Implementing ManPy, a semantic-free open-source discrete event simulation package, in a job shop

Oladipupo Olaitana, John Geraghty, Paul Young, Georgios Dagkakis, Cathal Heavey, Martin Bayer, Jerome Perrin, Sebastien Robin

Research output: Contribution to journalConference articlepeer-review

Abstract

The cost of acquiring commercial simulation packages is considerably high and this might explain why organisations are often reluctant to make further investments on training and retraining of employees on simulation modelling. Ironically, the level of benefit derived from simulation is highly dependent on experimental, analytical and statistical skills of the user. These cost and skill requirements make simulation an unattractive decision support tool to SMEs and small multinational organisations. Proposed in this study is ManPy, a semantic-free open-source approach to discrete event simulation (DES), such that users with different levels of skills can derive considerable benefits from simulation. ManPy eradicates the high investments required for simulation modelling by making it possible for low skilled users to benefit from readily available generic modelling objects which are contributed to an open source platform by highly skilled simulation practitioners, statisticians and academics. Another benefit of ManPy is the ability to integrate with other enterprise planning tools for system knowledge extraction and real time simulation input data. Some of these benefits are demonstrated through the implementation of ManPy in a SME that specialises in rapid prototyping and rapid tooling.

Original languageEnglish
Pages (from-to)253-260
Number of pages8
JournalProcedia CIRP
Volume25
Issue numberC
DOIs
Publication statusPublished - 2014
EventInternational Conference on Digital Enterprise Technology - DET 2014 Disruptive Innovation in Manufacturing Engineering towards the 4th Industrial Revolution - Stuttgart, Germany
Duration: 25 Mar 201428 Mar 2014

Keywords

  • Job shop scheduling
  • Open source software
  • Simulation and optimization

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