Agenda

Invited Talks

INVITED TALK on Tuesday, April 16, 2024

MaiMa autofrei - A digital quality gate for tool requalification after maintenance employing MaiMa and Space

Yvonne Bergmann, Robert Bosch GmbH


After the maintenance of a production tool, the tool has to be requalified before being put back into production. Testwafers are used for processing and measuring the critical tool parameters. To date the testwafer results are evaluated manually. The software solution “MaiMa autofrei” automates the evaluation the testwafer results by using the maintenance manager MaiMa and the SPC Software Space. This increases the uptime of the production tool and it decreases the effort of the maintenance staff. Moreover, a digital First Time Right gate can be established.  


The MaiMa Ecap for visualizing the maintenance is equipped with a wait node and a scheduler for a periodic data query from the data base. The teswafers ordered at the beginning of the MaiMa ecap are tracked. The SPC software space provides the valuation of the testwafer measurement. Hence, there is a feedback loop assessing if the the tool state after the preventive maintenance is OK or NOT OK.


The average tool down time may be decreased at each maintenance. As the testwafer results are valuated digitally, a result report can be obtained. This enables a digital quality gate to assess the quality of the manitenance process. Less human effort is required, because the MaiMa ecap is able to wait for the test results. Valuation of the tests is achieved by the help of Space.

Curricula Vitae | Yvonne Bergmann

Yvonne Bergmann is working as a coordinator for public funded projects at Robert Bosch GmbH in Reutlingen. She received her physics diploma from Berlin Free University in 2010 and joined Bosch in 2010. She did her PhD of Engineering in the department of material science with Christian Albrecht University of Kiel in collaboration with Bosch about Through Silicon Via concepts for MEMS. From 2013 to 2023 she worked in the Wafer Fab as an Equipment Engineer in the Lithography department. To improve machine uptime in the automated Wafer Fab, she started focusing on software solutions for the automated tool requalification “MaiMa autofrei”.

INVITED TALK on Wednesday, April 17, 2024

Novel approach to master the challenges of run-to-run control in high-mix low-volume production – PART 3

Ulf Seidel | Infineon Technologies Dresden

 
To improve the stability of semiconductor manufacturing processes run-to-run control is used in addition to the internal control-loops of the manufacturing tool. A typical run-to-run strategy comprises two steps. First, a suitable state of the controlled process is estimated using process data of previous materials. In a second step the estimated state is used to calculate the recipe tuning parameters for the next materials. High-mix low-volume production poses a real challenge for the state estimation as data is both scarce and erratic. The estimates can be corrupted in many ways, e.g. by missing, delayed or faulty measurements. In order to avoid yield loss and/or scrap it is vital to validate the states permanently. The validation routines are a crucial part of the control algorithm.

At the 2022 apc|m conference in Toulon we proposed to exploit the estimation errors calculated by a Kalman filter for state validation. The numerical shortcomings of the Kalman filter and respective solutions were discussed in the second part of the talk presented at the apc|m conference in Bruges last year. This year we will focus on tuning the parameters of the Kalman filters.

The talk starts with a brief recap of the previous talks. Strategies to tune the parameters of the Kalman filter will be discussed next. Typically physical reasoning is used to specify the tuning parameters. Unfortunately, this approach is not applicable for run-to-run control due to the complex production environment. Instead, the tuning parameters have to be estimated from production mass data. The straight forward estimation strategy  is to minimize the model prediction errors for the mass data.  We will demonstrate that Kalman filters cannot be tuned with this strategy. The solution to this problem will be developed step by step in the talk.

Curricula Vitae | Ulf Seidel

Ulf Seidel is Principal Engineer for Advanced Process Control working both in operations and research at Infineon Technologies Dresden, Germany. He received the M.Sc. degree in Control Engineering from the University of Sheffield, U.K., in 1994, and the Dipl.-Ing. degree in Electrical Engineering as well as the Dr.-Ing. degree (Ph.D.) in Control Engineering from TU Dresden, Germany, in 1995 and 2000, respectively. He was with Klippel GmbH, Dresden from 2000 to 2008 where he developed instruments for diagnosis and quality control of audio systems including novel online identification of nonlinear loudspeaker models. He joined the run-to-run control group at Qimonda Dresden from 2008 to 2009. From 2009 to 2010 he was with InfraTec GmbH, Dresden developing measurement systems for pyroelectric infrared detectors. Since 2010 he has been with the advanced process control group at Infineon Technologies Dresden.