Demand differentiation in field stock optimization – ASML

 Overview

Company Description

ASML is an innovation leader in the semiconductor industry. We provide chipmakers with everything they need – hardware, software, and services to mass-produce patterns on silicon through lithography.

Project Description

Project description:

The Field Forecasting & Planning department at ASML is responsible for the forecasting and planning of spare parts and service tools required to service our machines at the customer. We aim to optimize our planning strategy in terms of cost & capital whilst adhering to service level agreements (SLAs). Our department uses a model, called SPartAn, to optimize our field stocking strategy. This model is a multi-item multi-location inventory model that we developed in close collaboration with the TU/e. As the model is a simplification of reality, there are some gaps between operational execution and tactical planning. One of which is the assumption that all demand has to be fulfilled immediately, whilst in reality a delay is allowed for some service orders.

Trigger for project

In our operations we distinguish between different types of service orders which are emergency orders, priority orders and routine orders. As the name suggests, emergency orders are required ASAP. However, for priority service orders slack can range between 4 to 14 days and for routine service orders even between 15 to 42 days. Currently we do not make a distinction in our service forecast and in our tactical plan between these different types of service orders. This potentially results in overperformance or too high inventory levels. ASML wants to make the next step in our field stocking strategy by relaxing the immediate order fulfillment assumption. Thereby, we aim to bridge the gap between our operational (over)performance and tactical plan.

Goals of the project:

Integrate demand differentiation in the field stocking strategy to bridge the gap between operational execution and the tactical plan. The implemented solution should fit in the current framework for forecasting and planning, while making use of the available data.

Deliverables:

• Literature study to determine which methods can be used
• Conduct interviews within ASML to determine which methods are already considered and which business data is available to support these methods
• A proposal for a planning method (could build on existing method)
• Model and analysis to evaluate the effectiveness of the proposed method
• Identify and develop KPIs to measure the performance of the proposed method
• Managerial guidelines for implementation

 More information: escf@tue.nl