Examples

All of the examples are part of the open source repository on GitHub: examples/

Once you have the SimPROCESD package installed and the source code downloaded you can run examples like so:

# To run SingleMachine.py example navigate to the root folder of SimPROCESD
# and run the following command:
python -m examples.SingleMachine

SingleMachine.py

• Basic setup: Source -> Machine -> Sink

BufferExample.py

• Using a Buffer.

ParallelStations.py

• Multi-stage production line with multiple machines in each stage running in parallel.

VariousFlows.py

• Model with 2 parallel production paths that both share one of the machines.

• Visual representation of the setup (see below):

  • Top diagram: the design being modeled with M3 machine as part of 2 production paths.

  • Bottom diagram: the actual model layout with a single M3 machine followed by 2 filters (DecisionGate) that control part flow.

PartQuality.py

• Changing/updating part quality when parts are processed by machines.

ExtendingPartObject.py

• New class that extends Part in order to add a new property.

• Example model using the new class.

FilterParts.py

• Setup DecisionGate devices to manage where parts go based on part quality.

OperatingSchedule.py

• Using ActionScheduler to control when a machine can produce parts.

BatchProcessing.py

• Using Batch part type vs using individual parts.

• Using PartBatcher to batch and unbatch parts.

SingleMachineWithFaults.py

• Using an extended machine class to model periodic faults.

• Configuring maintenance times determined by a geometric distribution.

• Request maintenance when machine has a fault.

SharedResources.py

• Setting up machines that have to reserve limited resources in order to process parts.

ConditionBasedMaintenance.py

• Using an extended machine class to model accumulating damage on the machine.

• Use sensors to periodically measure machine damage and request maintenance if damage is over threshold.

MaintenanceOptimization.py

• Setup 5 parallel machines that accrue damage which negatively impacts part quality.

• Run a series of simulations where a different damage threshold is used to trigger machine maintenance.

• Show final results in graphs to assist with deciding the best maintenance policy.

DataExploration.py

• Setup a Buffer with a sensor measuring buffer level (how many parts it is holding).

• Setup parallel machines that accumulate damage over time at different rates.

• Quality of parts is reduced based on machine’s accrued damage since last maintenance.

• Machines are maintained only when they experience a hard failure.

• Demonstrate using built-in graph functions and plotting data.

• Cumulative average throughput over time.

• Machine damage over time.

• Cumulative costs/values associated with sourcing parts and final part products.

• Buffer level over time.

SaveSimulationToFile.py

• Example of saving the System object to a file and loading it back from the file.

PaperMillCmsEvaluation.py[Experiemental]

• Simulate a manufacturing system with and without Condition Monitoring System (CMS) to get expected benefit of using a CMS.

• Setup a simulated CMS that tracks machine status through a sensor of part quality and has configurable false alert and missed alert rates.

• Setup machines with periodic soft faults, cost of maintenance, and cost of false alerts.