PhD Candidate - Heterogeneous Fleet Management for Resilient Intralogistics under Nominal and Exceptional Flows

1. POST ENVIRONMENT

School of the ministry in charge of industry, IMT Mines Albi is a school of the Institut Mines-Télécom, 1st group of engineering and management schools of France. At the forefront of industrial and academic issues on the international scene, it acts as a territorial scientific and economic engine by combining its 4 missions - to train engineers by integrating the dynamics of sustainable development, scientific research, contributing to economic development and spreading the culture of science, technology and innovation - in a virtuous and innovative cycle.

Its positioning in terms of training and research places IMT Mines Albi as a reference school on three of the four themes of the Institut Mines-Télécom: responsible future industry, energy, circular economy and society, and engineering, health and well-being.

The doctoral position is hosted by the Industrial Engineering Center of IMT Mines Albi. The center develops research on the modelling, design, control and evaluation of industrial, logistics and socio-technical systems, with a strong emphasis on decision support, performance assessment and industrial transfer.

The PhD will be carried out in the context of a collaborative research project with an aircraft manufacturer. It will focus on the design, comparison, dimensioning and control of intralogistics systems that combine nominal production flows with exceptional flows in an aerospace final assembly environment.

2. MAIN MISSIONS AND ACTIVITIES

1. Scientific positioning and research objectives

In line-side logistics, intralogistics systems are often designed and evaluated against nominal production flows associated with standard assembly schedules. In practice, a significant part of the activity is generated by late replanning, quality events, missing or misplaced items, returns, rework and other exceptional flows. These flows consume logistics resources irregularly, create trade-offs between nominal service and urgent requests, and may affect line-side performance through shortages, micro-stops or workarounds.

The thesis will investigate how to compare, dimension and control heterogeneous intralogistics systems under uncertainty, when part of the workload is difficult to predict but critical for production continuity. The research will contribute to resilience-by-design approaches for production logistics, where capacity, slack, pooling and prioritization rules are evaluated not only as costs but also as levers for robust service.

• Define a measurable framework for nominal and exceptional intralogistics flows in a perimeter covering picking from warehouse to line-side, kitting, supermarkets, line feeding and returns.

• Compare alternative segmentation and distribution schemes for intralogistics flows, including the conditions under which each scheme is relevant.

• Model the coupling between logistics resources, exceptional flows and production performance at line-side level.

• Evaluate dispatching, prioritization, preemption, pooling and resource allocation policies for heterogeneous fleets and logistics resources, for example automated, semi-automated and human-operated resources.

• Assess effective capacity, service robustness and recovery capability under variability, resource unavailability, urgent requests and changes in production priorities.

• Identify operational and structural levers to reduce the frequency, criticality or impact of exceptional flows while preserving cost and service performance.

2. Methods, activities and expected outputs

• Carry out an operational mapping of the selected intralogistics perimeter, actors, resources, flow families, interfaces and risk points.

• Build a baseline of nominal and exceptional flows, including volumes, variability, criticality levels and service indicators.

• Develop discrete-event and/or agent-based simulation models coupling nominal flows, exceptional flows, heterogeneous resources and line-side service requirements.

• Design and compare optimization-based or rule-based dispatching policies for priority management, resource allocation and arbitration between nominal and urgent activities.

• Run simulation experiments and stress tests to compare logistics configurations, distribution schemes and control policies against performance, robustness and resilience indicators.

• Produce scientific publications, project deliverables, prototype models or dashboards, and operational recommendations for industrial deployment.

• Participate in project meetings, field interactions with the industrial partner, academic seminars and international conferences.

3. TRAINING AND SKILLS

Minimum required level of training and/or experience:

• Master's degree, engineering degree or equivalent degree in industrial engineering, supply chain management, logistics, operations research, production systems, data science, simulation, decision sciences, or a related field.

• A strong academic record and a clear motivation for doctoral research in close interaction with industrial partners.

Knowledge, soft skills and experience

• Knowledge of industrial engineering, production logistics, intralogistics, operations research, simulation, data analysis or decision-support methods.

• nterest in production systems, logistics automation, heterogeneous resources, line-side service, robustness and resilience of industrial systems.

• Initial experience with discrete-event simulation, agent-based simulation, optimization, dispatching policies or experimental design would be appreciated.

• Programming skills in Python, R, simulation software or equivalent tools would be an asset.

• Good written and oral communication skills in English. French language skills is expected to have smooth interaction with the industrial partners.

Abilities and aptitudes

• Ability to structure complex operational situations into research questions, models, scenarios and performance indicators.

• Capacity to interact with industrial stakeholders, understand field constraints and translate them into modelling assumptions.

• Analytical rigor, autonomy, curiosity, synthesis skills and interest in applied research.

• Ability to communicate results to both scientific and industrial audiences.

4. ADDITIONAL INFORMATION

• Application package: curriculum vitae, cover letter, academic transcripts, Master thesis or report if available, and contact details for references.

• Applications and informal enquiries may be sent to Eva Petitdemange and Jacques Lamothe: eva.petitdemange@mines-albi.fr  Jacques.lamothe@mines-albi.fr .

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

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