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

Constant Flow Management - Investigating manufacturing flow variability

This project investigates the manufacturing flow variability in order to stabilize the factory process flow. Nowadays, in manufacturing production lines and particularly in modern front end semiconductor lines, processes and equipments are very complex. Any disturbance of the process creates variability in the line, and causes substantial losses in productivity for manufacturing corporations. These disturbances are unpredictable, difficult to control and result in long recovery times. Variability occurring in a production system disturbs the whole processing flow and results in long product cycle times. Hence, a range of sources of variability was determined from the literature and analyzed. This lead with the cooperation of factory managers to the development of four main objectives: (1) Determine a proper metric to measure the variability in the production system. (2) Determine the effect of batching and tool availability on the process flow. (3) Understand the interaction between operations. (4) Develop a release strategy in order to stabilize the production flow. First, from the observation of real production data, a difference metric was developed and operations creating or removing variability were identified. The propagation of variability can be followed using a correlation coefficient. Nevertheless, the data were not detailed enough to explain the origin of the variability. Consequently, several simulation models were created to investigate variability. The simulations‘ results show that the release strategy should be adjusted as a function of batch, tool availability and constraint parameters, in order to stabilize the flow of items in the line and control cycle time and cycle time variability. The notion of critical availability is introduced and defined. Improvement of the line performance is obtained through a tighter control of the availability of high capacity operations. This lead to the development of a new hybrid push pull release strategy, named CONFLOW, to regulate the flow of items reaching the constraint operation. CONFLOW was tested under many simulating conditions (batching, parallel processing, and different line length). Compared to a push system, CONFLOW release strategy results, into significant improvement (up to 80%) in cycle time, cycle time standard deviation and WIP level at the cost of 13% reduction in throughput. CONFLOW performances were compared to common TOC strategies (SA and DBR). The results are encouraging. In the specific conditions considered, CONFLOW performances are similar to SA and slightly better than DBR

Analysis and Evaluation of the Impacts of Predictive Analytics on Production System Performances in the Semiconductor Industry

Problem Statement: Predictive Analytics (PA) may effectively support semiconductor industry (SI) companies in order to manage the special challenges in SI value chains. To discover the implications of PA, the realistic benefits as well as its limitations of its application to semiconductor manufacturing, it is necessary to assess in which ways the application of PA affects the production system (PS) performances. However, based on the literature survey, the influences of PA on the various performance characteristics of an SI PS are not as clear as expected for the efficiently operative application. Besides, the existing performance models are not effective to predict the impacts of PA on the SI PS performances. Therefore, the overall aim of this thesis is to analyse and evaluate the impacts of PA on the SI PS performances and to identify under which conditions a PA application would generate the most significant performance improvements. The focus of this thesis is predictive maintenance (PdM). Research Methodology: Based on a post-positivist philosophy, the thesis applies a deductive research approach using mixed-methods for data collection. The research design has the following stages: (1) theory, (2) hypothesis, (3) state of research, (4) case study and (5) verification. Main Achievements: (1) The systematic literature review is carried out to identify the gaps of the existing research and based on these findings, a conceptual framework is proposed and developed. (2) The existing performance models are analysed and evaluated against their applicability to this study. (3) A causal loop model for SI PS is generated based on the assessment of experts with industrial engineering and equipment maintenance expertise. (4) An expert system is developed and evaluated in order to investigate transitive and contradictory effects of PdM on SI PS performances. (5) A simulation model is developed and validated for investigating the strengths and limitations of PdM regarding SI PS performances under different circumstances. Results: The results of the logical inference study show that PdM has 34 positive effects as well as 4 contradictory effects on SI PS performance characteristics. Based on the various simulation experiments, it has been found that (1) ’Mean Time to Repair’ decreases only if PdM supports proportionate reduction of failures and repair times. (2) Logistics performance improves only if the underlying workcenter is limited in capacity or the four partners are nonsynchronous. (3) PdM supports optimal cost decreases for workcenters where the degree of exhausting wear limits can be most effectively improved and (4) the degree of yield improvement gained by PdM is dependent on the operation scrap rate. However, (5) if a workcenter has overcapacity, PdM will potentially worsen PS performances, even if the particular workcenter performance can be improved. These new insights advance existing knowledge in production managements when adopting predictive technologies at SI PS in order to improve PS performances. The findings above enable SI practitioners to justify a PdM investment and to select suitable workcenters in order to improve SI PS performances by applying the proposed PdM. Contributions: The main contributions of this PhD project can be divided into practical application and theoretical work. The contributions from the theoretical perspective are: 1) The critical review and evaluation of the state of the research for PA in the context of semiconductor manufacturing and the models for predicting and evaluating SI PS performances. 2) A new framework for investigating the implications of PA on the challenges such as gaining high utilizations and controlling the variability in production processes in SI value chains. 3) The new knowledge about transitive and contradictory effects of PdM on SI PS performances, which indicates that PdM can be used to improve PS performances beyond a single machine. 4) The new knowledge about strengths and limitations of PdM in order to improve SI PS performances under particular circumstances. The contributions from the practical application perspective are: 1) A practical method for identifying workcenters where PdM delivers the most significant benefits for SI PS performances. 2) An expert system that provides a comprehensive knowledge base about causes and effects within SI PS in order to justify a PdM investment. 3) A concise review of important PA applications, their capabilities for the wafer fabrication and the most suited PA methods. These findings can be adopted by SI practitioners

A framework for creating production and inventory control strategies

In multiproduct manufacturing systems, it is difficult to assure that an optimised setting of a pull production control strategy will be able to maintain its service level and inventory control performances. This is because the competition for resources among products is liable to make them affect the service levels of one another. By comparing different pull strategies, this research has observed that tightly coupled strategies are able to maintain lower amount of inventory than decoupled strategies, but they do so at the detriment of service level robustness. As a result, tightly coupled strategies are better suited to manufacturing environments with low variability, while decoupled strategies are more robust in high variability environments. Here, robustness is a measure of how well a strategy is able to minimise the drop below its original optimised service level when the initial system conditions change. Furthermore, the Kanban allocation policy applied under a strategy plays a major role in its ability to manage the performances of multiple products. Experimental results show that the Shared Kanban Allocation Policy (SKAP) keeps a lower amount of inventory than the Dedicated Kanban Allocation Policy (DKAP), but it is more susceptible to the variability in the demand or processing times of one product impacting the service level of another. Therefore, a Hybrid Kanban allocation policy (HKAP) that combines both the DKAP and the SKAP has been implemented. This approach considers products’ demand and processing time attributes before categorising them into the same Kanban sharing group. The results of the implementation of the HKAP show that it can keep as low inventory as the SKAP and avoid products impacting the service levels of one another. Additionally, it offers a better approach to managing large multiproduct systems, as the performances of product groups can be differentially managed through the combination of Kanban sharing and dedication policies. Lastly, the observations on the performances of strategies and policies under different system conditions can be used as a framework through which line designers select strategies and policies to suit their manufacturing system

Voraussicht zur Verbesserung der Zielerreichung bei prioritätsregelgesteuerter Produktion

In der vorliegenden Arbeit wird ein umfassender Überblick zum Thema Voraussicht im Rahmen der Ablaufplanung gewährt. Zunächst werden die unterschiedlichen Verfahren aus allen Bereichen der Ablaufplanung dargestellt und klassifiziert. Darauf folgend werden neu entwickelte Verfahren vorgestellt, die als Repräsentanten ihrer Klassen zur Erweiterung von Prioritätsregeln eingesetzt werden können. Dabei handelt es sich um ein modulares Konzept, das es gestattet, die Einzelmechanismen in beliebiger Kombination einzusetzen. Zur Überprüfung der Wirksamkeit findet eine Untersuchung aller entwickelten Verfahren im Rahmen eines stochastisch dynamischen Job Shops mithilfe umfangreicher Experimente statt. Bestandteil dieser experimentellen Studie ist auch die Untersuchung der Wechselwirkungen der verschiedenen Voraussichtsmechanismen. Die Experimentergebnisse zeigen auf, dass Voraussicht in vielen Situationen zur Verbesserung der Zielerreichung eingesetzt werden kann und liefern zudem zahlreiche Erkenntnisse über den Einfluss der Systemparameter auf die Vorteilhaftigkeit der einzelnen Voraussichtsklassen