Enhancing internal supply chain management in manufacturing through a simulation-based digital twin platform

Повышение эффективности управления внутренней цепочкой поставок в производстве с помощью платформы цифрового двойника на основе моделирования
Antonio Cimino, Francesco Longo, Giovanni Mirabelli, Vittorio Solina, Pierpaolo Veltri
2024-10-21

Make-To-OrderOil & Gas case studydata integration and standardizationinternal supply chainmulti-plant production planningobject-oriented simulationreal-time simulationscheduling rulessimulation-based digital twinwhat-if analysis
• Simulation-based digital twin platform for internal supply chain management. • Exploiting real-time simulation for multi-plant production planning. • Ease of use, flexibility and scalability for company competitiveness. • Data integration and standardization for efficient information flow. • Case Study in the Oil&Gas Sector for testing and validation. Digital Twin (DT) technology is profoundly changing the manufacturing landscape and supply chain management with its ability to create real-time digital replicas of physical processes, allowing for enhanced monitoring and optimized decision-making. However, the analysis of scientific literature reveals that further efforts are needed to spread the use of Industry 4.0 technologies, in the specific context of Internal Supply Chains (ISCs). The main aim of this study is to design, develop test and validate a multi-plant Simulation-Based DT production planning platform for ISCs management. A modular architecture is adopted, and the focus is on a Simulation-Based Digital Twin module, which uses an object-oriented structure and enables what-if analyses, involving several scheduling rules and ISC configurations. The proposed solution ensures flexibility and scalability, two crucial features in a constantly evolving market environment. The platform is tested and validated through a case study, involving a corporate group in the Oil & Gas manufacturing sector, which needs to improve the ISC performance, under a Make-To-Order production strategy. The comparison with a baseline scenario, where the platform is not adopted, shows that the proposed approach can significantly reduce the average flow time, the average tardiness, the number of late orders. This study has important practical implications because enables proactive and smart decision-making, aimed at resource optimization and continuous improvement, through predictive analytics and scenario analysis.
1
A modular, simulation-based Digital Twin (DT) platform was designed and developed for multi-plant internal supply chain (ISC) production planning.
2
Case study in an Oil & Gas manufacturing corporate group under Make-To-Order strategy validated the platform.
3
Compared to a baseline without the platform, the proposed approach significantly reduced average flow time, average tardiness, and number of late orders.
4
The DT module uses an object-oriented structure enabling what-if analyses with multiple scheduling rules and ISC configurations.
5
The platform emphasizes ease of use, flexibility, scalability, and data integration/standardization to support efficient information flow.
6
The platform enables proactive, smart decision-making through predictive analytics and scenario analysis for resource optimization and continuous improvement.

Simulation-based digital twin production-planning platform for multi-plant internal supply chain management

Improving internal supply chain performance metrics (average flow time, average tardiness, number of late orders) and enabling flexible, scalable what-if production planning, resource optimization and predictive scenario analysis under Make-To-Order multi-plant configurations

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2024-10-21
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Authors
Antonio Cimino
Francesco Longo
Giovanni Mirabelli
Vittorio Solina
Pierpaolo Veltri
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