For evaluating the performances of dynamic systems
(reliability/safety/production availability analyses)
using Stochastic Petri Nets with Predicates and Assertions.
The Petri module serves to model the behavior of complex dynamic systems based on stochastic Petri nets with Predicates and Assertions. It is based on Moca-RP (Monte-Carlo – Petri Nets), TOTAL high speed calculation engine based, as its name suggests, on the Monte-Carlo simulation, which pushes back the boundaries of modeling and is enriched by more than 30 years of research and development.
Modeling and main computations
Petri nets (RdP) are easy to build via an intuitive graphic interface. Places, transitions, arcs and tokens can be created and all types of mathematical variables and logic operators (OR, AND, If-Then-Else, Min (), Max (), etc.) are available. These variables represent indicators and act on the validation (Predicates) of transitions and can also be modified when firing transitions (Assertions).
Once the system has been modeled, the Moca-RP engine produces numerous results:
- Evaluation on a time, mean or given-period basis of any indicator created by the user.
- 7 types of statistics available for each variable (mean over the calculation period, mean per time interval, variation frequency, etc.).
- Analysis of the different values during the different simulated histories.
- Transition firing frequency.
- Mean sojourn time in each place and the mean marking for each place, etc.
The flexibility of the module will enable you to obtain both standard dependability values (availability, reliability, etc.) and information concerning production systems (quantities produced, number of resources used, etc.).
Specificities and strong points
The great strength of stochastic Petri nets with Predicates and Assertions lies as much in their modeling power as in their ability to describe the dysfunctional parts of an installation (component failures) and the working parts.
Without any theoretical usage limits, this module can be used for any system. Strong dependences among components can be modeled with reconfigurations over time, using deterministic or stochastic transitions: exponential, Weibull, triangular, uniform or any other law you may have programmed.
You can run hybrid simulations by linking Moca-RP to a C++ code to define the physical properties of the system (temperature variation, propagation calculation, etc.).
Priorities among different actions, intervention times, stock management, operating costs or a change in policy after an event – all these data can be easily included in this module.
The versatility of the Petri module means that it can be used in a wide variety of industrial sectors: nuclear energy transportation, aerospace, oil and gas, etc.
The Petri module uses the graphical tree structure common to all the modules. Switching to Interactive Simulation mode enables the user to check/validate the model. Component prototypes can be created and stored in a library, and reused either directly as Petri nets to easily create a larger Petri net, or as stochastic block diagrams in the BStoK or Petro module.
GRIF is upgraded every year, on the basis of user comments and suggestions to improve the ergonomics of the interface and automate repetitive tasks.
Data exploitation and results
- Synthesis of input data in the form of tables that makes it easier to control the quality of an entry.
- Possibility of automating calculations (batch run).
- Results stored in the same document and exportable in different formats (csv, XML, Excel, etc.).
- Visualization of results as curves, pie charts or histograms.
- Vector printing of graphic elements and curves in PDF format which maintains optimum quality, even in A3 or A2 format.
- Interaction with the operating system: option to copy/paste curves or results to word processing software, spreadsheets or presentation tools.
- Possible connection to MySQL, Access and Excel databases to recover the values to be used for the settings
As in all the modules of the simulation package, calculations can be run simultaneously on several processors, to radically reduce calculation time.