Print Email Facebook Twitter Towards the development of a Digital Twin for the improvement of cool chain operational quality Title Towards the development of a Digital Twin for the improvement of cool chain operational quality: A KLM Cargo case study Author Sijtsma, Jorrit (TU Delft Mechanical, Maritime and Materials Engineering) Contributor Pang, Y. (mentor) Negenborn, R.R. (graduation committee) Nicolet, A. (graduation committee) Degree granting institution Delft University of Technology Programme Mechanical Engineering | Multi-Machine Engineering Date 2023-02-23 Abstract The demand for accurate and effective cool chains has been expected to increase, especially for pharmaceuticals in the air freight industry. However, several problems and challenges remain such as cool chain breaks and cool storage capacity constraints while there are rarely routine systems in place for consistent insight into the operational quality of such systems. Besides, the concept of a DT has received increasing attention in the literature, while a multitude of applications have been found in fresh cool chains. Therefore, the DT concept has been applied to a pharmaceutical cool chain for operational quality improvement. Firstly, a novel operational quality metric has been proposed: the OCCE. Consequently, a cool chain at KLM Cargo has been studied and modelled by means of the DES technique in order to derive a virtual representation. Consequently, the DT concept has been applied through the implementation of a decision support module for cool storage decision-making. The model implementation has shown that the cool chain operational quality has been improved while the average exposure of freight has decreased. Subject Digital TwinCool ChainDiscrete Event SimulationDecision Making To reference this document use: http://resolver.tudelft.nl/uuid:09681ddf-26dd-40dc-aa83-0433af58c4bf Part of collection Student theses Document type master thesis Rights © 2023 Jorrit Sijtsma Files PDF Thesis_Jorrit_Sijtsma_final.pdf 10.18 MB Close viewer /islandora/object/uuid:09681ddf-26dd-40dc-aa83-0433af58c4bf/datastream/OBJ/view