TY - JOUR
T1 - A material handling system modeling framework
T2 - a data-driven approach for the generation of discrete-event simulation models
AU - Soufi, Zakarya
AU - Mestiri, Slaheddine
AU - David, Pierre
AU - Yahouni, Zakaria
AU - Fottner, Johannes
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
PY - 2024
Y1 - 2024
N2 - The design and reconfiguration of Material Handling Systems (MHSs) at the factory scale are known to be complex. Various design and reconfiguration alternatives have to be considered and evaluated through indicators such as: On Time Delivery (OTD) within the plant, number of material shortages or product waiting time, etc. Due to the dynamic behavior of MHS, simulation-based approaches play an essential role in such analysis. However, developing simulation models for MHS can be time-consuming (especially for modeling Large Scale Systems) and difficult to build (some skills and knowledge are required to use simulation software). To overcome these challenges, data-driven approaches have been proposed in the literature for the generation of MHS simulation models. Nevertheless, the available approaches focus on specific domains and may not always account for all the necessary data, including MHS control policies. Therefore, this paper aims to propose a framework that employs a data catalog regrouping five data categories (layout, product features, production process, material handling process, and MHS control methods) to support the generation of MHS simulation models using SIMIO. The article details the data structure used to gather MHS simulation data, the selection of a simulation tool, the modeling patterns integrated into the simulations, and the application of the transformation rules. The whole approach is implemented to form the generation framework. The framework is designed to assist decision-makers (who have basic simulation knowledge) in the evaluation of MHS design/reconfiguration alternatives. The paper finally presents a validation of the framework on two case studies.
AB - The design and reconfiguration of Material Handling Systems (MHSs) at the factory scale are known to be complex. Various design and reconfiguration alternatives have to be considered and evaluated through indicators such as: On Time Delivery (OTD) within the plant, number of material shortages or product waiting time, etc. Due to the dynamic behavior of MHS, simulation-based approaches play an essential role in such analysis. However, developing simulation models for MHS can be time-consuming (especially for modeling Large Scale Systems) and difficult to build (some skills and knowledge are required to use simulation software). To overcome these challenges, data-driven approaches have been proposed in the literature for the generation of MHS simulation models. Nevertheless, the available approaches focus on specific domains and may not always account for all the necessary data, including MHS control policies. Therefore, this paper aims to propose a framework that employs a data catalog regrouping five data categories (layout, product features, production process, material handling process, and MHS control methods) to support the generation of MHS simulation models using SIMIO. The article details the data structure used to gather MHS simulation data, the selection of a simulation tool, the modeling patterns integrated into the simulations, and the application of the transformation rules. The whole approach is implemented to form the generation framework. The framework is designed to assist decision-makers (who have basic simulation knowledge) in the evaluation of MHS design/reconfiguration alternatives. The paper finally presents a validation of the framework on two case studies.
KW - Data-driven approach
KW - Discrete event simulation
KW - Manufacturing systems
KW - Material handling systems
KW - Performance analysis
UR - http://www.scopus.com/inward/record.url?scp=85188184775&partnerID=8YFLogxK
U2 - 10.1007/s10696-024-09535-z
DO - 10.1007/s10696-024-09535-z
M3 - Article
AN - SCOPUS:85188184775
SN - 1936-6582
JO - Flexible Services and Manufacturing Journal
JF - Flexible Services and Manufacturing Journal
ER -