As the effective deployment of system production capacity and operational capability becomes critical for competitive semiconductor manufacturing, there is an increasing interest toward the development of a control framework which allows effective and efficient operation of the emerging 300 mm wafer fabs. In the paper, a colored Petri net-based approach is taken to develop such a distributed event-driven 300 mm fab controller. The key element of the proposed controller design is the distribution of control function, to the constituent components of the 300 mm fab, while maintaining the logical correctness and efficiency of the fab behavior. Furthermore, in order to achieve the viability of the resulting control scheme, the proposed approach seeks to incorporate detailed operational characteristics of the 300 mm fabs, including batching, setups, reworks, maintenance, machine failures, and complex resource allocation dynamics due to the routing flexibility and auxiliary resource sharing. The proposed approach is demonstrated through a small-scale example, modeling the operation of a 300 mm fab bay.

Semiconductor fabs are capital intensive. The rate of capital return heavily depends on their productivity. Accordingly, simulation has been adopted in many cases as a viable design and analysis tool to achieve better productivity. However, the gap between the simplistic simulation models and real complex systems has limited the confidence to apply simulation results directly to real systems. Ideally, the simulator should support the rapid modeling and fast execution of high-fidelity fab models in order to be able to provide more realistic simulation results. In this paper, we present our current research effort to develop a high-fidelity web-based simulator for the 300 mm wafer fabs. We take a model-view-control approach that allows us to develop modular and reusable fab simulation objects. The proposed approach is implemented as a distributed system that uses a message-based event synchronization mechanism to coordinate the simulation objects as well as to support distributed simulation execution. The presented simulator also provides a high quality VRML animation for visualization of real time paced simulation execution.

An ideal warehousing and distribution system has no inventory and operates with minimal handling. In an attempt to achieve this ideal, expert designers rely on their intuition, together with analytical models and procedures formalized over years of experience. Understanding the processes that experts employ to realize their designs can have great benefits, for instance, in developing computational tools to assist in design. We have conducted an ethnographic study of an expert design team during actual system design. In this paper, we describe our observations and a process model of design.

Design of warehousing and distribution systems is more an art than a science that reflects the cultures of particular design teams. Warehouses are often designed and operated by third party logistics companies with tight margins. Therefore, there is increased pressure to design warehouses that are flexible and adaptable, even while the available information is incomplete. Also, designers lack coherent and explicit models of information and function flow. The primary goal of the research discussed is to lay the foundation for developing such models. Working closely with expert designers, we have identified the key pieces of information and organized them in the form of an object model. Using this model, it should eventually be possible to provide relevant information to designers via context-sensitive (or 'ecological' or 'intelligent') displays. Upon further development, the model will be incorporated into an interactive system to assist in design. The authors describe the object model, and outline plans for implementing a design system.

Even though the methodologies for warehouse design are taught in traditional industrial engineering programs, students often find it difficult to develop the skills necessary to complete actual designs. The difficulty in translating the textbook knowledge of using the analytical and mathematical tools for design stem from their lack of experience in using such tools for designing warehouses of reasonable levels of fidelity compared to real systems. It is often very difficult to incorporate large datasets and the computational algorithms necessary during the different phases of warehouse design into the course material. As part of a larger research effort to develop a comprehensive collection of online teaching materials integrated into the undergraduate and graduate curricula, we have developed a warehouse design tutor in which additional functionality is constantly being added. Certain key details of the tutor are discussed in this paper.