Cyclical (Repeating / Regular) Processes

The cyclical (repeating / regular) processes drive the behavior of the system-of-interest. These are triggered either by a time based event or a specific event based upon internal or external conditions.

If the system is being developed, then the behavior can be modelled and simulated or estimated based upon the current configuration assumed for the analysis. These measurements can also be compared with similar existing systems and their performance.

These interactions and behaviour create the systemic properties or functions / capabilities described in the System Properties section. The performance measurements are actually of the systemic properties for the system.

Examples of cyclical processes are:

• Living systems: Metabolism based upon energy, matter and information inputs and outputs.

• Designed systems: the process from order to cash in the bank or the process of manufacturing a product.

The interactions allow the flow of information, energy and matter to be seen in a temporal view.

Some interactions vary depending upon the startup, operation and close operations of cyclical processes.

The following types of models or analysis approaches are useful in this section:

• Mathematical Models: Transfer functions using Laplace Transforms

• Causal Loop Diagrams

• Activity Diagrams

• Markov Chains (Based upon probabilities)

• Monte Carlo Methods (based upon probabilities)

• Decision Trees

Note: The cyclical changes may also cause or trigger developmental processes which may change the state of the system or allow for improved systemic properties (e.g. mental or physical abilities).