BlockSim Software Features
Using exact computations or discrete event simulation, BlockSim facilitates a wide variety of analyses for both repairable and non-repairable systems that will be of use to both product designers and asset managers. This includes reliability analysis, maintainability analysis, availability analysis, reliability optimization, throughput calculation, resource allocation, life cycle cost analysis and other system analyses.
Reliability Block Diagrams and Fault Trees
Simple drag-and-drop techniques make it easy to build reliability block diagrams or fault trees to model systems and processes. All of the traditional RBD configurations and fault tree gates and events are supported, along with advanced capabilities to model complex configurations, load sharing, standby redundancy, phases, duty cycles, subdiagrams and more.
Your BlockSim projects can contain both fault trees and reliability block diagrams, together in the same analysis workspace. You can also integrate the diagrams by linking a fault tree as a subdiagram to an RBD or vice versa.
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, Probability of Failure, Reliable Life (i.e., time for a given reliability), BX% Life (i.e., time for a given unreliability), Mean Life, Failure Rate, pdf plots, Reliability Importance plots and Minimal Cut Sets.
You can also enter cost and achievable reliability improvement information to determine the most cost-effective component reliability allocation strategy to meet a system reliability goal.
Repairable System Analysis via Discrete Event Simulation
BlockSim's simulation capability for maintainability analysis and availability analysis of repairable systems is more sophisticated and realistic than ever. When you utilize simulation, the analysis can consider factors such as duty cycles, restoration factors, downtime and cost/availability for repair crews and spare parts. You can also achieve the appropriate modeling for maintenance scheduling that depends on other components (maintenance groups) and systems that go through different phases during the course of their operation (phase diagrams).
The simulation results can be used for a wide variety of applications, including but not limited to:
- Choosing the most effective maintenance strategy, considering safety, cost and/or availability.
- Determining the optimum preventive maintenance (PM) interval.
- Managing the spare parts inventory, considering factors such as cost, utilization rate, supply bottlenecks, etc.
- Identifying the components that have the biggest impact on availability (downtime).
In addition, BlockSim’s Throughput Analysis can be used to identify bottlenecks, optimize resource allocation and otherwise improve the processing efficiency of the system.
Whenever applicable, BlockSim allows you to specify the direct and indirect costs associated with the maintenance strategies that you have defined. This yields a wide array of simulation results that are instrumental in performing realistic Life Cycle Cost assessments.
Why Upgrade to Version 9?
BlockSim now offers a completely updated user interface and many useful new features. This includes:
- Integration into the Synthesis Platform®, which allows multiple users throughout the organization to share analysis information between any of ReliaSoft's Synthesis-enabled analysis tools.
- Multi-thread support and re-optimized code that have resulted in speed increases in excess of 10x.
- Direct integration with RENO. Option to build RBDs or fault trees from system configuration and failure mode data in Xfmea/RCM++/RBI, or from failure rate predictions in Lambda Predict.
- More flexible modeling capabilities, such as state change triggers, new gates for fault trees, success/failure paths in phase diagrams and enhanced cost calculations. New worksheet for performing batch simulation of an RBD, using different input values for each simulation.
- New utilities for calculating the optimum reliability allocation to meet a specified goal, or the optimum interval for preventive maintenance.