existing unavailability methods and it is shown that the proposed approach provides a sufficiently robust result for all system architectures.  

Probabilistic Aspects of Designing with Ceramics

1977 ◽  
Vol 99 (4) ◽  
pp. 617-630 ◽  
Author(s):  
A. Paluszny ◽  
W. Wu
Keyword(s):  
High Temperature ◽  
Design Methodology ◽  
Slow Crack Growth ◽  
Statistical Treatment ◽  
Turbine Rotor ◽  
Probability Of Failure ◽  
Material Strength ◽  
Time To Failure ◽  
Brittle Behavior ◽  
Proof Testing

The paper reviews the design methodology for brittle materials which is being developed under the Ford/ARPA contract. Theoretical aspects of designing with high-temperature ceramics are discussed and demonstrated on a turbine rotor system. Statistical treatment of brittle behavior, based on Weibull’s model, is reviewed and relations for predicting probability of failure and material strength requirements for complex ceramic structures are presented. Reliability considerations, uncertainty of predictions, and need for proof testing are discussed. Similarly, a probabilistic treatment of time to failure of a typical turbine structure in the presence of slow crack growth is presented using fracture mechanics and Weibull relations.

Rams Analysis for Different XT Technologies

2021 ◽  
Author(s):  
Markus Glaser ◽  
Tobias Winter
Keyword(s):  
Probability Of Failure ◽  
Hydraulic Actuator ◽  
System Architectures ◽  
Electric Actuator ◽  
Availability Analysis ◽  
On Demand ◽  
Roller Screw ◽  
Critical Components ◽  
Valve Operation ◽  
Reliability And Availability

Abstract This paper analyses the probability of failure on demand of different subsea christmas tree actuation principles and their related control system architectures. The all-electric technology has limited or insufficient field data available. This means that the reliability and availability analysis is based on theoretical analysis from data provided in reliability handbooks for mechanical and electronic components. The analysis includes the probability of failure on demand to isolate the well and the availability of each equipment type until a first failure causes the need for repair. The following different actuator and system designs were chosen for this analysis: – Spring based hydraulic actuator – Spring based electric actuator – Electric power screw actuator – Electric planetary roller screw actuator All Electric Systems (except the spring based electric actuator) utilize a battery to provide the energy for the valve operation. The reliability analysis provides detailed information about the major contributors that limit the reliability of the actuators and systems. With this knowledge, qualification activities can focus on the improvement of the reliability of the critical components and the actuator elements within the system. The power screw actuator and the corresponding system provides the best reliability and availability compared to other systems. The electric with spring design provides better results than the hydraulic with spring design. Generally, the battery-based systems provide a better reliability than spring-based designs. The most critical elements are the mechanical springs, sealings, brakes and the spindle mechanisms. Another aspect is the analysis of an optimized operation strategy in order to utilize the redundant components to improve the availability and reduce the number of interventions by analysis of the second and third failure in the system.

Probability of Failure on Demand in IEC 61508

2004 ◽  
pp. 2404-2409
Author(s):  
Tsuneharu Shimodaira ◽  
Isamu Takeda ◽  
Koichi Suyama ◽  
Yoshinobu Sato
Keyword(s):  
Probability Of Failure ◽  
On Demand ◽  
Iec 61508

UNCERTAINTY IN BINOMIAL FAILURES AND DEMANDS WITH APPLICATIONS TO RELIABILITY

1996 ◽  
Vol 03 (01) ◽  
pp. 43-57 ◽  
Author(s):  
HARRY F. MARTZ ◽  
PAUL H. KVAM ◽  
CORWIN L. ATWOOD
Keyword(s):  
Risk Assessment ◽  
Bayesian Methods ◽  
Prior Distribution ◽  
Real Data ◽  
Probability Of Failure ◽  
Boiling Water Reactors ◽  
Binomial Probability ◽  
Numerical Examples ◽  
On Demand ◽  
Water Reactors

In estimating a plant-specific binomial probability of failure on demand p in probabilistic risk assessment, the corresponding number of binomial demands n or the observed number of failures x (or both) may be uncertain. We present several methods which account for uncertainties in both x and n when using Bayesian methods to estimate p. A beta prior distribution on p is considered. While the methods formally require the use of numerical integration, approximations are provided to implement them in practice. Several numerical examples are used to illustrate the methods, including a real-data example involving commercial nuclear boiling water reactors.

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