Supply Chain​/Logistics Intern, Inventory Control & Analysis

Overview

The internship will be carried out within the Supply Planning department of Shell Chemicals Europe, supporting the supply chain operations for the integrated chemical manufacturing assets in Pernis and Moerdijk. The assignment focuses on investigating how emerging Agentic AI technologies can support tactical supply planning processes within a complex petrochemical production environment. The intern will analyse current planning practices, identify operational bottlenecks, and explore opportunities to improve planning responsiveness through AI-enabled decision support.

• Map and analyse current tactical supply planning processes and workflows.
• Identify planning bottlenecks, spreadsheet dependencies, and sources of response latency within the planning organization.
• Conduct literature research on Agentic AI, Digital Twins, AI-driven decision support, and supply chain planning.
• Interview planners, logistics specialists, and other stakeholders to understand business requirements and operational constraints.
• Analyse quantitative process data related to planning activities, response times, and manual workload.
• Design an Agentic AI framework to support multi-period supply planning under material balance and capacity constraints.
• Evaluate how AI-enabled planning solutions could improve decision-making efficiency, planner workload, and supply chain responsiveness.
• Develop practical recommendations for future implementation within Shell Chemicals.
• Present findings and conclusions to both academic and business stakeholders.

For the organization:
Improve understanding of current planning bottlenecks and process inefficiencies; identify opportunities to reduce manual planning effort and spreadsheet dependency; develop a practical Agentic AI framework applicable to tactical supply planning; generate recommendations for future digital transformation initiatives within Shell Chemicals Europe.

For the intern:
Apply academic supply chain management theories in a real industrial environment; gain experience in supply planning, process analysis, digital transformation, and AI applications; develop research, stakeholder engagement, data analysis, and problem-solving skills; understand how advanced planning and decision-support technologies can be applied within complex process industries; deliver a Master Thesis including findings, framework design, recommendations, and managerial implications.

• Current-state assessment of the existing supply planning process.
• Analysis of planning bottlenecks and opportunities for improvement.
• Agentic AI framework design for tactical supply planning.
• Final Master Thesis report.
• Final presentation with conclusions and recommendations for Shell Chemicals Europe.