Abstract
This research aims to develop a decision support tool to assess the probability of meeting customer deadlines, while considering the different risks associated with the various links in the supply chain (SC). The work was conducted in collaboration with a leading aeronautical industry. The tool developed enables real-time flow management, i.e. from a system initial state, we can define the delivery date of a product and calculate the on-time delivery (OTD) performance indicator over the horizon of our order book. The tool is composed of three essential components: i) input data, which includes data related to the characteristics of the system under study (flow diagram, lead time, cost, capacity) and data related to the risks associated with the system links. ii) a discrete event simulation (DES) model reproducing the studied system by integrating the risks to identify the delivery date of each product and iii) a performance evaluation tool to calculate the distribution of our performance indicator. A multi-scenario analysis was conducted by varying the different parameters of the system and analysing the impact on our OTD. An illustrative example based on real data was presented to show the interest of the developed tool.
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Hilali, H., Dallery, Y., Jemai, Z., Sahin, E. (2022). A Decision Support Tool to Assess the Probability of Meeting Customer Deadlines. In: Kim, D.Y., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. APMS 2022. IFIP Advances in Information and Communication Technology, vol 663. Springer, Cham. https://doi.org/10.1007/978-3-031-16407-1_63
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DOI: https://doi.org/10.1007/978-3-031-16407-1_63
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