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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

21100 - Other engineering and technologies

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Journal of industrial information integration>

ISSN

2467-964X

e-ISSN

—

Svazek periodika

47

Číslo periodika v rámci svazku

SEP

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

19

Strana od-do

—

Kód UT WoS článku

001523482300001

EID výsledku v databázi Scopus

2-s2.0-105009091443