Hans Ehm

Modelling and analysis of semiconductor manufacturing in a shrinking world: challenges and successes

A panel session on the role of modeling and analysis in semiconductor manufacturing in a shrinking world is presented. Therefore, two participants are from Asia, two from Europe, and two from US and there are two panel organizers/ moderators (Fowler and Monch). One panelist from each continent is from industry and one from academia. Only initial position statements are included in the proceedings. However, these initial statements form the basis for the panel discussion. The statements of the panelists from industry relate to modeling and analysis problems found in their own companies. The position statements of the panelists from academia describe the role that modeling and analysis is expected to play in their current and ongoing research in semiconductor manufacturing. Furthermore, their views on the challenges and successes of modeling and analysis in a globalized world are also included.

Modeling and analysis of semiconductor manufacturing in a shrinking world: challenges and successes

A panel session on the role of modeling and analysis in semiconductor manufacturing in a shrinking world is presented. Therefore, two participants are from Asia, two from Europe, and two from US and there are two panel organizers/ moderators (Fowler and Monch). One panelist from each continent is from industry and one from academia. Only initial position statements are included in the proceedings. However, these initial statements form the basis for the panel discussion. The statements of the panelists from industry relate to modeling and analysis problems found in their own companies. The position statements of the panelists from academia describe the role that modeling and analysis is expected to play in their current and ongoing research in semiconductor manufacturing. Furthermore, their views on the challenges and successes of modeling and analysis in a globalized world are also included.

Towards a supply chain simulation reference model for the semiconductor industry

In this paper, we describe major steps to build a supply chain simulation reference model for the semiconductor industry. We start by identifying requirements for such a reference model. Then we identify the main building blocks of the model. We present a technique to deal with load-dependent cycle times in single front-end and back-end facilities and in the overall network to reduce the modeling and computational burden. The quality of this reduction technique is assessed by comparing the full model and the model with a reduced level of detail. Finally, we discuss several potential application scenarios for a simulation reference model of a semiconductor supply network.

Modeling supply contracts in semiconductor supply chains

Semiconductor manufacturers face high demand uncertainty due to volatile and rapidly changing technology development as well as inaccurate customer forecasts. The paper first presents a description of contract clauses used in semiconductor supply chains, obtained through a literature review and a field study. The paper then presents a review of the literature on studies in supply chain contracts focusing on flexibility contracts and capacity option contracts. Finally, the paper presents models to study contract flexibility and capacity reservation options for a semiconductor manufacturer supplier and a buyer. The purpose of the models is to compare a representative standard flexibility contract currently used in semiconductor supply chains and a capacity options contract.

A discussion of object-oriented process modeling approaches for discrete manufacturing on the example of the semiconductor industry

We introduce a domain specific object-oriented data model for the high-tech discrete manufacturing on the example of the semiconductor company Infineon Technologies AG. This model is needed to describe the complex supply chain of a global company in the competitive semiconductor arena with frequent product changes. However, the data model alone is not solving all problems. For this we need e.g. event-driven internet-based workflows. To get those in a structured way, we show possibilities to come from an object-oriented data model to object-oriented business processes based on existing process models. Two ways - one with SysML and one with ARIS - are shown conceptually and are discussed. An outlook is given on how this approach will provide internet-based workflows on the one hand, and it also shows up process improvement potentials on the other hand.

Are simulation standards in our future

This panel seeks to initiate a discussion within the production system simulation community about a fundamental change in the way we think about, teach, and implement production system simulation. Today, production system simulation, while based on formal simulation languages, is largely an artistic process. We teach production system simulation as a studio course, i.e., students learn an esthetic for production system simulation, learn by example, and their progress is evaluated through studies in which they create simulations. We are not surprised, in fact fully expect that two simulationists will create possibly quite different simulations of the same production system, even using the same language.

A Short-Term Forecast Method for Demand Quantities in Semiconductor Manufacturing

In this paper, we study a forecast method for demand quantities in semiconductor manufacturing. We formulate and test a parameter-driven scheme to generate forecasts. We forecast demand quantities using the formula F = aX + bY where a and b are non-negative parameters to be estimated, X is a simple exponential smoothing forecast based on historical data, and Y are the firm orders that have been placed for the product for the current month. The parameters a, b, and the exponential smoothing parameters are chosen to optimize a statistical measure of forecast quality. We develop a spreadsheet model to address this problem. We suggest several forecast accuracy performance measures. We present the results of computational experiments on real-world data that clearly demonstrate that the suggested approach outperforms the current forecast approach.

Complexity Management in the Semiconductor Supply Chain and Manufacturing Using PROS Analysis

Supply chain complexity is a rising problem, especially in the semiconductor industry. Many innovative activities occur in the daily supply chain and manufacturing, and these changes inevitably bring in the complexities to the organization. But not all of them are valuable to the business goals. Decision makers want to keep value-added complexity and reduce non-value-added complexity. To manage the complexity, we propose a framework with four steps from changes identification towards the final decision making. The core solution of this framework is PROS (process, role, object, state) idea, which provides an understandable and structural way to describe the complexity. A simplified small real example from semiconductor supply chain is used to demonstrate this approach. The results indicate that the PROS idea is able to analyze complexity from different aspects and extract most key information; however, how to measure the structural complexity of a large complex system without complete information is still under investigation.

The global supply chain is our new fab: Integration and automation challenges

The globalization of the world economy as well as progresses in information technology made global supply chains a new paradigm for high-tech and semiconductor manufacturers like Infineon Technologies. Consequently supply chain operational excellence has become a key competitive advantage. Along with it comes the need for an agile, adaptable, and aligned global manufacturing network for mastering the volatile market demand — known as the triple-A challenge. A high degree of integration and automation is required across all stages of the value chain: equipment, factory, and supply chain levels. In this paper we describe several factors from shop-floor to corporate level addressing this challenge, and we outline a successful example of frontend-backend integration.

A Testbed for Simulating Semiconductor Supply Chains

In this paper, a supply chain simulation testbed for the semiconductor industry is proposed. We start by identifying requirements for such reference datasets, and then we identify the main building blocks. The nodes of the supply chain that represent semiconductor wafer fabrication facilities (wafer fabs) are built on a simulation model from the measurement and improvement of manufacturing capacity project. We present two techniques to reduce the modeling and computational burden that are able to deal with load-dependent cycle times in single front-end and back-end facilities and in the overall network. The first method models in detail only the bottlenecks in the nodes of the supply chain, while the second one uses empirical distributions for cycle time and throughput. The quality of these reduction techniques is assessed by comparing the detailed model and the models with a reduced level of detail. We present an application scenario for the testbed by simulating a semiconductor supply network. In addition, the usage of the testbed is discussed.