Patrick Preuss

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Co-Authors

Boon Ping Gan

Simulation Technologies (United States)

Peter Lendermann

Simulation Technologies (United States)

Wolfgang Scholl

Infineon Technologies (Germany)

Daniel Noack

Technische Universität Berlin

Marcin Mosinski

Robert Bosch (Germany)

Wolfgang Schöll

Medical University of Graz

André Naumann

Fraunhofer Institute for Factory Operation and Automation

Oliver Rose

Universität der Bundeswehr München

Andre Naumann

Matthias Forster

Infineon Technologies (Germany)

Cooperative Institutions

Infineon Technologies (Germany)

Simulation Technologies (United States)

Hochschule für Technik und Wirtschaft Dresden – University of Applied Sciences

TU Dresden

Singapore Institute of Manufacturing Technology

Singapore Institute of Technology

Fraunhofer Institute for Factory Operation and Automation

Nanyang Technological University

Robert Bosch (Germany)

Universität der Bundeswehr München

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Towards realization of a high-fidelity simulation model for short-term horizon forecasting in wafer fabrication facilities

Wolfgang Scholl Boon Ping Gan Ming Li Peh Peter Lendermann Daniel Noack

Discrete Event Simulation (DES) has widely been used for mid and long term forecasting in wafer fabrication plants. But the use of DES for short term forecasting has been limited due to the perceived modelling and computation complexity as well as the non-steady state nature of today's wafer fab operations. In this paper, we discuss some important modelling issues associated with building an online simulation model. Key elements considered are actual process routes, process and throughput modelling as a function of equipment behavior, lot size, and available processing modules, process dedication at equipment level, equipment downs at mainframe level, estimated lot release strategy, send ahead wafers, dispatch rules, and setup. Typical application areas are proactive dedication management, preventive maintenance scheduling and WIP based sampling optimization.

Wafer fabrication

Discrete-Event Simulation

Realization (probability)

Wafer-level packaging

10.5555/2433508.2433825

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Citations (17)

Enhancement of simulation-based semiconductor manufacturing forecast quality through hybrid tool down time modeling

Winter Simulation Conference (2014)

Patrick Preuss André Naumann Wolfgang Scholl Boon Ping Gan Peter Lendermann

Material flow forecast based on Short-Term Simulation has been established as a decision support solution for fine-tuning of Preventive Maintenance (PM) timing at Infineon Dresden. To ensure stable forecast quality for effective PM decision making, the typical tool uptime behavior needs to be portrayed accurately. In this paper, we present a hybrid tool down modeling approach that selectively combines deterministic and random down time modeling based on historical tool uptime behavior. The method allowed to approximate the daily uptime of reality in simulation. A generic framework to model historical down behavior of any distribution type, described by the two parameters Mean Time to Failure (MTTF) and Mean Time to Repair (MTTR) is also discussed.

Maintenance engineering

10.5555/2693848.2694156

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Citations (0)

BRIDGING THE GAP BETWEEN FAB SIMULATION AND SUPPLY CHAIN FORECAST

2018 Winter Simulation Conference (WSC) (2018)

Wolfgang Schöll Matthias Forster Patrick Preuss André Naumann Hui Ping Ooi

The Infineon Dresden 300mm fab is the first wafer fab in the world to run high volume production of power technology products. This requires the coordination of multiple production facilities in the supply chain. Output from one facility is fed as an input to the subsequent facilities in a push or pull operation mode, depending on technology lines. In a push operation mode, lots transition from one facility to another in a continuous manner, while in the pull operation mode, lots are stored and continuation of the lots is triggered by customer order to the supply chain. The latter case triggers the need of synchronizing material flows from one facility to another, and thus requiring an accurate material forecast for better planning and execution. In this paper, we discuss the modelling issues and solutions associated with this challenge, and the use cases of the simulation forecast.

Synchronizing

Wafer fabrication

Mode (computer interface)

10.1109/wsc.2018.8632277

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Citations (2)

Towards realization of a high-fidelity simulation model for short-term horizon forecasting in wafer fabrication facilities

Proceedings of Winter Simulation Conference (2010)

Wolfgang Schöll Boon Ping Gan Ming Li Peh Peter Lendermann Daniel Noack

Wafer fabrication

Discrete-Event Simulation

Realization (probability)

Wafer-level packaging

10.1109/wsc.2010.5678952

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Citations (16)

OPERATOR RESOURCE MODELLING IN A MULTIPLE WAFER SIZES FABRICATION ENVIRONMENT USING DISCRETE EVENT SIMULATION

2018 Winter Simulation Conference (WSC) (2018)

Georg Seidel Patrick Preuss André Naumann Soo Leen Low Chew Wye Chan

Infineon Villach wafer fab facility has a unique characteristic of producing products of different wafer sizes with shared resources, both operators and tools. Daily adaptation of resource allocation to manage changing workloads is done dynamically and imposes challenges in providing high accuracy simulation forecast. In this paper, we discuss the modelling approach that we have taken to represent this dynamic feature, where resources are adjusted in simulation based on WIP situation. The concept is similar to acquiring KANBAN prior to running a production lot. KANBAN quantity is kept at a minimum number in low WIP situation, while the quantity is kept at maximum number at high WIP situation. These values were adjusted by studying the historical moves observed for a period of 3 months. Using this approach, we managed to improve the forecast quality by 7 percentage points in moves and 64 percentage points in WIP.

Kanban

Wafer fabrication

Discrete-Event Simulation

Operator (biology)

10.1109/wsc.2018.8632398

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Citations (2)

Automatic model verification for semiconductor manufacturing simulation

Boon Ping Gan Peter Lendermann Wolfgang Scholl Marcin Mosinski Patrick Preuss

Short Term Simulation (STS) that provides daily forecasts of work center performance has been deployed in Infineon Technologies for operational decision makings. To ensure good forecast accuracy, the STS requires high modeling fidelity, requiring good basic data quality for model building. Forecast accuracy is maintained through an Automatic Model Verification (AMV) engine. The AMV monitors and verifies discrepancies between simulation and reality for modeling elements such as process dedication, uptime, process time/throughput, sampling rate, and batch/stream size. It reports the verification results with a multi-layered view, at different levels of abstraction, and the gaps between simulation and reality are highlighted. The user can quickly identify gaps and make correction to the errors. In this paper, we give an insight to the complete workflow on how AMV helps to detect data issues, the options to resolve such issues and the positive effect to the simulation forecast quality.

Abstraction

Semiconductor device fabrication

10.5555/2675983.2675876

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Citations (1)

Implementation of a simulation-based short-term lot arrival forecast in a mature 200mm semiconductor fab

Winter Simulation Conference (2011)

Wolfgang Scholl Boon Ping Gan Peter Lendermann Daniel Noack Oliver Rose

The ability to perform lot arrival forecast at work center level is a key requirement for pro-active FAB operation management. Visibility to this information enables preemptive resource allocation and bottleneck management. Today, the work center lot arrival forecast is achieved through the use of short term simulation technique in Infineon Dresden. High fidelity simulation model that includes detailed modeling feature such as attribute-based sampling procedure, dedication and temporary tool blocking is built automatically through the transformation of data queries from data sources. In this paper, we present the results of our model validation work, comparing the FAB and forecasted lot arrival of the defect density measurement work center. Due to the high capacity demand of automotive product that requires more than 20 inspection steps; engineering lots and preventive maintenance of DDM must be scheduled at the right time. This can only be achieved with high quality lot arrival forecast.

Visibility

10.5555/2431518.2431747

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Citations (12)

Enhancement of simulation-based semiconductor manufacturing forecast quality through hybrid tool down time modeling

Proceedings of Winter Simulation Conference (2014)

Patrick Preuss André Naumann Wolfgang Schöll Boon Ping Gan Peter Lendermann

Maintenance engineering

10.1109/wsc.2014.7020088

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Citations (1)

A multi-stage discrete event simulation approach for scheduling of maintenance activities in a semiconductor manufacturing line

Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC) (2012)

Wolfgang Scholl Marcin Mosinski Boon Ping Gan Peter Lendermann Patrick Preuss

Discrete event simulation (DES) has been established as a frequently used decision-support method in semiconductor manufacturing. One of the key application areas is the planning and scheduling of extended (several days) maintenance activities. The first stage of maintenance activity planning is conducted with a transient long-term simulation model with the focus on evaluating the effect of maintenance activity on the expected fab performance. Decisions such as wafer start reduction or adjustment of delivery commitments among affected work centers are made. The second stage of the planning is initiated several days before the start of the maintenance activities, where resource planning and scheduling of the activity is done through assessment of the expected WIP situation forecasted by a high fidelity online simulation model. In this paper, we will explain this simulation-based multi-stage approach for maintenance activity scheduling. The associated benefits and challenges will be presented with an example use case.

Discrete-Event Simulation

Semiconductor device fabrication

Maintenance engineering

10.1109/wsc.2012.6465320

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Citations (13)

Harmonizing operations management of key stakeholders in wafer fab using discrete event simulation

2018 Winter Simulation Conference (WSC) (2017)

Georg Seidel Ching Foong Lee Ai Mei Kam Boon Ping Gan Chew Wye Chan

Operations meeting in a wafer fab involves daily alignment of action items among key stakeholders: operations, maintenance, engineering and planning department. They have conflicting job functions. The maintenance department is required to conduct preventive maintenance (PM) to improve tools' reliability The engineering department is required to qualify new products and processes. Both cases interfere with the flow of production lots. The planning department must ensure production ramp up. This can have a short term impact on overall fab delivery and capacity. The primary challenge is to reach aligned decisions e.g. the best timing for PM or optimizing dispatch prioritization of production and development lots to ensure on-time delivery while maximizing capacity and tool utilization. In this paper we discuss the associated modelling issues of a 7-day simulation-based forecast, providing forecast of incoming WIP, moves and utilization at work center level. The simulation forecast consistently achieved an accuracy above 90%.

Discrete-Event Simulation

Prioritization

Work order

Wafer fabrication

10.1109/wsc.2017.8248079

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Citations (7)