Abstract:The upcoming logistic environment is about to modify deeply the way we supply products. In fact, some new trends are going to require more and more agility between a large number of stakeholders in open and dynamic networks. This should be possible to achieve thanks to new data collection and treatment abilities. Considering this moving technological and logistic environment, it appears necessary to define and categorize more specifically the main disruptive events that can affect a supply chain. In fact, amount of data are collected on the field and must be helpful to make relevant decisions in case of disruption. In order to understand automatically what these data mean, it is necessary to detect and classify the disruptive events in order to find the best adaptation. This paper focuses on the sensitive products' supply chains, that are facing with agility high requirements, based on their ability to detect disruptive events. We take as an example the blood supply chain.
Sensitive products supply chain and supply chain facing crisis management share several aspects. In both cases, several decision makers have to choose the best options most of the time under pressure, often in emergency and need to access numerous information from the field. This shared monitoring aspect put forward the visualization need to consider in each decision all the crisis potential impacts. Unfortunately, for the transportation steps we focus on, the current transport management systems do not reach these requirements. In this paper, focusing on supply chains during crisis situations, we present a new monitoring system with adapted functionalities. The added value is a connection in real time and relevant way the data from the field to the information on a shared model used to make reliable decisions. We use the French Blood Establishment supply chain to illustrate the proposition.
Internet of Things, connected devices, and other wireless sensors networks offer a number of new opportunities to manage transportation flows. This is particularly interesting for critical Supply Chains like Blood Supply Chains. In this research work, we investigate how such new technologies can enhance transportation system by better managing hazards and changes. By developing an event-driven decision support system, we demonstrate how a hyperconnected solution could change the way to design and control transportation routes. This decision support system will both inform users in real-time with relevant information and propose appropriate behaviors. This system will also allow improving the whole collaboration that exists between the shippers, the carriers and the customers. A dawning application to the Blood Logistics in France is developed to highlight potential benefits of such an approach.
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