PhD Proposal : Dynamic Balancing under uncertainties for aircraft final Assembly lines

Global Information

This PhD will take place in the “Centre de génie industriel” at IMT Mines Albi (France)

• Location: Albi, CGI https://cgi.imt-mines-albi.fr/

• Expected start date: September or October 2026 depending on student availability

• Keywords: dynamic line balancing, operations research, robust optimization, workforce planning

Context

The design of assembly lines is a critical issue in industrial processes, with challenges at multiple levels (see references below): the integration of new technologies—from robotics to AI—to reduce and control operation times and improve the ergonomics of user interfaces; balancing the various workstations on the line and sizing technical requirements and human skills; information systems to ensure traceability and monitoring of flows; organizing and managing logistics to supply assembly stations; layout of the line in existing or new facilities; addressing flexibility needs (product mix, reconfigurability, schedules) and variabilities (in time, quality, or availability of assembly and logistics resources).

The project that funds this research project is led by an aeronautical manufacturer. It aims to design a final assembly line of aircrafts, considering the specificities of the aeronautics sector: large takt time, variability in the product mix, the size of the aircraft, which allows for multiple parallel work zones, dimensional diversity and the large number of components to manage,and the need for traceability of flows throughout the logistics chain, among others. Several PhD theses are being conducted in parallel, with the following topics, and will need to work synergistically:

•       Dynamic Balancing under uncertainties for aircraft final Assembly lines;

•       An immersive multi-user environment to assist in the layout of an assembly line within a building;

•       Heterogeneous Fleet Management for Resilient Intralogistics under Nominal and Exceptional Flows;

•       Evaluating the impacts of standardized, shared, and connected packaging to optimize the supply chain logistics for assembly lines.

Problem Statement

This PhD addresses the balancing and dynamic control of an aeronautical Final Assembly Line (FAL), a complex system characterized by strong industrial constraints: thousands of elementary tasks to organize, a long takt time, partial cobotization of operations, significant diversity in operator skills, the large scale of an aircraft offering parallel work zones, sensitivity of sizing variables to product mix, multiple sources of variability that require anticipating both nominal and degraded operating modes.

The first challenge is to develop a methodology to guide the selection of the most suitable line concept among existing models (moving line, pulse line, dock line, or hybrid) to ensure robust sizing under uncertainty and degraded modes. This involves identifying critical constraints, sources of variability and uncertainty, available forms of flexibility, and possible configurations to deduce the optimization levers to be exploited.

At a second level, the focus will shift to sizing the selected line configurations by addressing a line balancing problem. This includes assigning tasks to stations or zones, sizing and allocating resources (operators and equipment). The margins and levers identified in the first phase will enable the proposal of adaptation strategies (robustness- or dynamicity-oriented) to manage disruptions and line variability.

The proposed methodology will rely on an iterative process between these two levels: the line choices made in Level 1 will condition the line balancing in Level 2, whose results will, in turn, validate or invalidate initial assumptions, induce new configuration choices, or refine uncertainty scenarios.

The proposed concepts will be dynamically validated through simulation by a parallel post-doctoral study, using tailored indicators to assess the system’s ability to absorb variability (disruptions, product mix).

Research Problem Addressed in this Thesis

The main scientific challenges are methodological, modeling-related, and tied to combinatorial optimization in line balancing problems:

• How to articulate and guide the feedback loop between the different decision levels ;

• Which level(s) of granularity to consider in order to strike a balance between scalability, computation time, reproducibility of the balancing in simulation, and exploitation of flexibility;

• Modeling specific constraints and levers in this line balancing problem ;

• Decomposing the problem for its resolution through combinatorial optimization techniques ;

Action Plan

Proposed Action Plan for the Thesis

•       Conduct a literature review on line balancing models and resolution methods

•       Model and compare a priori the different types of aircarft assembly lines

•       Generate line configurations for study

•       Perform line balancing on the various configurations

•       Develop a macro-model of line balancing results to enable simulation

•       Compare line balancing outcomes and iterate back to refine line configuration modeling

   The position includes regular meetings with industrials, and opportunities to attend international conferences, and to undertake an academic exchange at a European partner institution, depending on the progress of the research and project opportunities.

  Possible teaching involvement at IMT Mines Albi may be considered, depending on the candidate profile and institutional needs.

References

Battaïa, Olga, et Alexandre Dolgui. 2022. « Hybridizations in line balancing problems: A comprehensive review on new trends and formulations ». International Journal of Production Economics, Special Issue celebrating Volume 250 of the International Journal of Production Economics, vol. 250 (août): 108673.

Sikora, Celso Gustavo Stall. 2024. « Balancing mixed-model assembly lines for random sequences ». European Journal of Operational Research 314 (2): 597‑611.

Sotskov, Yuri N. 2023. « Assembly and Production Line Designing, Balancing and Scheduling with Inaccurate Data: A Survey and Perspectives ». Algorithms 16 (2): 100.

IMT Mines Albi and CGI Laboratory

IMT Mines Albi, a school under the authority of the French Ministry of Industry, is part of the Institut Mines-Télécom, France’s leading group of engineering and management schools. At the forefront of industrial and academic challenges on the international stage, it acts as a scientific and economic driver for its region by combining its four missions—training engineers with a focus on sustainable development, conducting scientific research, contributing to economic development, and promoting the culture of science, technology, and innovation—into a virtuous and innovation-driven cycle.

Its position in education and research establishes IMT Mines Albi as a reference school in three of the IMT’s four thematic areas: future sustainable industries, energy - circular economy and society and, health and well-being engineering.

Through its Centre Génie Industriel (CGI), IMT Mines Albi conducts research at the intersection of artificial intelligence and industrial engineering, in collaboration with national and international public and industrial partners.

The Centre Génie Industriel (CGI) (cgi.imt-mines-albi.fr) comprises approximately 70 people, including 25 PhD students. The center focuses on supporting the transition of ecosystems by enabling responsible and sustainable decision-making in unstable or disrupted environments. This is achieved through the representation, modeling, and analysis of organizational data to formalize knowledge that leads to decision-making in heterogeneous, collaborative, uncertain, and/or disrupted contexts.

The CGI is structured around applied research axes and scientific programs. The research axes are:

• FLOWS: Flexible Logistics and Operations for Sustainable Worlds (this PhD contributes here).

• DiSCS: Digital Systems for Crisis Management and Security;

• TRACE: Territorial Resilience, Agility, and Circular Economy;

• WHOPS: Well-being and Health through Organizational Processes and Services.

The two core scientific programs underpinning these research axes are:

• HOPOPOP: Hybridization for Operations & Planning, Organizations & Performance, Optimization & Problem-solving (this PhD contributes here).

• AIME-DM: Automated Information Modeling and Extraction for Decision-Makers.

Profile and application:

Education

• Master’s or engineering degree in in Industrial Engineering (or computer science with experience in industrial engineering)

• Research experience and a clear motivation for doctoral research in interaction with industrials.

Core competencies

• Production planning and control, supply chain management

• Operations Research, combinatorial optimisation, robust optimisation, metaheuristics.

• Discrete event and multi-agent simulation

• Data science applications

• Software development skills (Java, Python)

• Strong proficiency in English (minimum level B2) and French (minimum level B2)

Transversal skills

• Autonomy and ability to work collaboratively within a research team.

• Motivation to contribute to industrial application of research.

Application

Application materials: CV, cover letter, summary of Master’s thesis or research work, transcripts, Recommendation letters  (in industry and research experience) and any other supporting documents.

Application deadline: June 7, 2026, 12:00 PM.

Notification for interview: no later than June 15th, 2026.

Contacts:

Jacques Lamothe, CGI IMT Mines Albi, jacques.lamothe@mines-albi.fr

Cléa Matinez, CGI IMT Mines Albi, clea.martinez@mines-albi.fr