Seminar
Robust Spare Parts Inventory Management
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Series
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SpeakerAhmadreza Marandi (Eindhoven University of Technology)
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FieldOperations Analytics
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LocationVrije Universiteit Amsterdam, main building
Amsterdam -
Date and time
February 06, 2025
16:00 - 17:00
Abstract
Product Introduction (NPI) phase when historical data is limited. Most conventional spare parts inventory control models assume demand follows a Poisson process with a known rate. However, the rate may not be known when limited data is available. We propose an adaptive robust optimization (ARO) approach to multi-item spare parts inventory control. We show how the ARO problem can be reformulated as a tractable deterministic integer programming problem. We develop an efficient algorithm to obtain near-optimal solutions for thousands of items. We demonstrate the practical value of our model through a case study at ASML, a leading semiconductor equipment supplier. The case study reveals that our model consistently achieves higher service levels at lower costs than the conventional stochastic optimization approach employed at ASML.