MAccuracy of service parts planning – ASML



Company Name / Department ASML
Contact Person

Roy van Hugten

Location Veldhoven, Netherlands
Study programme(s)

Supply Chain Management

Community ESCF
Start Date Around February 2020
Housing arranged by company No


 500 Eur per month

Company Description

ASML develops, produces, markets, sells, and services advanced semiconductor equipment systems consisting of lithography related systems for memory and logic chipmakers. It also offers metrology and inspection systems, including optical metrology solutions to measure the quality of patterns on the wafers; and e-beam solutions to locate and analyze individual chip defects. In addition, the company provides computational lithography and software solutions to create applications that enhance the setup of the lithography system; and mature products and services that refurbish used lithography equipment and offers associated services.


Project Description

The Service Inventory Management department at ASML is responsible for the planning of spare parts and service tools in order to meet service level agreements with ASML’s customers.

In order to improve planning of spare parts further, we want to develop a method to measure the accuracy of our planning in terms costs and performance. This should be the basis to identify areas to improve our planning.

Overall results should be a better allocation of spare parts around the world resulting in higher availability or lower costs.


Goals of the Project

A method to measure the accuracy of the current planning strategy and a method to use this method to improve the accuracy.



  • Literature study to determine to determine which methods can be used to measure planning accuracy
  • A proposal for a measuring method
  • Align proposed solution with the planning team
  • Model and analysis to evaluate the effectiveness of the proposed method(s)
  • Proposal how to use the accuracy to determine improvements
  • Guidelines for implementation of the method


    Essential Student Knowledge

    Strong capital goods background with passion for data analytics and programming


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