Cycle Time Analysis For Photolithography Tools In Semiconductor Manufacturing Industry With Simulation Model : A Case Study [TR940. S618 2008 f rb].

Perkembangan industri semikonduktor dalam bidang fabrikasi biasanya melibatkan kos pelaburan yang tinggi terutamanya dalam alatan photolithography. The industry of semiconductor wafer fabrication (“fab”) has invested a huge amount of capital on the manufacturing equipments particular in photolithograph

Analysis of production control methods for semiconductor research and development fabs using simulation

The importance of semiconductor device fabrication has been rising steadily over many years. Integrated circuit technology and innovation depends on successful research and development (R&D). R&D establishes the direction for prevailing technology in electronics and computers. To be a leader in the semiconductor industry, a company must bring technology to the market as soon as its application is deemed feasible. Using suitable production control methods for wafer fabrication in R&D fabs ensures reduction in cycle times and planned inventories, which in turn help to more quickly, transfer the new technology to the production fabs, where products are made on a commercial scale. This helps to minimize the time to market. The complex behavior of research fabs produces varying results when conventional production control methodologies are applied. Simulation modeling allows the study of the behavior of the research fab by providing statistical reports on performance measures. The goal of this research is to investigate production control methods in semiconductor R&D fabs. A representative R&D fab is modeled, where an appropriate production load is applied to the fab by using a representative product load. Simulation models are run with different levels of production volume, lot priorities, primary and secondary dispatching strategies and due date tightness as treatment combinations in a formally designed experiment. Fab performance is evaluated based on four performance measures, which include percent on time delivery, average cycle time, standard deviation of cycle time and average work-in-process. Statistical analyses are used to determine the best performing dispatching rules for given fab operating scenarios. Results indicate that the optimal combination of dispatching rules is dependent on specific fab characteristics. However, several dispatching rules are found to be robust across performance measures. A simulation study of the Semiconductor & Microsystems Fabrication Laboratory (SMFL) at the Rochester Institute of Technology (RIT) is used to verify the results

Cycle Time Analysis For Photolithography Tools In Semiconductor Manufacturing Industry With Simulation Model: A Case Study

Perkembangan industri semikonduktor dalam bidang fabrikasi biasanya melibatkan kos pelaburan yang tinggi terutamanya dalam alatan photolithography. Perkembangan pesat dalam bidang industri semikonduktor kini telah memerangsangkan teknik untuk mengoptimumkan penggunaan mesin-mesin dengan efektif setelah membelanjakan beribu juta dalam perlaburan. Tanpa penggunaan perisian komputer yang canggih dalam analisis, adalah sukar untuk menggunakan teknik purba dalam analisis pengiraan apabila menghadapi perkembangan produk yang semakin tinggi teknologinya. Dalam kajian ini, satu model simulasi telah dibina untuk menganalisis masa mendulu dalam alatan photolithography melalui teknik yang lebih sistematik dan efektif. Model simulasi ini telah dibina berasaskan perisian computer yang memerlukan informasi yang teliti seperti mas a memproses dan juga aliran proses dalam alatan photolithography. The industry of semiconductor wafer fabrication ("fab") has invested a huge amount of capital on the manufacturing equipments particular in photolithography area which has driven the needs to re-look at the most profitable way of utilizing and operating them efficiently. Traditional industrial engineering analysis techniques through mathematical models or static models for the studies of photolithography process are simply not adequate to analyze these complex environments. In this research, a more realistic representation of photolithography tools that can give a better prediction results and a more systematic methodology for minimizing photolithography cycle time is presented. The proposed method is to reduce waiting time and increase utilization of the photolithography process, which would result in an overall equipment cycle time reduction

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

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%

Entwicklung und Einführung von Produktionssteuerungsverbesserungen für die kundenorientierte Halbleiterfertigung

Production control in a semiconductor production facility is a very complex and timeconsuming task. Different demands regarding facility performance parameters are defined by customer and facility management. These requirements are usually opponents, and an efficient strategy is not simple to define. In semiconductor manufacturing, the available production control systems often use priorities to define the importance of each production lot. The production lots are ranked according to the defined priorities. This process is called dispatching. The priority allocation is carried out by special algorithms. In literature, a huge variety of different strategies and rules is available. For the semiconductor foundry business, there is a need for a very flexible and adaptable policy taking the facility state and the defined requirements into account. At our case the production processes are characterized by a low-volume high-mix product portfolio. This portfolio causes additional stability problems and performance lags. The unstable characteristic increases the influence of reasonable production control logic. This thesis offers a very flexible and adaptable production control policy. This policy is based on a detailed facility model with real-life production data. The data is extracted from a real high-mix low-volume semiconductor facility. The dispatching strategy combines several dispatching rules. Different requirements like line balance, throughput optimization and on-time delivery targets can be taken into account. An automated detailed facility model calculates a semi-optimal combination of the different dispatching rules under a defined objective function. The objective function includes different demands from the management and the customer. The optimization is realized by a genetic heuristic for a fast and efficient finding of a close-to-optimal solution. The strategy is evaluated with real-life production data. The analysis with the detailed facility model of this fab shows an average improvement of 5% to 8% for several facility performance parameters like cycle time per mask layer. Finally the approach is realized and applied at a typical high-mix low-volume semiconductor facility. The system realization bases on a JAVA implementation. This implementation includes common state-of-the-art technologies such as web services. The system replaces the older production control solution. Besides the dispatching algorithm, the production policy includes the possibility to skip several metrology operations under defined boundary conditions. In a real-life production process, not all metrology operations are necessary for each lot. The thesis evaluates the influence of the sampling mechanism to the production process. The solution is included into the system implementation as a framework to assign different sampling rules to different metrology operations. Evaluations show greater improvements at bottleneck situations. After the productive introduction and usage of both systems, the practical results are evaluated. The staff survey offers good acceptance and response to the system. Furthermore positive effects on the performance measures are visible. The implemented system became part of the daily tools of a real semiconductor facility.Produktionssteuerung im Bereich der kundenorientierten Halbleiterfertigung ist heutzutage eine sehr komplexe und zeitintensive Aufgabe. Verschiedene Anforderungen bezüglich der Fabrikperformance werden seitens der Kunden als auch des Fabrikmanagements definiert. Diese Anforderungen stehen oftmals in Konkurrenz. Dadurch ist eine effiziente Strategie zur Kompromissfindung nicht einfach zu definieren. Heutige Halbleiterfabriken mit ihren verfügbaren Produktionssteuerungssystemen nutzen oft prioritätsbasierte Lösungen zur Definition der Wichtigkeit eines jeden Produktionsloses. Anhand dieser Prioritäten werden die Produktionslose sortiert und bearbeitet. In der Literatur existiert eine große Bandbreite verschiedener Algorithmen. Im Bereich der kundenorientierten Halbleiterfertigung wird eine sehr flexible und anpassbare Strategie benötigt, die auch den aktuellen Fabrikzustand als auch die wechselnden Kundenanforderungen berücksichtigt. Dies gilt insbesondere für den hochvariablen geringvolumigen Produktionsfall. Diese Arbeit behandelt eine flexible Strategie für den hochvariablen Produktionsfall einer solchen Produktionsstätte. Der Algorithmus basiert auf einem detaillierten Fabriksimulationsmodell mit Rückgriff auf Realdaten. Neben synthetischen Testdaten wurde der Algorithmus auch anhand einer realen Fertigungsumgebung geprüft. Verschiedene Steuerungsregeln werden hierbei sinnvoll kombiniert und gewichtet. Wechselnde Anforderungen wie Linienbalance, Durchsatz oder Liefertermintreue können adressiert und optimiert werden. Mittels einer definierten Zielfunktion erlaubt die automatische Modellgenerierung eine Optimierung anhand des aktuellen Fabrikzustandes. Die Optimierung basiert auf einen genetischen Algorithmus für eine flexible und effiziente Lösungssuche. Die Strategie wurde mit Realdaten aus der Fertigung einer typischen hochvariablen geringvolumigen Halbleiterfertigung geprüft und analysiert. Die Analyse zeigt ein Verbesserungspotential von 5% bis 8% für die bekannten Performancekriterien wie Cycletime im Vergleich zu gewöhnlichen statischen Steuerungspolitiken. Eine prototypische Implementierung realisiert diesen Ansatz zur Nutzung in der realen Fabrikumgebung. Die Implementierung basiert auf der JAVA-Programmiersprache. Aktuelle Implementierungsmethoden erlauben den flexiblen Einsatz in der Produktionsumgebung. Neben der Fabriksteuerung wurde die Möglichkeit der Reduktion von Messoperationszeit (auch bekannt unter Sampling) unter gegebenen Randbedingungen einer hochvariablen geringvolumigen Fertigung untersucht und geprüft. Oftmals ist aufgrund stabiler Prozesse in der Fertigung die Messung aller Lose an einem bestimmten Produktionsschritt nicht notwendig. Diese Arbeit untersucht den Einfluss dieses gängigen Verfahrens aus der Massenfertigung für die spezielle geringvolumige Produktionsumgebung. Die Analysen zeigen insbesondere in Ausnahmesituationen wie Anlagenausfällen und Kapazitätsengpässe einen positiven Effekt, während der Einfluss unter normalen Produktionsbedingungen aufgrund der hohen Produktvariabilität als gering angesehen werden kann. Nach produktiver Einführung in einem typischen Vertreter dieser Halbleiterfabriken zeigten sich schnell positive Effekte auf die Fabrikperformance als auch eine breite Nutzerakzeptanz. Das implementierte System wurde Bestandteil der täglichen genutzten Werkzeuglandschaft an diesem Standort

A Simulation study of dispatching rules and rework strategies in semiconductor manufacturing

The semiconductor industry is fast paced and on the cutting edge of technology, resulting in very short life spans of semiconductor products. In order to stay competitive, manufacturers must be able to quickly adapt to produce new products, and they must achieve a high level of productivity. Two major operational components of semiconductor fabrication plants (fabs) that effect productivity are dispatching rules and rework strategies. Although prior research has been conducted independently on these two issues, the hypothesis is that the interrelationship between the dispatching rules and rework strategies has a significant effect on the productivity of the fab. Moreover, the goal is to determine which combination of widely-used dispatching rules and new and existing rework strategies results in the highest level of fab productivity. To test this hypothesis, the significance of rework is evalutated, and a four-factor experiment is conducted to determine the effect of dispatching rules, rework strategies, fab types, and rework levels on key fab performance measures. Five dispatching rules are combined with three previously studied rework strategies and the first bottleneck strategy which is developed in this study. The treatment combinations are compared based on fab performance measures including cycle time, percentage on time, work-in-process, and the XTheoretical value. Simulation models based on actual fab data are constructed to carry out the experiments. The detailed results of the experiment show that combinations of dispatching rules and rework strategies have a significant impact on fab performance measures at each rework level in both fab types. In general, two dispatching rules, rework priority and first-in-first-out, in combination with the first bottleneck rework strategy perform the best. Further analysis concludes that the rework priority dispatching rule and the first bottleneck rework strategy result in the highest level of fab performance and are most robust over alterative fab configurations