A Reinforcement Learning Powered Digital Twin to Support Supply Chain Decisions

The complexity of making supply chain planning decisions is growing along with the Volatility, Uncertainty, Complexity and Ambiguity of supply chain environments. As a consequence, the complexity of designing adequate decision support systems is also increasing. New approaches emerged for supporting decisions, and digital twins is one of those. Concurrently, the artificial intelligence field is growing, including approaches such as reinforcement learning. This paper explores the potential of creating digital twins with reinforcement learning capabilities. It first proposes a framework for unifying digital twins and reinforcement learning into a single approach. It then illustrates how this framework is put into practice for making supply and delivery decisions within a drug supply chain use case. Finally, the results of the experiment are compared with results given by traditional approaches, showing the applicability of the proposed framework

Making Strategic Supply Chain Capacity Planning more Dynamic to cope with Hyperconnected and Uncertain Environments

Public and private organizations cope with a lot of uncertainties when planning the future of their supply chains. Additionally, the network of stakeholders is now intensely interconnected and dynamic, revealing new collaboration opportunities at a tremendous pace. In such a context, organizations must rethink most of their supply chain planning decision support systems. This is the case regarding strategic supply chain capacity planning systems that should ensure that supply chains will have enough resources to profitably produce and deliver products on time, whatever hazards and disruptions. Unfortunately, most of the existing systems are unable to consider satisfactorily this new deal. To solve this issue, this paper develops a decision support system designed for making strategic supply chain capacity planning more dynamic to cope with hyperconnected and uncertain environments. To validate this decision support system, two industrial experiments have been conducted with two European pharmaceuticals and cosmetics companies

Enabling supply chain agility and resilience improvement: toward a methodolody and platform

International audienceOur research ambition is to provide businesses with a methodology and platform able to guide them towards the improvement of their logistics network in terms of agility and resilience, and so of their overall supply chains performances. To minimize the efforts that businesses will have to provide, our methodology will enable the platform to automate the recommendations for logistics network performance improvements in terms of agility and resilience. To fulfil this ambition, we are combining two research projects: the Physical Internet Initiative and the IO-Suite project

Electrocardiographic correlates of mechanical dyssynchrony in recipients of cardiac resynchronization therapy devices

SummaryBackgroundThe relationship between electrical and mechanical indices of cardiac dyssynchronization in systolic heart failure (HF) remains poorly understood.ObjectivesWe examined retrospectively this relationship by using the daily practice tools in cardiology in recipients of cardiac resynchronization therapy (CRT) systems.MethodsWe studied 119 consecutive patients in sinus rhythm and QRS≥120ms (mean: 160±17ms) undergoing CRT device implantation. P wave duration, PR, ePR (end of P wave to QRS onset), QT, RR–QT, JT and QRS axis and morphology were putative predictors of atrioventricular (diastolic filling time [DFT]/RR), interventricular mechanical dyssynchrony (IVMD) and left intraventricular mechanical dyssynchrony (left ventricular pre-ejection interval [PEI] and other measures) assessed by transthoracic echocardiography (TTE). Correlations between TTE and electrocardiographic measurements were examined by linear regression.ResultsStatistically significant but relatively weak correlations were found between heart rate (r=−0.5), JT (r=0.3), QT (r=0.3), RR–QT intervals (r=0.5) and DFT/RR, though not with PR and QRS intervals. Weak correlations were found between: (a) QRS (r=0.3) and QT interval (r=0.3) and (b) IVMD>40ms; and between (a) ePR (r=−0.2), QRS (r=0.4), QT interval (r=0.3) and (b) LVPEI, though not with other indices of intraventricular dyssynchrony.ConclusionsThe correlations between electrical and the evaluated mechanical indices of cardiac dyssynchrony were generally weak in heart failure candidates for CRT. These data may help to explain the discordance between electrocardiographic and echocardiographic criteria of ventricular dyssynchrony in predicting the effect of CRT

Un système d'aide à la décision pour la planification capacitaire des chaînes logistiques sur un horizon long-terme : une approche d'ingénierie dirigée par les modèles

Long-term Supply Chain Capacity Planning (SCCP) aims to define the plan of all actions to perform that will shape the available and required capacity of supply chains over several years. When performing long-term SCCP, companies are confronted with a multitude of decision options and uncertainty sources as well as a highly dynamic supply chain environment. Each company configures its own Decision Support System (DSS) to perform SCCP, composed of a decision-making process, an information system, and people. Companies can take advantage of existing decision-making processes and information systems to build their own SCCP DSS. However, the literature review on existing decision-making processes and information systems for SCCP revealed the following three major limitations: first, existing solutions are time-consuming. This constrains companies to consider only a small number of alternative scenarios associated with decision options and uncertainty sources. And it makes it difficult to keep SCCP analysis up to date. Second, existing solutions are designed to perform SCCP analysis on predefined supply chains without considering the whole set of potential alternative configurations. Third, decision-makers are reluctant to accept optimization methods because of the lack of visibility of the analysis leading to the recommended solution. Therefore, this thesis describes a new SCCP DSS proposal aiming to overcome these limitations. It is composed of an SCCP decision-making process proposal relying on an SCCP information system proposal. The SCCP decision-making process proposal contains two processes: implementation and routine. The SCCP information system proposal contains two software programs: a computational software program and a business intelligence software program. The SCCP DSS proposal was validated by undertaking two industrial pilot projects with two industrial partners. The following two major benefits have been confirmed: first, SCCP analysis can be performed in encompassing a multitude of decision options and uncertainty sources at a pace allowing updates in accordance with the pace of supply chain changes. Second, it provides decision-makers with the visibility and understanding of the impacts of their respective decisions and uncertainty sources which bolster their confidence in the decisions they can make. Finally, avenues for future research have been identified, including an opportunity for designing a hyperconnected SCCP DSS that automatically gathers information and triggers decision-making meetings when necessary rather than on a predefined frequency.La planification capacitaire des chaînes logistiques (SCCP) sur un horizon long-terme a pour objectif de définir un plan d’actions contenant l’ensemble des actions qui vont façonner la capacité disponible et requise des chaînes logistiques sur plusieurs années. Lorsque les entreprises réalisent leur SCCP sur un horizon long-terme, elles sont confrontées à une multitude d’options décisionnelles et de sources d’incertitudes, ainsi qu’à un environnement très dynamique. Chaque entreprise met en place son propre système d’aide à la décision (SCCP DSS) pour réaliser sa SCCP. Ce DSS est composé d’un processus de prise de décisions, d’un système d’information, et de personnes. Les entreprises peuvent utiliser les processus de prise de décisions et systèmes d'information existants pour créer leur propre SCCP DSS. Cependant, la revue de littérature relative aux processus de prise de décisions et systèmes d'information existants pouvant servir à la création d’un SCCP DSS a révélé les trois limitations suivantes : premièrement, les solutions existantes sont très chronophages. Cette limitation contraint les entreprises à ne prendre en compte qu’un nombre limité de scénarios alternatifs associés aux options décisionnelles et aux sources d’incertitudes. De plus, cela rend difficile le maintien à jour des analyses SCCP. Deuxièmement, les solutions existantes sont conçues pour réaliser les analyses SCCP sur des chaines logistiques prédéfinies et figées, sans considération de l’ensemble des potentielles alternatives structurelles. Troisièmement, les décideurs sont parfois réticents face aux méthodes d’optimisation du fait du manque de visibilité sur le processus d’obtention de la solution recommandée. Ainsi, cette thèse décrit la proposition d’un nouveau SCCP DSS ayant pour objectif de solutionner ces limitations. Il est composé d’une proposition de processus de prise de décisions SCCP tirant profit d’une proposition de système d'information SCCP. Le processus de prise de décisions SCCP est composé de deux processus : implémentation et routine. Le système d'information SCCP est composé de deux logiciels : un logiciel calculatoire et un logiciel de business intelligence. La proposition de SCCP DSS a été validée en réalisant deux projets pilotes avec deux partenaires industriels. Deux bénéfices majeurs ont été identifiés : premièrement, cela permet de prendre en compte une multitude d’options décisionnelles et de sources d’incertitudes durant les analyses SCCP à un rythme permettant un maintien à jour de ces analyses. Deuxièmement, cela permet aux décideurs d’avoir de la visibilité sur l’impact que leurs options décisionnelles et sources d’incertitudes auraient sur l’entreprise, ce qui renforce leur confiance vis-à-vis des décisions qu’ils peuvent prendre. Finalement, des perspectives de recherche ont été identifiées, incluant notamment la conception d’un SCCP DSS hyperconnecté qui collecterait automatiquement les informations et déclencherait des réunions de prises de décisions seulement quand cela est nécessaire plutôt qu’à une fréquence prédéfinie

A Platform to Support Collaboration and Agility in Logistics Web

International audienceSince time immemorial, collaboration between entities (people, companies, states, etc.) is our world strength. However, this collaboration efficiency is always limited by our technology development speed. One of the current challenges is the difficulty to make interoperate different entities having their communication based on new information technologies (mainly because of the great diversity of these new information technologies). So, our research ambition is to define main concepts and an architecture for Mediation Information Systems (MIS). Firstly, MIS ables to make interoperate a multitude of different entities in order to allow them to reach common goals. Secondly, MIS being agile (i.e., being able to detect unexpected events and adapt in response). Finally, MIS implementing these two previous characteristics in an as automated way as possible (i.e., using as less human actions as possible). In this paper, we summarize the MISE (Mediation Information System Engineering) approach aiming to reach our MIS ambition, and we introduce the third iteration of this project. Finally, we illustrate our results using a logistic domain use case: French drug deliveries to pharmacies

A Platform to Support Collaboration and Agility in Logistics Web

International audienceSince time immemorial, collaboration between entities (people, companies, states, etc.) is our world strength. However, this collaboration efficiency is always limited by our technology development speed. One of the current challenges is the difficulty to make interoperate different entities having their communication based on new information technologies (mainly because of the great diversity of these new information technologies). So, our research ambition is to define main concepts and an architecture for Mediation Information Systems (MIS). Firstly, MIS ables to make interoperate a multitude of different entities in order to allow them to reach common goals. Secondly, MIS being agile (i.e., being able to detect unexpected events and adapt in response). Finally, MIS implementing these two previous characteristics in an as automated way as possible (i.e., using as less human actions as possible). In this paper, we summarize the MISE (Mediation Information System Engineering) approach aiming to reach our MIS ambition, and we introduce the third iteration of this project. Finally, we illustrate our results using a logistic domain use case: French drug deliveries to pharmacies

Strategic Supply Chain Planning and Risk Management: Experiment of a Decision Support System Gathering Business Departments Around a Common Vision

“© © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”International audienceStrategic supply chain planning and supply chain risk management are two fields of supply chain management that are inseparable nowadays. The ability to consider risks is essential to maintain business performance. In addition, integrating the different business departments’ visions in a common business vision is necessary to properly plan the future of a company. However, it is still a challenge for companies to design and maintain a decision-making process supporting strategic supply chain decisions that integrates risk management and unify business vision across departments. This paper relates an industrial experiment as an attempt to meet this challenge. This experiment was asked by a pharmaceutical company with the aim of supporting strategic decisions regarding its network of suppliers. It led to a decision-making process including the use of a computerized information system composed of a software for computations and a business intelligence software to easily make decisions. This process was put in practice on a pilot use case with two years old data. It resulted in the identification of several decisions that could have been made if the process was in operation two years ago, which is considered as a first validation of the approach. Finally, limitations have been identified regarding the data collection, opening avenues for future research on an innovative approach combining supply chain hyperconnectivity and event-driven principles

Towards Decision Support Automation for Supply Chain Risk Management among Logistics Network Stakeholders

International audienceThis paper is one pillar of a research project aimed to design a decision support system supporting collaborative Supply Chain Risk Management among logistics network stakeholders. It presents the motivation behind this objective, and the contribution towards this objective: a methodology to automatically deduce all the supply chain options enabled by a logistics network to fulfil the demand. This methodology is introduced as part of a decision support automation framework for Supply Chain Risk and Opportunity Management among logistics network stakeholders. The methodology focuses on strategic and tactical supply chain decisions, and on manufacturing stakeholders

Towards Hyperconnected Supply Chain Capability Planning: Conceptual Framework Proposal

International audienceThis paper is to drive research towards a methodology that will enable organizations to foster high performance when planning their supply chain capabilities in the Physical Internet (PI) era. It first introduces the relevant concepts to understand the specificities of performing Supply Chain Capability Planning (SCCP) in the PI era and deduces two enablers: hyperconnectivity and automation. Second, it assesses the relevance of the Sales and Operations Planning (S&OP) methodology to perform SCCP in the PI era and concludes that it would not be sufficient. Consequently, it third introduces the Hyperconnected Supply Chain Capability Planning (HSCCP) methodology and the associated conceptual framework proposal, aiming to fill the gaps left by the S&OP methodology to perform SCCP in the PI era. It finally concludes leading the limitations of this paper towards avenues for future research