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BlockSim 7Software de Confiabilidad de Sistemas, Mantenibilidad, Disponibilidad y Análisis RelacionadosResumen del Producto

ReliaSoft South America  >  Software  >  BlockSim

BlockSim 7Software de Confiabilidad de Sistemas, Mantenibilidad, Disponibilidad y Análisis RelacionadosResumen del Producto

BlockSim 7 proporciona una interfaz gráfica muy sofisticada que ayuda en modelar desde sistemas simples hasta los sistemas más complejos gracias al uso de Bloques de Diagramas de Confiabilidad (Reliability Block Diagrams - RBD's) o Árboles de Fallas (Fault Trees) - ¡ o una combinación de los dos enfoques! El programa calcula después algebraicamente la confiabilidad del sistema y la asignación de confiabilidad óptima basadas en la confiabilidad exacta de la función del sistema. BlockSim proporciona también un motor de simulaciones discretas muy sofisticadas para el uso en el área de confiabilidad, mantenibilidad, desempeño y costos de ciclos de vida y análisis relacionados.

Creación Flexible de Bloques de Diagramas de Confiabilidad (RBD) La interfaz de BlockSim para la creación de Bloques de Diagramas de Confiabilidad es la más intuitiva, flexible y más transparente en la industria.

Una implementación simple de la técnica arrastra-y-suelta le permite a construir Bloques de Diagramas de Confiabilidad tanto para sistemas simples como para los más complejos. Las opciones de configuración incluyen Series, Paralelos, y k-de-n (y en varias combinaciones complejas) más...

o Bloques de Repartición de Carga: En una configuración de repartición de carga, cada bloque soporta un porcentaje de la carga total.

o Bloques de Respaldo: En una configuración de respaldo, los bloques de respaldo están disponibles para activarse en situaciones específicas.

o Bloques tipo Espejo y Multibloques: Proporcionan una versatilidad incrementada mediante la habilidad de simular caminos bidireccionales, el ahorro de tiempo/espacio al ingresar múltiples bloques idénticos, y mucho más...

Capacidad ilimitada de crear y enlazar sub-diagramas con componentes en otros diagramas.

Interfaz gráfica personalizable con la habilidad de exportar gráficas de diagramas.

Plantillas predefinidas y una opción de importar/exportar para ahorrar tiempo y garantizar la coherencia, habilidad para de-activar bloques individuales para análisis de tipo "que pasaría",

Este recurso está disponible también en

Inglés.

                 Versión 7

  BlockSim 7  Nuevo en Versión 7      Folleto (*.pdf)   Resumen       Folleto (*.pdf)  Características      Brochure (*.pdf)  Ejemplos   Demo Gratuito  Actualizaciones  Activación

  Todo el Software  Software de Confiabilidad   Ordene/Precios   Opciones de Licencias   Mantenimiento  Servicio  Entrenamiento  Testimoniales

      Otras Versiones

  BlockSim 6  BlockSim 6 FTI  BlockSim 1.0/1.5

archivos adjuntos, y más...

Características Integradas para Análisis de Árboles de Fallas ¡Ahora integradas en el paquete estándar en la Versión 7!

El análisis de árboles de falla de BlockSim usa todas las puertas FTA (Fault Tree Analysis) y símbolos de eventos que son aplicables a la confiabilidad de sistemas y análisis relacionados (incluyendo AND, OR, VOTING OR, cohibido, Prioridad AND y puertas de tipo Secuencia tanto como eventos de tipo Básico, No-desarrollado, Disparador, Resultante y eventos Condicionales). Adicionalmente, BlockSim permite a usted expandir la capacidad de modelar mediante la introducción de nuevas compuertas lógicas para representar las configuraciones de Repartimiento de Carga y de la Redundancia Respaldo.

Sus proyectos BlockSim pueden incorporar análisis de árboles de falla tanto como diagramas de bloques de confiabilidad, al mismo tiempo en el mismo proyecto. Incluso podrá integrar los Árboles de Falla enlazándolos con los Diagramas de Bloque y viceversa; copiando eventos de un árbol de falla y agregándolos como bloques en un Diagrama de Bloques; y automáticamente convirtiendo los Árboles de Fallas en Diagramas de Bloques.

Resultados/Representaciones Gráficas Exactos de Confiabilidad y Asignación Óptima de Confiabilidad Gracias a un algoritmo exclusivo creado y popularizado por ReliaSoft, BlockSim calcula algebraicamente la función exacta de la confiabilidad del sistema hasta los más complejos sistemas. Los resultados calculados incluyen la Confiabilidad, la Tasa de Fallo, MTTF, Tiempo de Garantía, Vida B(X), representaciones gráficas en formato pdf, representaciones gráficas de Importancia de Confiabilidad, y más... 

Una característica exclusiva de BlockSim, es un modo de ingresar los costos e información sobre la mejora de confiabilidad que se puede lograr para determinar la asignación estratégica más rentable de componentes confiables para llegar a un objetivo de confiabilidad.

Opciones Extensas de Simulación para el Análisis de Sistemas ReparablesLa capacidad de simulación de BlockSim para la mantenibilidad de sistemas reparables es ahora más sofisticada que nunca.

Manutención Correctiva (CM - Corrective Maintenance), Manutención Preventiva (PM - Preventive Maintenance) e Inspección

o Duración de la Manutención y Factores Restaurativos: Especifique distribuciones dependientes del tiempo o de duración fija para acciones de manutención y determine si los equipos serán "como nuevos" o restaurados en menos de 100% por la manutención. ¡Mejorado en la Versión 7! Incluye soporte para el Modelo

Restaurativo Tipo 1 de Kijima. o Políticas de Manutención: Describa las

condiciones bajo cuales el mantenimiento será realizado (por ejemplo: en intervalos fijos, manutención de varios grupos de equipos, etc.).

o Almacenes de Repuestos y Equipos de manutención: Describa las condiciones bajo cuales los repuestos serán obtenidos, las condiciones bajo cuales los equipos de manutención estarán disponibles, también como los costos asociados.

o Ciclo de deberes: Aplique un factor para definir un ciclo de deberes para un bloque que puede experimentar una carga diferente de los otros bloques del diagrama. ¡Nuevo en la Versión

7! Diagramas de Fase: Use el Folio Intuitivo de

Diagramas de Fase de BlockSim para modelar los sistemas que pasan por distintas fases durante su curso de operación. Por ejemplo, algunos componentes de aviones (como los trenes de aterrizaje) operan solo durante las fases de despegue y de aterrizaje durante la misión y otros (como los motores) experimentan una tasa de fallas mas alta gracias a su operación continúa. Solo BlockSim proporciona la habilidad de cambiar completamente la configuración y las propiedades de un componente de una fase a otra. El programa también introduce y apoya el concepto de Fases de Manutención, que permiten modelar escenarios en los cuales un sistema entra en manutención después de haber completado una secuencia específica de fases o omite las fases restantes y empieza directamente la manutención si ocurre una falla. ¡Nuevo en la Versión 7!

Resultados Comprensivos y Representaciones Gráficas: Resultados de manutención y disponibilidad por sistema y/o por bloque incluyendo: Tiempo de Funcionamiento, Periodo de Inactividad, Tiempo Medio hasta la Primera Falla (Mean Time To First Failure MTTFF), Promedio de Disponibilidad, punto de disponibilidad, Punto de Confiabilidad, Número de Fallos, Número de Manutención Preventiva, Número de Inspecciones, Representaciones Gráficas del Sistema Tiempo de Funcionamiento/Periodo de Inactividad, Punto de Disponibilidad contra Tiempo, Punto de Confiabilidad contra Tiempo, y mucho más... ¡Mejorado en la Versión 7! ¡Resultados del Sistema "Puntos" están ahora disponibles!

La simulación también proporciona resúmenes de Costos de Ciclos de Vida, estimaciones de Desempeño, calculación de Manutención Preventiva Óptima, y muchos otros resultados necesarios para hacer decisiones efectivas sobre su sistema.

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A su conveniencia, la información sobre este producto está disponible en varios idiomas...

In English: BlockSim: System Reliability, Maintainability, Availability, Optimization, Throughput, Life Cycle Cost and Related Analyses

En Español: BlockSim: Confiabilidad del Sistema, Mantenibilidad, Disponibilidad, Optimización, Rendimiento, Costes de Ciclos de Vida y Análisis Relacionados

New and Enhanced Features in Version 7

BlockSim 7 provides a sophisticated graphical interface to allow you to model the

simplest or most complex systems using Reliability Block Diagrams (RBDs) or Fault

Trees -- or a combination of both approaches! The software then algebraically

computes exact system reliability results and optimum reliability allocations.

BlockSim also provides a sophisticated discrete event simulation engine for

reliability, maintainability, availability, throughput, life cycle cost summaries and

related analyses. The following new and enhanced features in Version 7 allow you to

perform analyses and simulations that are more powerful and realistic than ever!

Additional Distributions

In addition to the Weibull, mixed Weibull, normal, lognormal and exponential

distributions, BlockSim 7 now supports the generalized gamma, gamma, logistic,

loglogistic and Gumbel distributions. These additional distribution options provide

even more modeling power and flexibility.

Phase Diagrams

You can use BlockSim’s intuitive new Phase Diagram Sheets to model systems that

go through different phases during the course of their operation. For example, some

aircraft components (such as landing gear) operate only during the take-off and

landing phases of a mission and others (such as engines) experience a higher

failure rate during these phases due to higher stress. Likewise, a manufacturing

plant’s production may differ during the day shift and the night shift. To model this

type of situation in BlockSim 7, simply create an RBD to describe the system’s

operation during each phase and use the new Phase Diagram to describe how the

system proceeds through the phases over time.

Exclusively in BlockSim, the Phase Diagram Sheets allow you to completely

change the system configuration and component properties from one phase to

another. In addition, you have the option to define Maintenance Phases to model

scenarios in which a system goes into maintenance after completing a specific

sequence of phases or skips remaining phases and goes directly to maintenance if a

failure occurs. For example, if a failure occurs on an aircraft during taxiing, it may

go directly to maintenance and then start from the beginning of the sequence after

the repair (rather than from the point of failure as with traditional RBD analysis. This

flexibility provides a tremendous leap forward in the ability to simulate more

realistic situations.

More Realistic Simulation Factors

Duty Cycles: BlockSim 7 now allows you to apply a factor to define a duty cycle

for a block that may experience a different stress load than the other blocks in the

diagram. For example, when analyzing a computer system, the CD-ROM drive does

not operate continuously. If you assume that the drive operates for 6 minutes out of

every hour, for example, you could apply a Duty Cycle factor of 0.1 (10%). You can

also treat the Duty Cycle as an acceleration factor in cases where it is necessary to

increase or decrease the stress applied to a component. This option is also available

for phases in Phase Diagrams, e.g. when the entire system goes through a different,

more or less stressful environment.

Variable Throughput:

A systems throughput may vary over time. For example, the flow from an oil well

may drop over time as the oil reserves are depleted or a manufacturing plant’s

production may slowly ramp up again after shut-down. Version 7 provides a choice

of three models to describe a system’s time-dependent variable throughput within

your simulation.

Type I Restoration Factors: BlockSim 7 now provides more flexibility for using

restoration factors to model imperfect maintenance scenarios. The software now

supports the Kijima Type I model, which allows you to define maintenance that

reduces a specified portion of the damage since the last repair only, along with the

Kijima Type II model, where the maintenance is assumed to reduce a specified

portion of the total damage to the item.

Additional Simulation Results

BlockSim 7's Simulation Results Explorer now reports a system's Mean Availability,

Interval Mean Availability, System Failures and Throughput. For simulations

performed on Phase Diagrams, results are reported at the system and phase levels,

with a phase summary that includes Mean Duration, End-of-Phase Point Availability,

Throughput, Executions and the Criticality Index for Aborted Missions.

Resource Usage Window

The new Resource Usage window provides an at-a-glance view of the diagrams and

blocks where specific resources (e.g. maintenance policies, spare parts policies,

etc.) are used within a project. This provides a quick summary of the project’s

defined resources in either a list or tree view and also allows you to delete unused

resources with a single click.

Analytical FRED Reports

In addition to the simulation-based FRED reports for repairable systems, BlockSim 7

now provides an analytical report for non-repairable systems. This report provides a

graphical representation of a non-repairable system’s reliability characteristics to

help identify components that may require improvement.

 

BlockSim Features - System Analysis Using RBDs or Fault

Trees

ReliaSoft's BlockSim 7 provides a comprehensive and flexible platform to model systems and processes using both reliability block diagram (RBD) and fault tree analysis (FTA) approaches. An extensive array of RBD configurations and FTA gates and events are supported, including advanced capabilities to model complex configurations, load sharing, standby redundancy, phases, duty cycles, and more!

Using exact computations and/or discrete event simulation, BlockSim 7 supports a wide variety of analyses for both repairable and non-repairable systems that will be of use to product designers and asset managers. This includes reliability, maintainability, availability, reliability optimization, throughput, resource allocation, life cycle cost and other analyses.

BlockSim 7 provides a sophisticated graphical interface that allows you to model the simplest or most complex systems using Reliability Block Diagrams (RBDs) or Fault Trees -- or a combination of both approaches! The software then algebraically computes system reliability results and optimum reliability allocations based on the exact system reliability function. BlockSim also provides a sophisticated discrete event simulation engine for reliability, maintainability, availability, throughput, life cycle cost summaries and related analyses.

Flexible Reliability Block Diagram (RBD) Creation

BlockSim's interface for Reliability Block Diagram (RBD) creation is the most intuitive, flexible and polished in the industry.

Simple drag-and-drop techniques allow you to build RBDs for the simplest to the

most complex systems. Configuration options include Series, Parallel, and k-out-of-

n (and in various complex combinations) plus...

o Load Sharing Blocks: In a load sharing configuration, each block supports a

percentage of the total load.

o Standby Blocks: In a standby configuration, standby blocks are available to

become active under specified circumstances.

o Mirrored and Multi Blocks: Provide increased versatility with the ability to

simulate bi-directional paths, save time/space when entering multiple identical

blocks, and more...

Unlimited subdiagram capability to link diagrams as components in other

diagrams.

Customizable graphical display with the ability to export diagram graphics.

Pre-defined templates and import/export to save time and ensure consistency,

ability to de-activate individual blocks for "what-if" analyses, file attachments,

and more...

Integrated Fault Tree Analysis Features

BlockSim's fault tree analysis interface supports all of the traditional FTA gates and event symbols that are applicable to system reliability and related analyses (including AND, OR, Voting OR, Inhibit, Priority AND and Sequence Enforcing gates along with Basic, Undeveloped, Trigger, Resultant and Conditional events). In addition, BlockSim allows you to expand the modeling capabilities through the introduction of new logic gates to represent Load Sharing and Standby Redundancy configurations.

Your BlockSim projects can contain both fault trees and reliability block diagrams, together in the same analysis environment. You can even integrate your fault trees and RBDs by linking a fault tree as a subdiagram to an RBD or vice versa; copying events from a fault tree diagram and pasting them as blocks in an RBD; and automatically converting any fault tree diagram to a reliability block diagram.

Exact Reliability Results/Plots and Optimum Reliability Allocation

Using an exclusive algorithm pioneered by ReliaSoft, BlockSim algebraically computes the exact system reliability function for even the most complex systems. Calculated results include Reliability, Failure Rate, MTTF, Warranty Time, B(X) Life, pdf plots, Reliability Importance plots, and more...

Also exclusively in BlockSim, you can enter cost and achievable reliability improvement information to determine the most cost-effective component reliability allocation strategy to meet a system reliability goal.

Extensive Simulation Options for Analysis of Repairable Systems

BlockSim's simulation capability for maintainability analysis and availability analysis of repairable systems is more sophisticated and realistic than ever. These tools can be used

to help you plan and improve a new product design and also to help equipment operators achieve effective asset management.

Corrective Maintenance (CM), Preventive Maintenance (PM) and

Inspection

Enhanced in Version 7!

o Maintenance Duration and Restoration Factors: Specify time-dependent

distributions or fixed durations for maintenance actions and whether the item will

be "as good as new" or less than 100% restored by the maintenance. Support for

Kijima model Type 1 Restoration Factors is now available in Version 7.

o Maintenance Policies: Describe the conditions under which maintenance will

be performed (e.g. upon fixed interval, maintenance of another group item, etc.).

o Spare Parts Pools and Maintenance Crews: Describe the conditions under

which spare parts can be obtained and crews are available to perform

maintenance, as well as the associated costs.

New in Version 7!

o Duty Cycles: Apply a factor to define a duty cycle for a block that may

experience a different stress load than the other blocks in the diagram.

New in Version 7!

Reliability Phase Diagrams: Use BlockSim’s intuitive Phase Diagram Sheets to

model systems that go through different phases during the course of their

operation. For example, some aircraft components (such as landing gear) operate

only during the take-off and landing phases of a mission and others (such as

engines) experience a higher failure rate during these phases due to higher stress.

Only BlockSim provides the ability to completely change the configuration and

component properties from one phase to another. The software also introduces

and fully supports the concept of Maintenance Phases, which allow you to model

scenarios in which a system goes into maintenance after completing a specific

sequence of phases or skips remaining phases and goes directly to maintenance if

a failure occurs.

Enhanced in Version 7!

Comprehensive Results and Plots: Maintainability and availability results per

system and/or per block including: Uptime, Downtime, Mean Time to First Failure

(MTTFF), Mean Availabilities, Point Availabilities, Point Reliabilities, Number of

Failures, Number of PMs, Number of Inspections, Plots of System

Uptime/Downtime, Point Availability vs. Time, Point Reliability vs. Time, and more.

System "point" results are now available in Version 7!

The simulations also provide Life Cycle Cost summaries, Throughput estimations, Optimum PM time calculations, and many other results necessary to make effective decisions about your systems.

 

Application Examples for BlockSim

We have compiled some case studies to demonstrate the types of analyses that you will be able to perform with ReliaSoft's BlockSim 7. Some of the many useful applications include the ability to:

Identify critical components (or failure modes) and determine the most effective

ways to improve system performance through design improvements and/or

maintenance planning.

Use simulation to obtain estimated performance metrics that can facilitate

decision-making in a variety of areas, such as scheduling planned maintenance,

planning for spares, identifying bottlenecks in production throughput and

estimating life cycle costs.

Identify vulnerabilities in a system and determine the most effective ways to

reduce the risk.

We have compiled some case studies to demonstrate the types of analyses that you will be able to perform with BlockSim. For the actual case studies, the data and/or exact test method that were used may have been modified in cases where the actual information was deemed to be confidential.

Example 1:

Reliability of a Storage Cluster

Reliability analysis of a "high-availability" storage cluster (computer servers and connection).

See Example

Example 2:

Optimized Reliability Allocation

In this example, a system is defined using subdiagrams. A reliability target is set for the entire system and reliability is then allocated to the subsystems, assemblies and components using an optimized allocation methodology.

See Example

Example 3:

Effect of Inspection Intervals

This example uses BlockSim to study the effects of different inspection intervals on a life vest aboard a commercial aircraft. Inspections are used to discover dormant failures.

See Example

Example 4:

Modeling Failure Modes

This example illustrates the use of the RBD methodology for a single component and its associated failure modes.

See Example

Example 5:

Remote Telecommunications System

This example looks at a telecommunications system (consisting of a transmitter, receiver with six relay stations) to be constructed in an uninhabited stretch of jungle. Both reliability and availability of the system are studied.

See Example

Example 6:

Combining Fault Trees and RBDs

This example analyzes a component based on its failure modes, using a combined fault tree analysis and RBD approach.

See Example

General Example:

Analytical Solution of a Complex System

One of the unique features of BlockSim 7 is its ability to

analytically resolve the most complex of systems. This example

illustrates a complex system and its analytic solution.

BlockSim Example RC1 - Reliability Analysis of a Storage

Cluster System

Download   Example File (*.rbp)

Background

This example is based on the example shown in Figure 8 of the article "Determining the Availability and Reliability of Storage Configurations" by Santosh Shetty, August 2002, as posted on Dell's Web site.

Analysis

Consider a "high-availability" cluster with a reliability block diagram (RBD) as shown in the next figure.

Furthermore (and from the referenced Web article), assume the following life distributions and parameters. (Note that this example, unlike the original article, assumes no repair of failed components.)

Server: Exponential (Mean = 45753 hr)

Switch: Exponential (Mean = 255,358 hr)

HBA: Exponential (Mean = 252,550 hr)

Controller: Exponential (Mean = 68,961 hr)

Step 1: Determine the "reliability equation" and cdf of the system....

Figure 1 illustrates BlockSim being used to determine the system reliability function.

Figure 1: BlockSim 7 screen shot with the system reliability equation.

You can also view the system reliability equation and cdf in HTML format .

Step 2: Looking at some system level plots...

Component Reliability Importance Plots

The next two charts are component reliability importance plots at t = 8544 hr (1 year). Both plots (a tableau area plot and a bar chart) illustrate the same concept. That is, the higher the importance of the component, the higher its effect on system reliability.

The next graphic shows a component reliability importance plot that varies with time.

Conclusion

The servers in this configuration are the most critical component while the hubs are the least critical.

System Reliability Plot

System Failure Rate Plot

System pdf Plot

Step 3: Determine System Results...

The MTTF of the system can be obtained from BlockSim's Analytical QCP.

BlockSim Example RC2 - Optimized Reliability Allocation

Download   Example File (*.rbp)

In this example, a system is defined using subdiagrams. A reliability target is set for the entire system and reliability is then allocated to the subsystems, assemblies and components using an optimized allocation methodology.

Consider the following system composed of two subsystems, A and B, as shown below:

Subsystem A is composed of two assemblies, A and B. Assembly B is in a 2-out-of-3 redundant configuration.

Subsystem B is composed of two assemblies, C and D.

Assembly A is made up of components 0 and 1.

Assembly B is made up of components 3, 4 and 5.

Assembly C is made up of components 6 and 7.

Assembly D is made up of components 8 and 9.

Furthermore, assume the following life characteristics for each component:

Component Life (Failure) Distribution

Comp. 0 : Weibull Beta = 2 Eta = 5,000

Comp. 1 : Weibull Beta = 2 Eta = 4,500

Comp. 3 : Weibull Beta = 1.5 Eta = 8,965

Comp. 4 : Weibull Beta = 1 Eta = 8000

Comp. 5 : Lognormal Log Mean = 10 Log Sigma = 1.4

Comp. 6 : Weibull Beta = 3 Eta = 10,000

Comp. 7 : Weibull Beta = 3 Eta = 6,000

Comp. 8 : Exponential Mean = 10,000  

Comp. 9 : Weibull Beta = 2.2 Eta = 7,000

The system reliability for this configuration at 500 hr is R(t) = 0.925656. Let's assume that the target reliability for this system is R(t = 500) = 0.95.

Determine an optimum reliability allocation strategy assuming that the cost/difficulty of increasing an item's reliability is defined by the following function.

    (1)

Where:

( ) is the penalty (or cost) function as a function of component reliability.

f is the feasibility (or cost index) of improving a component's reliability relative to

the other components in the system.

is the current reliability at the time at which the optimization is to be

performed.

is the maximum achievable reliability at the time at which the optimization

is to be performed.

At the system level, we'll set Subsystem 1 to f = 0.9 and Subsystems 2 to f = 0.7. Rmax for both subsystems is 0.99999 at 500 hrs.

Then the optimum allocation scheme for each subsystem is the one that satisfies:

While minimizing:

Solving this yields an optimum allocation for each subsystem. Specifically, the new target reliability for Subsystem A is 0.986137 and for Subsystem B is 0.963344.

Figure 1: Solution calculated using BlockSim 7.

The process can then be repeated for each assembly and component in the system. The results are given in the next table.

BlockSim Example RC3 - Effect of Inspection Intervals

Download   Example File (*.rbp)

This example studies the effects of different inspection intervals.

Odyssey Air uses inflatable life vests manufactured by ACME Life Vest Company aboard its commercial aircraft. Odyssey Air wants to study and understand the effect of different inspection intervals.

The vests are stored until they are required for use.

o Therefore, failures remain dormant until the system is needed or failed vests are

discovered during scheduled inspections.

o Scheduled inspections involve testing all vests on the aircraft. Vests found failed

are discarded and replaced with new vests (thus resulting in a mix of vests of

different ages aboard an aircraft).

o Past replacement data were utilized and a dormant failure distribution for these

vests was obtained.

Weibull with Beta = 2.55 and Eta = 6.89 years.

Odyssey Airlines is contemplating different inspection intervals for these life vests.

o Study the effect of  inspections done annually, every two years and every three

years.

Problem Setup in BlockSim

One way to approach this in BlockSim is to set up a single block with the given dormant failure distribution. Figure 1 shows the analysis in BlockSim.

If a vest is found failed it is replaced, thus a corrective action needs to be set for

the block.

o One can assume instantaneous replacement (zero duration) since the time to do

the inspection and replace the vest is not of interest in this analysis.

o Furthermore and since the vests are replaced with new ones, a restoration factor

of 1 can be assumed.

The corrective action is not initiated until the vest is found failed, thus the

corrective action will be based upon an inspection. The "Upon Inspection" setting

needs to be utilized.

o For annual inspections, the inspection would be once a year and so forth.

Figure 1: Using BlockSim 7 to define the block properties

Once the problem has been set up, simulation is utilized to see the effect of the inspection intervals. Specifically in this case, what is of interest is the Instantaneous or Point Availability, A(t). What this gives us (within the context of this problem) is the probability that a vest will be operational (non-failed) at a specific point in time.

Annual Inspection

Figure 2 shows A(t) when utilizing annual inspections. As it can be seen on the chart, A(t) goes to 1 after each inspection, implying that 100% of the vests are in a non-failed state after the inspection.

From the plot it can be seen that after 1.5 years, A(t) is approximately 98%, implying that 2% of the vests on the aircraft are in a failed state at that point in time. Furthermore, the following can be noted:

The percent non-failed decreases after each inspection.

The rate of decrease of A(t) keeps on increasing after each subsequent inspection

(since non-failed vests are not replaced and the population ages) until a periodic

reversal point is reached at which most vests are replaced with newer ones, thus

yielding a younger population.

Figures 3 and 4 repeat the analysis using two and three year inspection plans.

Figure 2: A(t) vs. time assuming annual inspection

 

Figure 3: A(t) vs. time assuming inspection every two years

 

Figure 4: A(t) vs. time assuming inspection every three years

BlockSim Example RC4 - Modeling Failure Modes

Download   Example File (*.rbp)

When thinking of a reliability block diagram (RBD), the application that most often comes to mind is the analysis of a system based on the component reliabilities. You can also use the same methodology to analyze a single component and its associated failure modes.

In analyzing this scenario, both independent (i.e. if one mode occurs, the rest are not more likely to occur) and dependent modes (i.e. if one mode occurs, the rest are more likely to occur) can be included. To illustrate this, a component with multiple primary modes as well as multiple secondary modes (sub-modes) will be considered. In addition, both independence and dependence will be utilized.

View this example*

*This example was published in the Reliability HotWire.

BlockSim Example RC5 - Remote Telecommunications System

Download Example File (*.rbp)Steps 1, 2 and 3 Example FileStep 4 Example File

A telecommunications system is to be constructed in an uninhabited stretch of jungle. The system consists of a transmitter and receiver with six relay stations to connect them.

The relays are situated so that the signal originating from one station can be picked up by the next two stations down the line. For example, a signal from the transmitter can be received by Relay 1 and Relay 2, a signal from Relay 1 can be received by Relay 2 and Relay 3 and so forth. Thus, this arrangement would require two consecutive relays to fail for the system to fail. (This is also known as a consecutive-k-out-of-n:F system.)

Step 1: Setup the Master RBD

Draw the RBD for this system.

Figure 1: The system RBD.

Step 2: Basic Reliability Analysis

Furthermore, consider the following:

The transmitter and receiver are made up of three subassemblies each, while the

relay stations have two subassemblies each (all in series). Specifically:

o Subassembly SPS1 (solar power supply) is common to all.

o The transmitter has two additional subassemblies, TRC1 and TRC2.

o The receiver also has two additional subassemblies, RCR1 and RCR2.

o Relay stations have a subassembly RLYC1 in addition to SPS1.

Assume the failure distributions for each subassembly, as given in Table 1.

Table 1

Step 2 Tasks

2.1 Determine the reliability of the system after 1000 hrs.

2.2 Does the failure of any of the redundant relays (1 through 6) have the same

effect on the system reliability? In other words, does it matter from a reliability

perspective which specific relay fails?

Step 2 Solution

Subdiagram RBDs are used for each element (transmitter, relay and receiver) and the appropriate failure distributions are set at the subdiagram level. (See the actual subdiagram setup used...)

2.1 Once the model has been set up, the Reliability at 1,000 hrs is determined to

be 97.675%. (See more details in computing this...)

2.2 Yes. Even though the relays are reliability-wise identical, their position within

the diagram matters. The greatest impact on reliability is if 2 or 5 fails followed by

4 or 3 and then by 1 or 6. (See more details in computing this...)

Step 3: Introduce Basic Repairs/Maintenance

Further assume that the components given in Table 1 are line replaceable units and each repair involves the replacement of the existing component with a new component. (Note that if this were not the case, i.e. if we had assumed imperfect repair, then restoration factors could have been utilized).

Additionally, each component has a probabilistic repair (replacement) duration, as given in Table 2. For this step we will assume that repair begins immediately upon failure and that when the system is failed components do not age. We will not utilize (include) any other constraints.

Table 2

Step 3 Tasks

3.1 Determine the point availability of the system after 1 year of operation (8760

hrs).

3.2 Determine the average availability of the system after 1 year of operation.

3.3.Estimate the Mean Time to First Failure of the system.

3.4 Rank the components in terms of their Failure Criticality Index (RS FCI).

3.5 Estimate the expected number of spare parts required for each component.

3.6 What is the expected system downtime?

Step 3 Solution

To obtain the results of interest, discrete event simulation was utilized with 10,000 runs.

3.1 Point availability after 1 year of operation, A(t = 8760 hrs), is: 0.9986 (See

more details...)

3.2 Average availability after 1 year of operation is 0.9993. (See more details...)

3.3.The Mean Time to First Failure of the system is 16397. (See more details...)

3.4 Table 3 shows that 99.9% of system failures were either due to the transmitter

or receiver. From that, 54% were due to the transmitter and 20.5% of the

transmitter failures were due to the SPS1 component. (See more details...)

Table 3

3.5 The expected number of spare parts can be obtained by looking at the

expected number of failures. Obviously, a spare part would be required for each

failure. Table 4 shows these numbers. For SPS1, 0.9579 failures are expected.

Another way to look at this is to say that there is a 96% chance that I will need a

spare part for SPS1. Now the choice as to whether to keep spare parts around is

based on additional economic and logistic information (e.g. How quickly can I get a

part? How much does it cost me to keep it around? etc.) (See more details...)

Table 4

3.6 The total system downtime is 6.16. (See more details...)

Step 4: Introduce Additional Constraints

To further analyze the system, let's introduce additional constraints/parameters to this analysis.

A subcontractor is available to repair the system. It takes on the average 36 hours (standard deviation of 6 ~ normal distribution) for the subcontractor to get a technician to the site and the subcontractor only has two technicians qualified to service this system. Also, the subcontractor keeps a single spare for SPC1 and RLYC1 on site. On-site spares (if in stock) are available immediately. Any other parts needed must be ordered and shipped.

Specifically, assume that:A spare part that is ordered and shipped arrives based on a normal distribution with a mean of 72 hours and a standard deviation of 12.One SPC1 and one RLYC1 are kept on site. When one is used, an additional spare is ordered.

Step 4 Tasks

4.1 Determine the average availability of the system after 1 year of operation.

4.2 What is the expected system downtime?

Step 4 Solution

Additional properties can now be set for each block. Specifically, a crew needs to be defined for each repair action. (See Crew settings...)

Once the crew has been added, spare part pools are utilized to emulate the situation. (See Spare Part settings...)

4.1 The average availability after 1 year of operation is 99.6%.

4.2 The expected system downtime is 36.21.

BlockSim Example RC6 - Modeling Failure Modes (RBD and

Fault Tree)

Download   Example File (*.rbp)

This is the same example as Example RC4. For this example, the Fault Tree Analysis (FTA) approach is integrated into the analysis.

Example RC4 used a reliability block diagram (RBD) approach to analyze a component and its associated failure modes. The example considers both independent modes (i.e. if one mode occurs, the rest are not more likely to occur) and dependent modes (i.e. if one mode occurs, the rest are more likely to occur). In this study we will repeat the same example using a combined fault tree and RBD methodology.

Example

Assume that a component can fail due to six independent primary failure modes: A, B, C, D, E and F. Some of these primary modes can be broken down further into the events that can cause them, or sub-modes. Furthermore, assume that once a mode occurs, the "event" also occurs and the mode does not go away. Specifically:

The component fails if mode A, B or C occurs. If mode D, E or F occurs alone, the component does not fail; however, the component will fail if any two (or more) of these modes occur (i.e. D and E; D and F; E and F). Modes D, E and F have a constant rate of occurrence (exponential distribution) with mean times of occurrence of 200,000, 175,000 and 500,000 hours, respectively. The rates of occurrence for modes A, B and C depend on their sub-modes.

Objective

The objective of this example is to determine the following:

1. The reliability of the component after 1 year (8760 hrs).

2. The B10 life of the component.

3. The mean time to failure (MTTF) of the component.

4. Rank the modes in order of importance at 1 year.

5. Re-calculate results 1, 2 and 3 assuming mode B is eliminated.

To begin the analysis, modes A, B and C can be broken down further based on specific events (sub-modes), as defined next.

Mode A

There are five independent events (sub-modes) associated with mode A: events S1, S2, T1, T2 and Y. It is assumed that events S1 and S2 each have a constant rate of occurrence with a probability of occurrence of 1 in 10,000 and 1 in 20,000, respectively, in a single year (8760 hours). Events T1 and T2 are more likely to occur in an older component than a newer one (i.e. they have an increasing rate of occurrence) and have a probability of occurrence of 1 in 10,000 and 1 in 20,000, respectively, in a single year and 1 in 1,000 and 1 in 3,000, respectively, after two years. Event Y also has a constant rate of occurrence with a probability of occurrence of 1 in 1,000 in a single year. There are three possible ways for mode A to manifest itself:

Events S1 and S2 both occur.

Event T1 or T2 occurs.

Event Y and either event S1 or event S2 occur (i.e. events Y and S1 or events Y

and S2).

RBD Solution

The RBD that satisfies the conditions for mode A is shown in Figure 1.

Figure 1: Reliability block diagram for mode A

Each mode is identified in the RBD. Furthermore, two additional items are included: a starting block (NF) and an end node (2/2). The starting block and the end node are set so they cannot fail and, therefore, will not affect the results. The end node is used to define a 2-out-of-2 k-out-of n configuration (i.e. both paths leading into the node must work).

Fault Tree Solution

The Fault Tree for mode A is shown in Figure 2.

Figure 2: Fault tree for mode A

Each mode is identified as an event in the fault tree.

Mode A Discussion

The system reliability equation for this configuration (regardless of how it is drawn) is:

R(t)=-2RT2·RS1·RS2·RT1·RY+RT2·RS1·RS2·RT1+RT2·RS1·RT1·RY+RT2·RS2·RT1·RY

Based on the given probabilities, distribution parameters are computed for each block (either RBD block or the fault tree event block). These were computed in Example RC4.

Mode B

There are three dependent events associated with mode B: events BA, BB and BC. Two out of the three events must occur for mode B to occur. Events BA, BB and BC have an exponential distribution with a mean of 50,000 hrs. The events are dependent (i.e. if BA, BB or BC occurs, the remaining events are more likely to occur). Specifically, when one event occurs, the MTTF of the remaining events is cut in half. This is basically a load sharing configuration. The reliability function for each block

will change depending on the other events. Therefore, the reliability of each block is not only dependent on time, but also on the stress (load) that the block sees.

RBD Solution

The reliability block diagram for mode B is shown in Figure 3.

Figure 3: Reliability block diagram for mode B

Fault Tree Solution

The fault tree for mode B is shown in Figure 4.

Figure 4: Fault Tree diagram for mode B (using a load sharing gate unique to

BlockSim).

Note that a "load sharing gate" is not a standard fault tree gate. BlockSim introduces this gate to allow for representation of dependent events in a fault tree diagram. It behaves in exactly the same way as a load sharing container in an RBD.

Mode B Discussion

To describe the dependency, we need a model that describes how a life characteristic (in this case, the mean) changes as the events occur. Life-stress relationships used in accelerated testing provide a very good way to describe the effects of stress (load) on life. Since the failure rate is constant, the exponential distribution applies. Any standard life-stress relationship (i.e. an exponential curve or power curve) would apply equally because the function is only being evaluated at the two loads of interest and not necessarily extrapolating or interpolating between these two points. For simplicity, the Arrhenius life-stress relationship will be used.

Once the parameters have been obtained, the properties for each event for mode B are set. The load sharing container (if an RBD) or the gate (if a fault tree) properties for the events of mode B are shown in Figure 5.

Figure 5: Arrhenius-exponential life-stress relationship properties

The reliability plot for this configuration is displayed in Figure 6.

Figure 6: Reliability plot for mode B

For details on the exact reliability equation formulation, please refer to ReliaSoft's System Analysis Reference: Reliability, Availability and Optimization (the load sharing section) that is available online at weibull.com and that accompanies BlockSim.

Mode C

There are two sequential events associated with mode C: CA and CB. Both events must occur for mode C to occur. Event CB will only occur if event CA has occurred. If event CA has not occurred, then event CB will not occur. Both events CA and CB occur based on a Weibull distribution. For event CA, beta = 2 and eta = 30,000 hours. For event CB, beta = 2 and eta = 10,000 hours.

RBD Solution

To model this, you can think of a scenario similar to standby redundancy. Basically, if CA occurs then CB gets initiated. A standby container can be used to model this, as shown in Figure 7.

Figure 7: Standby container for mode C

In this case, event CA is set as the active component and CB as the standby. If event CA occurs, CB will be initiated. For this analysis, a perfect switch is assumed. The properties are set in BlockSim as follows:

Contained Items

o CA: Active failure distribution, Weibull distribution (beta = 2, eta = 30,000).

o CA: Quiescent failure distribution: None, cannot fail or age in this mode.

o CB: Active failure distribution, Weibull distribution (beta = 2, eta = 10,000).

o CB: Quiescent failure distribution: None, cannot fail or age in this mode.

Switch

o Active Switching: Always works (100% reliability) and instant switch (no delays).

o Quiescent Switch failure distribution: None, cannot fail or age in this mode.

Fault Tree Solution

The fault tree for mode C is:

Figure 8: Sequence enforcing (standby) gate for mode C

Mode C Discussion

The failure distribution settings for event CA are shown in Figure 9.

Figure 9: Failure distribution settings for event CA

The failure distribution properties for event CB are set in the same manner.

Modes D, E and F

Modes D, E and F can all be represented using the exponential distribution. The failure distribution properties for modes D, E and F are presented next.

D: MTTF = 200,000 hours

E: MTTF = 175,000 hours

F: MTTF = 500,000 hours

Component

The last step is to set up the model for the component based on the primary modes (A, B, C, D, E and F). Modes A, B and C can each be represented by single blocks that encapsulate the subdiagrams already created. The RBD in Figure 10 represents the primary failure modes for the component while the fault tree in Figure 11 illustrates the same.

RBD Solution

Figure 10: RBD of Component

Fault Tree Solution

Figure 11: Fault Tree of Component

The node represented by 2/3 in the RBD indicates a 2-out-of-3 configuration. The voting gate in the fault tree accomplishes the same. Subdiagrams are used in both configurations for the sub-modes.

Once the diagrams have been created, the reliability equation for the system can be obtained, as follows:

R(t)System  = RA·RB·RF·RD·RC+RA·RB·RF·RC·RE+RA·RB·RD·RC·RE-2(RA·RB·RF·RD·RC·RE)

Where RA, RB and RC are the reliability equations corresponding to the sub-modes.

Analysis

The answers to the questions posed earlier can be answered using BlockSim. Regardless of the approach used (i.e. RBD or FTA), the answers are the same.

1) The reliability of the component at 1 year (8760 hours) can be calculated using the Analytical Quick Calculation Pad (QCP) or by viewing the reliability vs. time plot, as displayed in Figure 12.

Figure 12: Reliability vs. time plot for component

Therefore, R(t = 8760) = 86.4975%.

2) Using the Analytical QCP, the B10 life of the component is equal to 7,373.94 hours.

3) Using the Analytical QCP, the mean life of the component is equal to 21,659.68 hours.

4) The ranking of the modes after 1 year can be shown via the static reliability importance plot, as shown in Figure 13.

Figure 13: Static reliability importance for each of the modes at t = 8760 hours

5) Re-computing the results for 1, 2 and 3 assuming mode B is removed:

R = 98.72%

B10 = 16,928.38 hours

MTTF = 34,552.89 hours

Discussion

There are many options for modeling systems with fault trees and RBDs in BlockSim. The following figures illustrate some of these options.

Figure 14: Fault tree for the component without using subdiagrams (transfers)

Figure 15: RBD for the component using fault trees as subdiagrams.

Figure 16: Fault tree for the component using RBDs as subdiagrams.

System Analysis Software Using RBDs or Fault Trees

BlockSim provides a comprehensive platform for system reliability, availability,

maintainability and related analyses. The software offers a sophisticated

graphical interface that allows you to model the simplest or most complex

systems or processes using reliability block diagrams (RBDs) or fault tree

analysis (FTA) — or a combination of both approaches. Using exact

computations and/or discrete event simulation, BlockSim facilitates a wide

variety of analyses for both repairable and non-repairable systems. This includes

reliability analysis, maintainability analysis, availability analysis, reliability

optimization, throughput calculation, resource allocation, life cycle cost analysis

and other system analyses.

BlockSim.ReliaSoft.com

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