Machine assessment for performance update

Problem: A feasibility study to define the improved machine concept

A semiconductor OEM needed to make a significant step forward in machine performance without drastically changing their machine architecture. Philips Engineering Solutions was contacted to assist in setting up a feasibility study for the definition of the improved machine concept. To serve new market needs, the performance needs to be better than their current systems by a factor of at least 10. To save on development and implementation effort, they wanted to stay close to their current machine architecture.

Solution: Experimental performance assessment of current generation tools

To support the customer in defining the new machine architecture, Philips Engineering Solutions conducted an experimental performance assessment of their current generation tools. The purpose of this feasibility study was to identify the most critical machine aspects in a short amount of time. The focus was on getting a better understanding of the critical process parameters and finding out how different machine components were influencing this. Measurement data combined with predictive modeling were then used to define an optimal machine concept, fitting the specifications and constraints of the customer.

Through weekly teleconferencing, the overseas customer introduced us to their challenges for the near future, but also explained the status of their current generation. From there, machine components that could be re-used were selected and a measurement plan was presented to assess these parts. The measurements were guided by Philips Engineering Solutions and executed by the overseas customer. Through this, it was possible to find critical insights in a short period at a low cost.

Measurements were taken in the time domain (see Figure 1) and the frequency domain (see Figure 2) in order to identify critical machine parameters and to make a model that can be used to predict performance when the machine concept is changed (the model is schematically depicted in Figure 3).

Figure 1: Example of time domain analysis

Figure 2: Example of frequency domain analysis

Figure 3: Machine dynamic concept outline

Results: A significant step forward in machine performance

• Identification of critical performance features in the current generation of tools.
• Identification of components that were suitable for re-use.
• Usage of the measurement data as input for predictive models to evaluate concepts for the new generation tool.
• Insights into the mechatronic competences (gaps) of the customer. Based on this, a cooperation proposal was defined to create the highest and most sustainable benefit for the customer.
• An improved machine concept was selected, and a co-development project was defined to jointly design a critical component, resulting in the performance being achieved.