Internship OPTIMAN : Design and optimisation of a Physical and Virtual Model of a Flexible and Robotised Production Workshop: machining cells application CESI

Laboratory presentation

CESI LINEACT (UR 7527), Laboratory for Digital Innovation for Businesses and Learning to Support the Competitiveness of Territories, anticipates and accompanies the technological mutations of sectors and services related to industry and construction. The historical proximity of CESI to companies is a determining factor in our research activities. It has led us to focus our efforts on applied research close to companies and in partnership with them. A human-centered approach coupled with the use of technologies, as well as territorial networking and links with training, has enabled the construction of cross-cutting research; it puts humans, their needs, and their uses at the center of its issues and addresses the technological angle through these contributions.

Its research is organized according to two interdisciplinary scientific teams and several application areas.

• Team 1 'Learning and Innovating' mainly concerns Cognitive Sciences, Social Sciences, and Management Sciences, Training Techniques, and those of Innovation. The main scientific objectives are the understanding of the effects of the environment, and, more particularly, of situations instrumented by technical objects (platforms, prototyping workshops, immersive systems...) on learning, creativity, and innovation processes.

• Team 2 'Engineering and Digital Tools' mainly concerns Digital Sciences and Engineering. The main scientific objectives focus on modeling, simulation, optimization, and data analysis of cyber-physical systems. Research also focuses on decision-support tools and on the study of human-system interactions, particularly through digital twins coupled with virtual or augmented environments.

These two teams develop and cross their research in application areas such as

• Industry 5.0,

• Construction 4.0 and Sustainable City,

• Digital Services.

Areas supported by research platforms, mainly the one in Rouen dedicated to Factory 5.0 and the one in Nanterre dedicated to Factory 5.0 and Construction 4.0.

Abstract

This internship aims to design and evaluate a human-centred decision-support system based on a digital twin of a robotic machining cell, in order to jointly optimise production performance and operator well-being. In this cell, the production schedule combines manual operations performed by human workers with automatic operations executed by robots and CNC machines; therefore, the planning and its supporting tools must be explicitly human-centric and help improve working conditions rather than focus only on throughput.

Concretely, the intern will work on connecting an existing digital twin of the cell to a scheduling module (based on optimisation algorithms) and on designing interaction mechanisms that keep the human "in the loop": visualisation of schedules, comparison of alternative scenarios, simple actions such as changing priorities or shifting operations, and monitoring indicators related both to productivity (machine occupancy, lead times, utilisation) and to human factors (distribution of manual tasks, critical interventions, ergonomically unfavourable situations, perceived strain, etc.).

The internship is part of the OPTIMAN project conducted in collaboration with Maugars Industrie, which focuses on the optimisation and digitalisation of a robotic machining cell in an Industry 5.0 perspective. Within this context, the intern will build on an existing laboratory digital twin and will contribute to its integration with the scheduling tool and to the design of a first human-centred interface. Expected deliverables include: a connected and operational digital-twin/scheduler link, a set of representative test scenarios, a prototype of a human-centred interface, and a scientific report summarising the methods, experiments, and main insights for Industry 5.0 implementation.

Research Work

Industry 5.0 represents a strategic shift in production systems by combining advanced technologies-such as digital twins, collaborative robots and IoT-with a strong human-centred focus. Its ambition is to enhance the resilience of value chains, support environmental sustainability and improve operator well-being through intelligent and ergonomic work environments. Recent works highlight the need for open interoperability models and seamless integration between physical and virtual layers, relying on real-time communication, standardized data architectures and adaptive interfaces tailored to operators' needs (Gumzej & Rosi, 2023; Alexa et al., 2022; Partarakis & Zabulis, 2024). In parallel, research on collaborative robotics and digital twins shows that accurately modelling production cells makes it possible to simulate, monitor and remotely adjust complex industrial processes (Havard et al., 2021; Hémono et al 2024). When combined with human-aware planning approaches (e.g. fatigue-aware scheduling and break planning), these technologies contribute to reducing physical strain, improving safety and supporting more efficient decision-making on the shop floor (Chabane et al., 2023; Bouaziz, 2024; Hémono et al., 2025). In particular, the emergence of digital-twin-based control of robots offers a powerful way to manage smart systems interacting with human operators in increasingly uncertain industrial environments (Hémono et al., 2025).

Within this context, the Optiman project, conducted in partnership with Atelier Maugars, aims to develop a digital twin for a robotic cell, coupled with an instrumented physical model. The objective is to supervise and control machining machines in real time while integrating the latest advancements in human-machine interaction (Partarakis, 2024). This innovative approach not only enhances the responsiveness and reliability of production but also reduces the cognitive and physical load on operators. The implemented systems, based on cyber-physical systems and enhanced connectivity, will make the workshop more agile by facilitating adaptation to demand fluctuations and operational uncertainties. Ultimately, this project fully embodies the vision of Industry 5.0: combining industrial performance with consideration of human and environmental dimensions to foster resilience and sustainability.

This internship aims to design and develop the digital counterpart of an existing instrumented robotic model and to connect both parts in order to simulate, control, and test various human-machine interaction and communication scenarios. The physical cell has already been built and can be controlled from the laboratory; the core objective of the internship is therefore to develop the digital twin and ensure its real-time interaction with the physical system.

The expected outcomes include:

• Enhancing real-time supervision through a dynamic 3D digital representation of the cell.

• Validating innovative control and optimization algorithms for robotic cells using the digital twin as a safe testbed.

• Personalizing the user experience to improve operator efficiency and reduce workload strain.

Internship Phases:

1. Understanding the existing physical system (laboratory cell) and the objectives of the Optiman project.

2. Conducting a state-of-the-art review on digital twin technologies, communication architectures, and human-machine interaction in robotic cells.

3. Specifying the requirements and architecture of the digital twin (data model, 3D representation, communication interfaces).

4. Developing the digital model of the robotic cell and its interactive 3D visualization.

5. Implementing and testing the communication layer between the physical model and its digital twin (data exchange, synchronization,…

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