Supply Chain: With their project now reaching the halfway mark, Scalian and IMT Mines Albi review the activities of SCAN, their joint laboratory
Two-and-a-half years on from the founding of their joint research laboratory SCAN (Systèmes de Collaborations Agiles et Numériques – Agile and Digital Collaborative Systems) Scalian, the international consultancy and engineering group, and IMT Mines Albi, the French engineering school, review their achievements so far. Dedicated to research and development (R&D) in supply chain management, the purpose of the laboratory is to help decision-makers better address the risks and opportunities facing their business, in order to improve the agility and resilience of their supply chains.
Immersive management based on artificial intelligence
In autumn 2019, Scalian and IMT Mines Albi began working together on a functional methodology for managing system performance by measuring threats and opportunities. By implementing practical application cases in various sectors of activity, the objective is to represent and measure the impacts of these threats and opportunities.
“Our aim here is to innovate in two ways. The first strand concerns the threats and opportunities, which are considered as forces, based on an approach known as Physics of Decision or POD. This approach implements an analogy with the physical forces governing reality, the attributes and characteristics of the system whose performance we aim to measure using a range of indicators. The second strand concerns the management environment, for which we have adopted an immersive approach based on virtual reality,” explains Julien Jeany, co-director of the SCAN joint laboratory and Head of the R&D and Innovation lab at Scalian.
One of these practical cases involved designing a cockpit using virtual reality to manage an aeronautical supply chain. The aim is to take a performance process with no disruptions to the supply chain and compare it with an alternative process in a three-dimensional space. This makes it possible to measure the impact of threats that could become problems, while also assessing the opportunities offered by the system, and seeing how they could be activated to counter these threats and return the system performance process to an optimal state.
From a human or user viewpoint, this management system is more intuitive than the existing dashboards, whose complexity and detailed figures are difficult to understand. The functional cockpit prototypes developed by the SCAN joint laboratory are already attracting a great deal of interest from industry.
A POD approach to better support decision-makers
In order to support decision-making, we need to clearly understand the impacts of different events in order to be able to reconfigure our actions and submit solutions in response to the events taking place.
The SCAN laboratory was commissioned to carry out a recovery mission for a manufacturer that was unable to deliver. Implementing the “Physics of Decision” approach, the laboratory was able to study the current operation of the production chain, and precisely assess the impacts on different indicators, in order to identify the various cycles and possible decisions. The model illustrating the operation of the system under study must be sufficiently detailed to effectively simulate reality, prior to integration with the management environment.
“Today, instability has become the norm. One crisis follows another in rapid succession and reliability is no longer part of the global paradigm. Through this POD approach, we are able to support decision-makers and help them to understand not only the dynamics governing their system, but also the type of disruption likely to have a significant impact,” adds Julien Jeany.
A concept extending well beyond supply chain management
Initially, research focused on managing the threats and opportunities that can impact a system such as a supply chain. Later, the laboratory found that this concept could be extended to any system whose performance can be measured through indicators. Practical application cases have thus been developed, such as the management of a crisis relating to the reconfiguration of road networks following floods in the city of Nantes, or more recently, the management of health crises such as those experienced with COVID-19.
A large-scale project was also developed with Georgia Tech in the United States during the last US presidential elections. The SCAN laboratory sought to model the polling station set up on campus in order to optimise the flow of voters and the time taken to vote at the polling station. This practical case addresses problems arising from the highly complex voting process in the United States, where issues relating to machine availability can hamper the smooth running of the election.
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