Proceedings of the third International Workshop of the IFIP WG5.7

Contents of the papers presented at the international workshop deal with the wide variety of new and computer-based techniques for production planning and control that has become available to the scientific and industrial world in the past few years: formal modeling techniques, artificial neural networks, autonomous agent theory, genetic algorithms, chaos theory, fuzzy logic, simulated annealing, tabu search, simulation and so on. The approach, while being scientifically rigorous, is focused on the applicability to industrial environment

Increasing experiment velocity in a production environment

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, June 1999."May 1999."Includes bibliographical references (p. 49).by Shafali Rastogi.S.M

Reducing variability in a semiconductor manufacturing environment

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.Includes bibliographical references.The main drivers in today's flash memory business are low cost and flexibility. Low cost requires high tool utilizations, whereas flexibility and ability to respond quickly to changing customer demands require short throughput times. There is, however, an inherent operational conflict with achieving both high utilization and short cycle time simultaneously. Intel's flash memory factory is striving for shorter manufacturing throughput times without reducing tool utilizations. One of the major components in throughput time today is queuing time caused partly by variability in the manufacturing environment. Being able to reduce this variability component could result in improvements in throughput time. In this work, Factory Physics methods are used to analyze variability in the manufacturing flow. First, potential high variability areas in the flow are identified. Second, manufacturing data is analyzed to find the main sources of variability. Third, ways to reduce variability are investigated. Finally, means to align manufacturing metrics with variability reduction efforts and the effect of metrics on organizational culture and change implementation are discussed. During the study it was found out that the lithography area reduces the overall manufacturing flow variability. It was also found out, that the area is highly utilized and is thus introducing non-value adding queuing time for the product throughput time.(cont.) Arriving material flow was identified to be the main source of variability. Recommendations for improving the area performance include optimizing tool dedications, standardizing operator decision making, and changing preventive maintenance operations. The key takeaway from this study is the importance of metrics alignment. Metrics are the most powerful incentives for operator behavior. Unless the daily floor level performance measurements are aligned to support the organizational goals, implementing new operations management methods to reduce variability will be challenging.by Minja Johanna Penttilä.S.M.M.B.A

Intelligent shop scheduling for semiconductor manufacturing

Semiconductor market sales have expanded massively to more than 200 billion dollars annually accompanied by increased pressure on the manufacturers to provide higher quality products at lower cost to remain competitive. Scheduling of semiconductor manufacturing is one of the keys to increasing productivity, however the complexity of manufacturing high capacity semiconductor devices and the cost considerations mean that it is impossible to experiment within the facility. There is an immense need for effective decision support models, characterizing and analyzing the manufacturing process, allowing the effect of changes in the production environment to be predicted in order to increase utilization and enhance system performance. Although many simulation models have been developed within semiconductor manufacturing very little research on the simulation of the photolithography process has been reported even though semiconductor manufacturers have recognized that the scheduling of photolithography is one of the most important and challenging tasks due to complex nature of the process. Traditional scheduling techniques and existing approaches show some benefits for solving small and medium sized, straightforward scheduling problems. However, they have had limited success in solving complex scheduling problems with stochastic elements in an economic timeframe. This thesis presents a new methodology combining advanced solution approaches such as simulation, artificial intelligence, system modeling and Taguchi methods, to schedule a photolithography toolset. A new structured approach was developed to effectively support building the simulation models. A single tool and complete toolset model were developed using this approach and shown to have less than 4% deviation from actual production values. The use of an intelligent scheduling agent for the toolset model shows an average of 15% improvement in simulated throughput time and is currently in use for scheduling the photolithography toolset in a manufacturing plant

Analyzing sampling methodologies in semiconductor manufacturing

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2004.Includes bibliographical references (p. 81-83).This thesis describes work completed during an internship assignment at Intel Corporation's process development and wafer fabrication manufacturing facility in Santa Clara, California. At the highest level, this work relates to the importance of adequately creating and maintaining data within IT solutions in order to receive the full business benefit expected through the use of these systems. More specifically, the project uses, as a case example, the sampling methodology used in the fab for metrology data collection to show that significant issues exist relating to the software Various recommendations were undertaken to improve the application's effectiveness. As part of this effort, plans for an online reporting tool were developed allowing much greater visibility into the system's ongoing performance. Initial data updates and other improvements resulted in a reduction in both product cycle times and required labor hours for metrology operations. application database and business processes concerning data accuracy and completeness. The organizational challenges contributing to this problem will also be discussed. Without a rigorous focus on the accuracy and completeness of data within manufacturing execution systems, the results of continuous improvement activities will be less than expected. Furthermore, sharing information relating to these projects across geographical boundaries and business units is vital to the success of manufacturing organizations.by Richard M. Anthony.S.M.M.B.A

Online Simulation in Semiconductor Manufacturing

In semiconductor manufacturing discrete event simulation systems are quite established to support multiple planning decisions. During the recent years, the productivity is increasing by using simulation methods. The motivation for this thesis is to use online simulation not only for planning decisions, but also for a wide range of operational decisions. Therefore an integrated online simulation system for short term forecasting has been developed. The production environment is a mature high mix logic wafer fab. It has been selected because of its vast potential for performance improvement. In this thesis several aspects of online simulation will be addressed: The first aspect is the implementation of an online simulation system in semiconductor manufacturing. The general problem is to achieve a high speed, a high level of detail, and a high forecast accuracy. To resolve these problems, an online simulation system has been created. The simulation model has a high level of detail. It is created automatically from underling fab data. To create such a simulation model from fab data, additional problems related to the underlying data arise. The major parts are the data access, the data integration, and the data quality. These problems have been solved by using an integrated data model with several data extraction, data transformation, and data cleaning steps. The second aspect is related to the accuracy of online simulation. The overall problem is to increase the forecast horizon, increase the level of detail of the forecast and reduce the forecast error. To provide useful forecast results, the simulation model contains a high level of modeling details and a proper initialization. The influences on the forecast quality will be analyzed. The results show that the simulation forecast accuracy achieves good quality to predict future fab performance. The last aspect is to find ways to use simulation forecast results to improve the fab performance. Numerous applications have been identified. For each application a description is available. It contains the requirements of such a forecast, the decision variables, and background information. An application example shows, where a performance problem exists and how online simulation is able to resolve it. To further enhance the real time capability of online simulation, a major part is to investigate new ways to connect the simulation model with the wafer fab. For fab driven simulation, the simulation model and the real wafer fab run concurrently. The wafer fab provides several events to update the simulation during runtime. So the model is always synchronized with the real fab. It becomes possible to start a simulation run in real time. There is no further delay for data extraction, data transformation and model creation. A prototype for a single work center has been implemented to show the feasibility