International audienceWhen designing a new family of products, designers and manufacturers must define the product family and its supply chain simultaneously. At the very first step of the design process, designers propose various solutions for the set of variants of a product family and their bill-of-materials. The second step is to select some of these variants while choosing the architecture of the supply chain. A mixed integer linear programming model is investigated that optimizes the operating cost of the resulting supply chain while choosing the product variants. This work is applied to the problem of an automotive supplier

International audienceIn the modern supplier-customer relationship, Vendor Managed Inventory (VMI) is used to monitor the customer's inventory replenishment. Despite the large amount of literature on the subject, it is difficult to clearly define VMI and the main associated processes. Beyond the short-term pull system inventory replenishment often studied in academic works, partners have to share their vision of the demand, their requirements and their constraints in order to fix shared objectives for the medium/long-term. In other words, the integration of VMI implies consequences for the collaborative process that links each partner's different planning processes. In this article we propose a literature review of VMI. Based on the conceptual elements extracted from this analysis, we suggest a VMI macro-process that summarises both operational and collaborative elements of VMI

Demand driven material requirements planning or DDMRP is a recent and promising material management method that has been developed and implemented in the practitioner world. Essentially, DDMRP represents a rethinking of the basic MRP logic. By incorporating elements drawn from Lean Systems and the Theory of Constraints and by introducing new features such as dynamic buffers, DDMRP modifies the basic MRP logic so that it is better able to satisfy customer demands in an increasingly demanding, turbulent and dynamic environment. Claims have been made by firms that DDMRP represents a superior planning approach. In this paper, we introduce and explore DDMRP. In addition, we evaluate its effectiveness relative to two other widely accepted approaches -MRP II and Kanban/Lean productionthrough a series of structured computer simulation experiments. The results strongly indicate that DDMRP does represent a superior approachone that warrants further academic study.

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Hospitals are starting to move away from traditional based-systems to the information technology based-systems. Today, Internet of Things (IoT), Body Sensor Network (BSN), Modeling, Simulation, and Artificial Intelligence (AI) are core technology elements that will be used in hospital of the future to improve the quality of patient care. Collecting the patient's data and monitoring their states and behavior became mandatory to improve their care. This paper proposes a novel framework for supporting the hospital of the future named HospiT'Win. This framework uses the core technology elements mentioned above to create a digital twin, that is a virtual replica of the hospital, allowing the health care providers to trace the patient's pathways data, monitor their behaviors, and predict their near future outcomes. So that, they can provide the right care in a right place, and in a right time. The paper explains in details the main components, the structure, and the way to synchronize the state and the behavior of the digital twin with the patients pathways in the real hospital. In case of unexpected events, HospiT'Win predicts the near future to see their impact on the real hospital. Moreover, it provides the possible solutions to minimize the impact of these events to preserve the quality of health care inside the hospital.Index Terms-Digital Twin, Hospital of the Future, Internet of Things, Modeling, Simulation.

International audienceQuality control lead times are one of most significant causes of loss of time in the pharmaceutical and cosmetics industries. This is partly due to the organization of laboratories that feature parallel multipurpose machines for chromatographic analyses. The testing process requires long setup times and operators are needed to launch the process. The various controls are non-preemptive and are characterized by a release date, a due date and available routings. These quality processes lead to significant delays, and we therefore evaluate the total tardiness criterion. Previous heuristics were defined for the total tardiness criterion, parallel machines, and setup such as ATC (Apparent Tardiness Cost) and ATCS (ATC with setups). We propose new rules and a simulated annealing procedure in order to minimize total tardiness