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SOFTWARE

Simantha - Simulation for Manufacturing

Simantha is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it focuses on asynchronous production lines with finite buffers. It also provides functionality for modeling the degradation and maintenance of machines in these systems. Classes for five basic manufacturing objects are included: source, machine, buffer, sink, and maintainer. These objects can be defined by the user and configured in different ways to model various real-world manufacturing systems. The object classes are also designed to be extensible so that they can be used to model more complex processes.

In addition to modeling the behavior of existing systems, Simantha is also intended for use with simulation-based optimization and planning applications. For instance, users may be interested in evaluating alternative maintenance policies for a particular system. Estimating the expected system performance under each candidate policy will require a large number of simulation replications when the system is subject to a high degree of stochasticity. Simantha therefore supports parallel simulation replications to make this procedure more efficient.

Research Topics: Manufacturing: Manufacturing systems design and analysis, Manufacturing: Factory operations planning and control

Subject Keywords: discrete-event simulation, manufacturing, production, maintenance, python

Data Access

These data are public.

Data and related material can be found at the following locations:
Simantha

About This Dataset

Version: 1.0.0 Last modified: 2022-01-05

Cite this dataset

Hoffman, Michael , Dadfarnia, Mehdi , Drozdov, Serghei , Sharp, Michael (2022), Simantha: Simulation for Manufacturing , National Institute of Standards and Technology, https://doi.org/10.18434/mds2-2530 (Accessed 2022-04-20)

Advanced communications, Manufacturing, Factory operations planning and control, Manufacturing economics, Manufacturing systems design and analysis, Monitoring, diagnostics and prognostics, Process improvement, Process measurement and control, Mathematics and statistics, Modeling and simulation research and Numerical methods and software

Version

1.0.0

Type of Software

Discrete-Event Simulation Software

NIST Author

Mehdi Dadfarnia

Serghei Drozdov

Michael Sharp

Other Contributors

Michael Hoffman

Organizations

System/Platform Requirements

Using Simantha requires Python ≥ 3.6 and, optionally, SciPy ≥ 1.5.2 for running the included tests.

Licensing Information

NIST Disclaimer of Copyright and Warranty

This software was developed by employees of the National Institute of Standards and Technology (NIST), an agency of the Federal Government and is being made available as a public service. Pursuant to title 17 United States Code Section 105, works of NIST employees are not subject to copyright protection in the United States. This software may be subject to foreign copyright. Permission in the United States and in foreign countries, to the extent that NIST may hold copyright, to use, copy, modify, create derivative works, and distribute this software and its documentation without fee is hereby granted on a non-exclusive basis, provided that this notice and disclaimer of warranty appears in all copies.

THE SOFTWARE IS PROVIDED 'AS IS' WITHOUT ANY WARRANTY OF ANY KIND, EITHER EXPRESSED, IMPLIED, OR STATUTORY, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTY THAT THE SOFTWARE WILL CONFORM TO SPECIFICATIONS, ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND FREEDOM FROM INFRINGEMENT, AND ANY WARRANTY THAT THE DOCUMENTATION WILL CONFORM TO THE SOFTWARE, OR ANY WARRANTY THAT THE SOFTWARE WILL BE ERROR FREE. IN NO EVENT SHALL NIST BE LIABLE FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO, DIRECT, INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES, ARISING OUT OF, RESULTING FROM, OR IN ANY WAY CONNECTED WITH THIS SOFTWARE, WHETHER OR NOT BASED UPON WARRANTY, CONTRACT, TORT, OR OTHERWISE, WHETHER OR NOT INJURY WAS SUSTAINED BY PERSONS OR PROPERTY OR OTHERWISE, AND WHETHER OR NOT LOSS WAS SUSTAINED FROM, OR AROSE OUT OF THE RESULTS OF, OR USE OF, THE SOFTWARE OR SERVICES PROVIDED HEREUNDER.

Third-Party Endorsement Disclaimer

The use of any products described in this toolkit does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that products are necessarily the best available for the purpose.

Contact

Mehdi Dadfarnia

mehdi.dadfarnia@nist.gov

(301) 975-4251

Created April 20, 2022, Updated October 30, 2023