Mutli-echelon inventory optimization for complex aerospace supply chain - QC-095

Preferred Disciplines: Industrial Engineering, Data Science, Operations Research. Level: Masters; PhD and postdoc
Project length: Flexible/variable
Desired start date: ASAP
Location: Montreal (Quebec)
No. of Positions: Flexible/variable
Preferences: All Canada. English or bilingual.
Company: N/A 

About Company:

A world-class  company in the design and manufacture of aircraft engines 

Project Description:

The supply chain of aircraft engine assembly is very complex and dynamic. In the recent years, increasing supply uncertainty and market demand variability are becoming real challenges to optimize and sustain the supply chain performance. Inventory planning is one of the key supply chain processes considerably affected by these new challenges. The objective of this project is to leverage advanced analytics to optimize inventory through a holistic inventory strategy. For instance, this aims to develop a Multi-Echelon Inventory Optimization (MEIO) model to right-size inventory across the supply chain network (raw materials, finished parts, spare parts, etc.). Also, advanced statistics and predictive analytics techniques will be used to identify the original sources of uncertainity, to track trends of critical inventory drivers and to put into place an inventory alert system. This will help the company to be more competitive in the aircraft engines market by reducing supply chain costs and improving the service level.

Background and required skills

Research Objectives/Sub-Objectives:

  • Optimize safety stock allocation across all stages of the supply chain using a MEIO model
  • Use the MEIO tool to perform ‘what..if’ simulation analysis
  • Improve the process of inventory target setting by engine program
  • Manage effectively supply chain uncertainty
  • Reduce the impact of bullwhip effect on the overall supply chain perfromance 


  • Develop an analytics-based approach to capture the original sources of variability and to track variability propagation across the supply chain
  • Develop a MEIO to optimize safety stock allocation across the supply chain
  • Each part (engine component) at each plant is considered as a seperate echelon 

Expertise and Skills Needed:

  • Operations management, Supply Chain design, Inventory optimization
  • Operations Research (Dynamic programming, Stochastic optimization, Metaheuristics, Simulation)
  • Advanced statistics (Statistical modeling, Statistical Process Control, etc.)
  • Excellent communication skills

For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects.
  2. Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed!
  3. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Jesse Vincent-Herscovici at, jvh(a)