Automated Petri-net modelling based on production management data

6Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Timed Petri nets can be used for the modelling and analysis of a wide range of concurrent discrete-event systems, e.g. production systems. The present paper describes how to do so while starting from the information about the structure of a production facility and about the products usually given in production-data management systems. We describe a method for using these data to algorithmically build a Petri-net model. The timed Petri-net simulator, which was built in Matlab, is also described. This simulator makes it possible to introduce heuristics, and in this way production operations can be scheduled. To demonstrate the applicability of our approach, we applied it to a scheduling problem in a multi-product batch plant.

References Powered by Scopus

Petri Nets: Properties, Analysis and Applications

8590Citations
N/AReaders
Get full text

The application of Petri nets to workflow management

2243Citations
N/AReaders
Get full text

A state-of-the-art survey of dispatching rules for manufacturing job shop operations

818Citations
N/AReaders
Get full text

Cited by Powered by Scopus

A survey of data-based production scheduling methods

39Citations
N/AReaders
Get full text

Data-based scheduling framework and adaptive dispatching rule of complex manufacturing systems

34Citations
N/AReaders
Get full text

Industrial big data-based scheduling modeling framework for complex manufacturing system

18Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Gradisar, D., & Music, G. (2007). Automated Petri-net modelling based on production management data. Mathematical and Computer Modelling of Dynamical Systems, 13(3), 267–290. https://doi.org/10.1080/13873950600834082

Readers over time

‘10‘11‘13‘14‘16‘17‘19‘20‘21‘23‘2400.511.52

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 5

45%

Professor / Associate Prof. 2

18%

Lecturer / Post doc 2

18%

Researcher 2

18%

Readers' Discipline

Tooltip

Engineering 4

40%

Business, Management and Accounting 3

30%

Chemistry 2

20%

Computer Science 1

10%

Save time finding and organizing research with Mendeley

Sign up for free
0