Towards Digital Twin in intra-logistics. A press shop case

Nowadays, dynamic, complex, and uncertain environments may hinder the achievement of optimized production logistics. Digitalization helps improving operations planning and monitoring by enabling more effective decision-making through Digital Twins (DTs). Despite recent DT applications to intra-logistics, it lags behind manufacturing in digitalization and automation due to cost, time, and skill constraints, thus making research and practical applications in the field still limited. This paper presents a case study for the development of a Discrete Event Simulation model ready to evolve into a DT for the press shop end-of-line logistics in an automotive company. The model is applied to analyse the effects on selected Key Performance Indicators (KPIs) of strategies to move finished components to the warehouse. The KPIs concern the time press lines spend in a number of different states, such as set-up, working, or blocked because of unavailability of trains to move finished components from buffer areas, and the number of unit loads in the buffer areas at the end of each press line. As a next step, the simulation model will be further developed to transform it into a fully functional DT. Then, it will assist in studying the introduction of Automated Guided Vehicles to replace traditional tugger trains.