Industry 4.0 brings a revolution in the way to create and think of products. Consumer needs change rapidly and production systems must adapt quickly to market changes by changing processes, resources, and configurations. In this context, as real manufacturing systems are subject to constant change, simulations can easily become obsolete. This reduces the lifetime of the simulation model, causes repeated disruption in industrial planning support, and consequently continuous maintenance by experts. Within this framework, the novelty of the following research is the development of a flexible and resilient simulation model able to adapt according to its physical counterpart. Through advanced modeling, based on the object-oriented programming paradigm, an automated simulation model has been developed. This model adapts based on input data, ensuring accuracy and real-time planning support. The research is applied to a real case study of the production system of a world leader in the energy technology sector. The results show that the applied simulation tool can analyze different configurations and enhance production planning.
Automated simulation modeling: ensuring resilience and flexibility in Industry 4.0 manufacturing systems
Antonio Cimino;
2024-01-01
Abstract
Industry 4.0 brings a revolution in the way to create and think of products. Consumer needs change rapidly and production systems must adapt quickly to market changes by changing processes, resources, and configurations. In this context, as real manufacturing systems are subject to constant change, simulations can easily become obsolete. This reduces the lifetime of the simulation model, causes repeated disruption in industrial planning support, and consequently continuous maintenance by experts. Within this framework, the novelty of the following research is the development of a flexible and resilient simulation model able to adapt according to its physical counterpart. Through advanced modeling, based on the object-oriented programming paradigm, an automated simulation model has been developed. This model adapts based on input data, ensuring accuracy and real-time planning support. The research is applied to a real case study of the production system of a world leader in the energy technology sector. The results show that the applied simulation tool can analyze different configurations and enhance production planning.File | Dimensione | Formato | |
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