The SCAN research laboratory

SCAN : a joint research laboratory which aim is to provide decision-makers with the keys enabling them to fully take account of the risks and opportunities to which their businesses are exposed, thereby improving the agility and resilience of their supply chains.

Le laboratoire commun SCAN entre l'IMT Albi et Scalian

SCAN laboratory: outlook for the SC4.0 theme and academic collaboration

In order to speed up the progress of our R&D work for supplier network management and to further increase its relevance, we decided to set up a dedicated research programme that enables Scalian to work more closely with suitable academic and private partners.

The SCAN programme (Systèmes de Collaborations Agiles et Numériques – Agile and Digital Collaborative Systems) is the result of a collaboration between IMT Mines Albi and the Scalian Lab. This partnership started in October 2019, for a renewable five-year period.
Its goals are to:

  • Develop an Agile supplier risk and opportunity management system
  • Design a well-equipped methodology for designing and improving business resilience

The aim is to provide decision-makers with the keys enabling them to fully take account of the risks and opportunities to which their businesses are exposed, thereby improving the agility and resilience of their supply chains. The work is based on an ability to develop models to:

  • Provide alerts for the near future
  • Assess the supposed consequences of these events (risks or opportunities) on the activity of the supply chain in question
  • Suggest, where appropriate, action plans to limit the impact of risks or take better advantage of opportunities.

The PhD theses

In 2021, three ongoing theses will address different aspects of the problem:

Research theme 1: Thesis by Nafé MORADKHANI

This thesis, which was started in late 2019, aims to define the mathematical concepts necessary for modelling and simulating collaborative networks. The principle is based on an analogy with the physical world, where the players in a network are solids that move in a performance space according to the forces acting on them and the environment.

In 2019 and 2020, the theoretical concepts necessary for the modelling of collaborative systems were defined and validated. Several simulations were carried out on known systems in order to validate our approach (epidemic evolution, polling station organisation in the USA).

The modelling framework was based on physical laws. It attempts to identify and model risks and opportunities as forces controlling the trajectory of a system affected by them.

Collaborative networks can therefore be described and implemented by dynamic components known as “concepts”. Physics of organisation dynamics (POD) applies physical laws to these systems to manage them in a dynamic context. The role of POD is to identify and model potential negative (risk) events, as well as potential positive (opportunity) events.

Work is continuing in 2021 to establish a deep learning approach (LSTM) to identify the forces acting on the network.

Research theme 2: Thesis by Thibaut CERABONA

Also begun in late 2019, this thesis aims to apply the new modelling concepts created to the area of strategic and tactical management of supplier networks. The models thus created, based largely on the SCORE framework, should make it possible to assess a supplier network’s performance, how it changes over time, and the impact of external events or internal decisions on the achievement of objectives.

Alongside the experiments to assess our approach on the epidemiological model, we designed an application case for supplier network management, which is more complex than the epidemiological model for validation.

We chose to model the Airbus civil aircraft assembly lines at the Blagnac site. This environment has the advantage of representing a controlled industrial context, with small-scale and yet complex production, since it is part of a supply network of several tens of thousands of highly diverse companies (raw materials, standard components, complex systems, chemicals, etc.). We used data from the Airbus assembly line organisation and interviews with experts in the field to create a realistic representation of this network and identify the right attributes and indicators.

We were therefore able to demonstrate that the proposed modelling approach remains valid for a more complex application than the previous one (epidemic spread), in the context of a network of suppliers. It was in fact possible to develop a functional model able to simulate supply chain operation (nominal or disrupted) over several months. It was then necessary to identify the forces acting on the system and the strategies that could influence its performance.

Project 3: Thesis by Mahsa MALEK

This thesis began in 2021 and focuses on decision-support models for optimising performance at the strategic and tactical level. Based on the modelling carried out, the results of this work should help guide the choices of decision-makers in order to achieve the desired performance goals as effectively as possible.

Les docteurs chercheurs au sein du laboratoire SCAN

Scientific contribution

The work carried out on this topic has already been reported in several communications at conferences and in peer-reviewed journals, including the following:

Bénaben, Frédérick, Matthieu Lauras, Benoit Montreuil, Louis Faugere, Juanqiong GOU, et Wenxin Mu. « Physics of Organization Dynamics: An AI Framework for opportunity and risk management », 1‑6. Shangai, China, 2019.

Bénaben, Frédérick, Jiayao Li, Ibrahim Koura, Benoit Montreuil, Matthieu Lauras, Wenxin Mu, et Juanqiong Gou. « A Tentative Framework for Risk and Opportunity Detection in A Collaborative Environment Based on Data Interpretation ». In Proceedings of the 52nd Hawaii International Conference on System Science. Hawaii, 2019.

Bénaben, Frédérick, Benoit Montreuil, Louis Faugere, Matthieu Lauras, Juanqiong Gou, et Wenxin Mu. « A Physics-Based Theory to Navigate Across Risks and Opportunities tn the Performance Space: Application to Crisis Management ». In Proceedings of the 53rd Hawaii International Conference on System Sciences, 2187‑96. Hawaii, 2020.

Cerabona, Thibaut, Matthieu Lauras, Louis Faugere, Jean-Philippe Gitto, Benoit Montreuil, et Frédérick Bénaben. « A Physics-Based Approach for Managing Supply Chain Risks and Opportunities Within Its Performance Framework ». In 21st Working Conference on Virtual Enterprises, 418‑27. Valence, Spain, 2020.

Moradkhani, Nafe, Louis Faugere, Julien Jeany, Matthieu Lauras, Benoit Montreuil, et Frédérick Bénaben. « A Physics-Based Enterprise Modeling Approach for Risks and Opportunities Management ». In 13th IFIP Working Conference on the Practice of Entreprise Modelling, 339‑48. Riga, Latvia, 2020.

Bénaben, Frédérick, Louis Faugere, Benoit Montreuil, Matthieu Lauras, Nafe Moradkhani, Thibaut Cerabona, Juanqiong Gou, et Wenxin Mu. « Instability is the norm! A physics-based theory to navigate among risks and opportunities ». Enterprise Information Systems, 25 janvier 2021, 1‑28.


Future prospects

In 2021, work will continue as a direct follow-on from the theses already started, in particular on the following aspects:

  • Identification of the forces at play: a methodology for determining these forces based on simulation and deep learning will be drawn up and tested;
  • The definition of an “atomic” conception of the representation models of collaborative networks: the first atoms will be conceptualised and tested on a supplier network management application;
  • Establishment of algorithms for optimising the performance of collaborative networks according to potential events and changes in context;
  • New use cases will be designed and implemented in the virtual reality prototype.

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