A Smart Industrial Information System using a Business Process Model, Discrete Events Simulation, Optimization, and Machine Learning Algorithms

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24620%2F25%3A00013589" target="_blank" >RIV/46747885:24620/25:00013589 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2452414X25001190" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2452414X25001190</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jii.2025.100896" target="_blank" >10.1016/j.jii.2025.100896</a>

Result language

angličtina

Original language name

A Smart Industrial Information System using a Business Process Model, Discrete Events Simulation, Optimization, and Machine Learning Algorithms

Original language description

In industrial systems, managers face the critical challenge of efficiently managing resources to reduce production costs and time while maximizing profits. To address these challenges, production managers require advanced industrial information systems that optimize production time, costs, and profits. This paper presents a smart industrial information system that integrates Business Process Model and Notation (BPMN), AnyLogic simulation software for Discrete Event (DE) modeling, Response Surface Methodology (RSM), and Machine Learning (ML) algorithms. The system’s effectiveness is demonstrated through its application in an industrial steel skeleton production facility in Iran. To enhance revenue, we optimize key factors of the production process through simulation. Various ML algorithms, including Random Forest (RF), Random Tree (RT), and Bagging, were employed to improve system performance, with the Bagging model yielding the best results. The findings indicate that small hardener chamfer and welder for spare parts, with P-values of 0.0002 and %620.0001 respectively, are the most significant parameters impacting total costs and profits. Ultimately, the proposed industrial information system provides a cost-effective simulation approach that improves process-driven business operations, aligning with BPMN standards and economic criteria.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

21100 - Other engineering and technologies

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of industrial information integration>

ISSN

2467-964X

e-ISSN

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Volume of the periodical

47

Issue of the periodical within the volume

SEP

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

19

Pages from-to

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UT code for WoS article

001523482300001

EID of the result in the Scopus database

2-s2.0-105009091443