This project aims to revisit the Supply Chain (SC) design models while considering an endogenous demand sensitive to the environmental performance, which distinguishes our work from existing models where demand is usually modeled as an exogenous parameter that does not depend on the model decisions. Indeed, on the one hand, the environmental performance has become a factor of competitiveness for companies and an important purchasing criterion for customers whether in the context of B-to-B or B-to-C. On the other hand, the environmental performance depends on the decisions undertaken at the design of SC such as location/allocation of production sites, choice of suppliers, selection of manufacturing technologies and transportation modes, etc. While this project is theoretical research-oriented, we are aware of the necessity of validating our assumptions and models by considering real-worlds situations. Two industrial areas are particularly interesting for us: mechanical manufacturing and food industry. With this objective in mind, we will collaborate with “pôle LUTB”, “pôle Viaméca” and the company Diana Food that accepted to provide us with data and relevant examples. First, we have to determine the attributes that affect demand. For instance, the carbon footprint is often considered, but it is a shortcut that is increasingly challenged by some comprehensive approaches such as the Life Cycle Analysis. Then, we have to build mathematical equations establishing the relationships between the environmental performance of a product and its demand level. The next step is to integrate the demand functions established in the previous phases in SC design models and to solve these models. Two main categories of models will be considered: - mixed integer linear programming that can integrate several decisions simultaneously, but often do not allow characterizing analytically the optimal solution, - analytical models that are more generic but offer the possibility of integrating complex demand functions and obtaining analytically the optimal solution. We will use advanced operations research techniques for modeling and solving. Finally, we will dedicate the last step to the validation and experimentation of the proposed models. In fact, we will use our models to show that ignoring the sensitivity of demand to the environmental performance could lead to inappropriate decisions. We will also try to derive insights such as the trade-off between local and international SC when the customers are sensitive to the environmental performance, the impact of customers’ environmental awareness on logistics decisions, the expected gain of a company that takes into account the sensitivity of customers to environmental performance and adapts its SC to meet customers’ requirements, etc.

In the context of a European initiative already launched and currently under building (Call NMBP 22-2017) the ‘PSS-EURO-Network’ MRSEI has the ambition to create and establish a European scientific network on the management of the transformation of industrial Business Models, through servitization innovation strategies. Within the scientific and industrial community which is currently actively working on Product-Service-Systems, a strong originality of the PSS-EURO-Network is to put the focus of the research on the methods and tools to transform the industrial organizations themselves and their Business Models, as a way to go beyond current European researches focusing mainly on the engineering of the PSS solution. With the ambition to create, then deploy concretely via European projects, a consistent set of methods and tools aiming at strongly increasing the success rate of industrial Business Models transformations towards PSS solutions, the PSS-EURO-Network can bring important societal impacts via the transformation of consumptions behaviors thanks to the product-service approach. The first European project answer taken in charge by this PSS-EURO-Network is already quite mature, and the definition of the scientific aims, research program and full consortium is already well advanced for the first phase of the submission: a summary is given in the following sections. The project coordinated by ARMINES-Mines Saint Etienne has a large European representation, first based on 5 key scientific laboratories gathering strong complementary competencies on PSS and Business Models (France, Denmark, Germany, Italy, and United Kingdom). But, additionally, the consortium includes a rather large network of industrial and transfer actors (still under building), aiming at a large European impact of these research works. The activity program defined in the MRSEI project has the ambition not only to build a first submission to a European call (covering the finalization of phase 1 and all the phase 2) , but also to build a longer term active Network, with a clear Strategy of European project building. This PSS-EURO-Network would also use Digital Technology through a living internet virtual community, which would be created and implemented operationally thanks to the MRSEI project

Machines and software acting on behalf of humans (i.e. agents) get more autonomy and are increasingly less under the control of human operators or users. Therefore especially when machines interact with humans, we need to ensure that they do not harm them or threaten their autonomy. Consequently the question of an ethical regulation and control of such autonomous agents is raised and has been discussed in the literature, stressing the need of ethical standards. The objective of the ETHICAA project is to define what should be an autonomous entity that could manage ethical conflicts, considering both the individual agent and the multi-agent levels. The ethical conflicts that will be considered are those occurring 1) inside one agent, 2) between one agent and the ethical principles and values of the system it belongs to, 3) between one agent and a human operator or user, 4) between several agents including or not human beings. Ethical conflicts are characterized by the fact that there is no « good » way to solve them. Nevertheless when a decision must be made it should be an informed decision based on an assessment of the arguments and values at stake. The models, methods and tools developed within the project will contribute to define the ETHICAA framework for the definition and management of agent systems featuring ethical behaviours. ETHICAA proposes to base the achievement of this objective on two applicative domains: robotics and privacy management. These two domains have been chosen for their impact on society in terms of trust, acceptance and ethics. In the robotic domain, the ETHICAA framework will be used to manage ethical conflicts arising in the cooperation between one artificial agent and one human operator in the context of the joint operation of a UAV (Unmanned Air Vehicle). In the case of privacy management, ethical conflicts may arise between multiple artificial agents and human users inside a social network where ethical autonomous agents control and manage the privacy policies of the accounts owned by humans. The results targeted by the ETHICAA project are (i) formal representation of ethical principles, values and conflicts, as well as (ii) automatic reasoning models to handle these ethical representations, (iii) all being validated on real world scenarios. Consequently the outcome of ETHICAA is composed of a framework and recommendations to design ethical systems of artificial agents, i.e. able to execute ethical regulation modes depending of the context and ethical conflicts involving other agents or humans.

Sludge (also known as biosolids) treatment and management is a growing challenge for municipalities around the world. If all of the wastewater from the world’s urban population was collected and treated, 83 Mt of dry sewage sludge would be generated by 2017.The cost of biosolids treatment constitutes to approximately half of the cost of wastewater treatment, and the quantities continue to increase as new wastewater treatment facilities are built and the existing ones are upgraded to keep up with the growing population and stricter regulations. Sludge treatment and management is going to be a major challenge in the next decade. The goal of this research is to investigate the in-line and real-time use of novel holistic sludge descriptors to measure, monitor, model and predict sludge behavior through sludge treatment processes and use this knowledge for the optimization of design and operation of treatment processes. Based on the knowledge generated from this research, our ultimate goal is to develop in-line and real-time optimization and automation systems for sludge treatment processes with support from our industrial partners. The research will help to optimize sludge treatment processes, improve their performance while reducing the operational costs and the environmental impacts. This will result in important savings for treatment plants. Sludge rheology, far UV (FUV), near infrared (NIR) and electrical impedance (EIS) spectroscopies, and water activity will be used as holistic descriptors to capture the changes in sludge characteristics, flow, and behavior. These descriptors can be measured in-line and real-time, and they are non-destructive to sludge matrix. Therefore, they can be successfully used for optimization and automation of treatment processes. Both lab-scale and full-scale tests will be carried out in this study. The team will also complete an evaluation of environmental and economic impacts of treatment improvements and alternatives.