Quantifying Transparency in Production Logistics: An Improved Process Modelling Technique for Supporting Digital Transformation

Background: Production systems are complex environments where logistics processes play a crucial role alongside manufacturing. Although the digitalisation of value-creating processes is increasingly important, production-supporting logistics activities are often missing from digital models. Their absence reduces the accuracy of digital representations and may lead to suboptimal operational decisions. Methods: This study reviews digitalisation solutions in manufacturing systems with a focus on integrating production logistics activities. Relevant research articles are analysed, and integration problems are organised into a problem tree supported by practical experience. Based on these findings, an extended process modelling methodology and related indicators are applied to quantify digital transparency. The methodology is demonstrated through tests on a physical laboratory model. Results: The literature review and practical observations highlight several issues that hinder the integration and quantification of production logistics activities in digital models. The proposed modelling approach addresses these challenges by defining appropriate modelling depth and placement of logistics processes, enabling a clearer evaluation of digital transparency. Conclusions: Experiments conducted on the physical model confirm the feasibility of the methodology. The approach provides an important initial step toward the digital integration of production logistics and supports the development of more effective digital twin models for industrial applications in future research.

Authors

Institutions

Publication Details

Journal
Logistics
Published
2026-04-14
DOI
https://doi.org/10.3390/logistics10040091
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantifying Transparency in Production Logistics: An Improved Process Modelling Technique for Supporting Digital Transformation

Krisztián Bóna, Petra Molnár-Major
Logistics
Digital Transformation in Industry
article

Quantifying Transparency in Production Logistics: An Improved Process Modelling Technique for Supporting Digital Transformation

Krisztián Bóna, Petra Molnár-Major
article en

Abstract

Background: Production systems are complex environments where logistics processes play a crucial role alongside manufacturing. Although the digitalisation of value-creating processes is increasingly important, production-supporting logistics activities are often missing from digital models. Their absence reduces the accuracy of digital representations and may lead to suboptimal operational decisions. Methods: This study reviews digitalisation solutions in manufacturing systems with a focus on integrating production logistics activities. Relevant research articles are analysed, and integration problems are organised into a problem tree supported by practical experience. Based on these findings, an extended process modelling methodology and related indicators are applied to quantify digital transparency. The methodology is demonstrated through tests on a physical laboratory model. Results: The literature review and practical observations highlight several issues that hinder the integration and quantification of production logistics activities in digital models. The proposed modelling approach addresses these challenges by defining appropriate modelling depth and placement of logistics processes, enabling a clearer evaluation of digital transparency. Conclusions: Experiments conducted on the physical model confirm the feasibility of the methodology. The approach provides an important initial step toward the digital integration of production logistics and supports the development of more effective digital twin models for industrial applications in future research.

LogisticsVol. 10(4)
Budapest University of Technology and Economics (HU)
Nemzeti Kutatási, Fejlesztési és Innovaciós Alap
Openalex Percentile: Top 24%
Digital Transformation in Industry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.