Development and Simulation Assessment of Semiconductor Production System Enhancements for Fast Cycle Times

Long cycle times in semiconductor manufacturing represent an increasing challenge for the industry and lead to a growing need of break-through approaches to reduce it. Small lot sizes and the conversion of batch processes to mini-batch or single-wafer processes are widely regarded as a promising means for a step-wise cycle time reduction. Our analysis with discrete-event simulation and queueing theory shows that small lot size and the replacement of batch tools with mini-batch or single wafer tools are beneficial but lot size reduction lacks persuasive effectiveness if reduced by more than half. Because the results are not completely convincing, we develop a new semiconductor tool type that further reduces cycle time by lot streaming leveraging the lot size reduction efforts. We show that this combined approach can lead to a cycle time reduction of more than 80%

Simulation in der Computer-Chip-Produktion – Möglichkeiten und Grenzen

Der Beitrag führt zuerst in die Halbleiterfertigung und die damit verbundene innerbetriebliche Logistik, dabei vor allem das Transport- und Handhabungssystem, ein. Bei der Planung und Steuerung solcher Anlagen stellen sich sehr anspruchsvolle Aufgaben, die nur mithilfe der Simulation zu lösen sind. Hierzu wird dargestellt, wie sich der Simulationseinsatz in der Halbleiterproduktion und -logistik gestaltet. Mit der Komplexität der Prozesse und Systeme wächst natürlich auch die Komplexität der eingesetzten Simulationsmodelle – auf die Frage nach einem angemessenen Abstraktionsgrad gibt es bislang jedoch keine befriedigende Antwort. Der Beitrag stellt dazu Lösungsansätze vor und zeigt, worauf künftige Forschungsarbeiten fokussieren sollten

Financial Resources and Technology to Transition to 450mm Semiconductor Wafer Foundries

Future 450mm semiconductor wafer foundries are expected to produce billions of low cost, leading-edge processors, memories, and wireless sensors for Internet of Everything applications in smart cities, smart grids, and smart infrastructures. The problem has been a lack of wise investment decision making using traditional semiconductor industry models. The purpose of this study was to design decision-making models to conserve financial resources from conception to commercialization using real options to optimize production capacity, to defer an investment, and to abandon the project. The study consisted of 4 research questions that compared net present value from real option closed-form equations and binomial lattice models using the Black-Scholes option pricing theory. Three had focused on sensitivity parameters. Moore\u27s second law was applied to find the total foundry cost. Data were collected using snowball sampling and face-to-face surveys. Original survey data from 46 Americans in the U.S.A. were compared to 46 Europeans in Germany. Data were analyzed with a paired-difference test and the Box-Behnken design was employed to create prediction models to support each hypothesis. Data from the real option models and survey findings indicate American 450mm foundries will likely capture greater value and will choose the differentiation strategy to produce premium chips, whereas higher capacity, cost leadership European foundries will produce commodity chips. Positive social change and global quality of life improvements are expected to occur by 2020 when semiconductors will be needed for the $14 trillion Internet of Everything market to create safe self-driving vehicles, autonomous robots, smart homes, novel medical electronics, wearable computers with streaming augmented reality information, and digital wallets for cashless societies