Getting Started

Start an Execution Engine

To start an Execution Engine for custom process execution, run the main.py file. However, the main Program requires a set of mandatory and optional arguments that must be handed over from as program arguments:

Mandatory Arguments

• execution_engine_server_url

• path_to_pfdl

Here, the execution_engine_server_url specifies the web-address of the Execution Engines OPC UA server and the path_to_pfdl a path to a local PFDL file that should be executed with the Execution Engine.

Example configurations could be: - opc.tcp://localhost:4840 - ./PFDL_Examples/advanced.pdfl

Optional Arguments

The optional arguments are used to create kwargs for the Execution Engine object. Here, each argument that is set must provide a key and a value, separated by an equals. A potential configuration could be:

• “dashboard_host_address”=”http://localhost:8080”

• “device_registry_url”=”opc.tcp://localhost:8000”

• “custom_url”=”opc.tcp://localhost:”

• “number_default_clients”=5

• “assignment_agent_url”=”opc.tcp://localhost:10000”

• “delay_start”=20

Run the main.py file

The main.py file can be started from a terminal with at least both mandatory program arguments set:

python3 main.py "opc.tcp://localhost:4840" "./PFDL_Examples/advanced.pdfl"

In case that some or all optional arguments should be deployed, the command would look like:

python3 main.py "opc.tcp://localhost:4840" "./PFDL_Examples/advanced.pdfl" "dashboard_host_address"="http://localhost:8080" "device_registry_url"="opc.tcp://localhost:8000" "number_default_clients"=5

Installation Requirements

Ensure that the python version is 3.10.14 and the required python packages are installed:

pip install asyncua==1.1.5 nest-asyncio==1.6.0 pfdl-scheduler==0.9.0 python-on-whales==0.73.0

Besides, Graphviz (https://graphviz.org/) must be installed on the system.

Tutorials

For the tutorial section, we deploy the Demonstration Scenario environment, so that only an execution engine must be configured and a PFDL file specified. All other required components, such as a Device Registry, Assignment Agents or shop floor resources are started as pre-build docker environments. The executable code of the tutorials can be found in the Tutorials Section of this repository.

• Static Assignment
  • PFDL Definition
  • Process Execution
• Default Assignment
  • PFDL Definition
  • Process Execution
• Dynamic Assignment
  • PFDL Definition
  • Process Execution
• Service Specific Assignment
  • PFDL Definition
  • Process Execution
• Service Specific Device Registry
  • PFDL Definition
  • Process Execution
• Capability-based Assignment
  • PFDL Definition
  • Process Execution

Configure an Execution Engine

To Start an Execution Engine with the PFDL Scheduler as dispatcher the main.py file must be executed. Here, an instance of the Execution Engine class is created. Table 2 displays the mandatory and optional class arguments for an Execution Engine. Optional class arguments have default values that can be overwritten by providing a corresponding value when creating the Execution Engine object. A set of Tutorials is provided within this repository, where each of them features a different Resource Assignment strategy of the Execution Engine.

As stated before, we integrate the PFDL Scheduler as default dispatcher for the Execution Engine. However, if it is desired to replace the PFDL Scheduler as dispatcher and integrate a custom dispatcher, have a look a section Custom Dispatcher Integration. Anyway, the PFDL Scheduler must be set as Dispatcher Configuration. Afterwards, an instance of the PFDL Scheduler must be handed over to the Execution Engine object (Table 2). Table 1 displays the Dispatcher Configuration for the PFDL Scheduler

Table 1: Dispatcher Configuration

Argument	Type	Explanation
filepath	str	path to a file that contains the process description of the process to be executed with the Execution Engine
dashboard_host_address	str	URL of a visualization tool for the process execution. For the PFDL Scheduler, the SWAP-IT Dashboard is provided.

Table 2: Execution Engine Class Arguments

Argument	Type	Explanation
Mandatory
server_url	str	Target URL of the Execution Engine’s OPC UA server
dispatcher_object	dispatcher	Python object of a configured dispatcher
Optional
iteration_time	float	timespan between a loop operation of the Execution Engine’s OPC UA server. If no value is set, the iteration_time defaults to iteration_time=0.001 seconds.
log_info	bool	The Execution Engine prints log messages about the executed Tasks and Service. If no value is set, the log_info defaults to log_info = False, so that no log messages are printed.
number_default_clients	int	Number of OPC UA Clients that are started by the Execution Engine’s Control Interface. If no value is set, the value defaults to number_default_clients = 1, so that only a single client is started. In case that more Clients are required e.g., due to parallel service executions, the Execution Engine will start new clients, however, this requires computational effort.
device_registry_url	str	URL of the Device Registry’s OPC UA server. In case that no value is set, it has to be ensured, that a static resource assignment is provided (see Resource Assignment).
assignment_agent_url	str	URL of an Assignment Agent’s OPC UA server. In case that no value is set, either a static Assignment Agent must be provided, or the default assignment behavior of the Execution Engine is applied (see Resource Assignment).
delay_start	int	If set, the Execution Engine waits delay_start number of seconds, otherwise, the process execution starts without delay
docker	string	In case that the Execution Engine interacts with OPC UA server inside a docker environment, it might be possible that the server URL’s have to be adjusted, so that the Execution Engine can connect to them from outside the docker environment. If set, the Port from the server URL received from an Assignment Agent is extracted and added to the string specified in this argument. For example, if the Execution Engine receives an URL “opc.tcp://swap_server:4840” docker = “opc.tcp://localhost:” will adjust the url to “opc.tcp://localhost:4840”.