Abstract
The digital twin technology coordinates digital and physical spaces in order to improve the current and future actions in the system based on the real-time data. It allows organizations to follow and optimize their systems in a virtual environment before performing actions in reality. Digital twin can play a role in labor planning within an organization as well as in smart manufacturing environments such as performing the simulation of different scenarios, helping to determine the most efficient use of multi-skilled workers. In case of unexpected absences or changes in labor resource during a shift, organizations need to reconsider labor assignments to reduce downtime and inefficiencies. Traditionally, these actions are performed by the shift supervisor. In industry 4.0 concept, we design a digital twin-based decision support system with simulation capabilities for dynamic labor planning. The proposed system allows the unit to adapt to new conditions and also provides performance measures for the future state of the system. Additionally, the operator can simulate different scenarios and evaluate their performances. We present the results and performance of the proposed system on a case example.
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Soylu, B., Yildiz, G.B. (2024). A Digital Twin-Based Decision Support System for Dynamic Labor Planning. In: Şen, Z., Uygun, Ö., Erden, C. (eds) Advances in Intelligent Manufacturing and Service System Informatics. IMSS 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-6062-0_20
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DOI: https://doi.org/10.1007/978-981-99-6062-0_20
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