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

AI based state observer for optimal process control: application to digital twins of manufacturing plants

Les plantes de fabricació estan subjectes a restriccions dinàmiques que requereixen una optimització robusta per millorar el rendiment i l' eficiència del sistema. En aquest projecte es presenta un nou sistema de control òptim basat en IA per a un bessó digital d' una planta de fabricació. El sistema proposat implementa un observador d' estat basat en IA per predir l' estat intern d' un model de procés altament incert i no lineal, tal com seria un sistema de producció real. Una funció d' optimització multi-objectiu es utilitzada per controlar els paràmetres de producció i mantenir el procés funcionant en condicions òptimes. El mètode d'Optimització del Control basat en AI es va implementar en un cas d'estudi d'una planta de fabricació d'acer. El rendiment del sistema es va avaluar utilitzant els KPIs de fabricació rellevants, com ara les taxes d'utilització i productivitat de l'equip del procés. L'ús de sistema de control optimitzat via AI millora amb èxit els KPIs de procés i potencialment podria reduir els costos de producció.Las plantas de fabricación están sujetas a restricciones dinámicas que requieren una optimización robusta para mejorar el rendimiento y la eficiencia. En este informe se presenta un nuevo sistema de control óptimo basado en IA para un gemelo digital de una planta de fabricación. El sistema propuesto implementa un observador de estado basado en IA para predecir el estado interno de un modelo de proceso altamente incierto y no lineal, tal y como sería un sistema de producción real. Una función de optimización multiobjetivo es utilizada para controlar los parámetros de producción y mantener el proceso funcionando en condiciones óptimas. El método de Optimización del Control basado en AI se implementó en un caso de estudio de una planta de fabricación de acero. El rendimiento del sistema se evaluó utilizando los KPIs de fabricación relevantes, como la utilización del equipo y las tasas de productividad del proceso. El uso del sistema de control óptimo de IA mejora los KPIs del proceso y podría reducir potencialmente los costos de producción.Manufacturing plants are subject to dynamic constrains requiring robust optimization methods for improved performance and efficiency. A novel AI based optimal control system for a Digital Twin of a manufacturing plant is presented in this report. The proposed system implements an AI based state observer to predict the internal state of a highly uncertain and non-linear process model, such as a real production system. A multi-objective optimization function is used to control production parameters and keeps the process running at an optimal condition. The AI Optimization Control method was implemented on a study case on a steel manufacturing plant. The performance of the system was evaluated using the relevant manufacturing KPIs such as the equipment utilization and productivity rates of the process. The use of the AI optimal control system successfully improves the process KPIs and could potentially reduce production costs

A NASA family of minicomputer systems, Appendix A

This investigation was undertaken to establish sufficient specifications, or standards, for minicomputer hardware and software to provide NASA with realizable economics in quantity purchases, interchangeability of minicomputers, software, storage and peripherals, and a uniformly high quality. The standards will define minicomputer system component types, each specialized to its intended NASA application, in as many levels of capacity as required

Discrete Event Simulations

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES

Productivity improvement in downstream EPC projects using value streams based organization

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2006.Includes bibliographical references (p. 82).Productivity improvements in manufacturing facilities have been studied in detail and there are many standardized tools and frameworks readily available to the industry for implementation. However the concept of productivity improvement in large engineering projects that involve high white-collar job content is less clearly understood. While lean concepts like value streams or continuous improvement apply to this environment there are no ready tools available for implementing a lean improvement initiative. This thesis applies lean and concurrent engineering concepts to large scale engineering design and development projects. ABB Lummus, the sponsor company for the internship behind this thesis, is in the business of executing such large-scale projects. Lummus is an EPC contractor providing engineering, procurement and construction (EPC) services for building manufacturing plants. EPC projects run for few years and involve coordination of efforts by hundreds of engineering staff. There are inherently many productivity and information flow issues in such projects. EPC industry in general has been facing significant operational efficiency difficulties leading to cost and schedule overruns in recent years.(cont.) The main issue was identified as rework due to the fact that the existing project structures do not deal with concurrent engineering nature of the projects. In this thesis we leverage the concepts a combination of lean value streams, Design Structure Matrix (DSM) and Theory of Constraints (TOC) to propose a value streams based organization for EPC projects. We show how this approach addresses the common problem in the EPC projects and sets the stage for improving productivity. The discussion in this thesis has helped launch an initiative that has enabled the acceptance of value streams and DSM techniques at ABB Lummus. Currently a dedicated program is planning a large (> 1 Bn Euro) EPC project along the line of value streams. The following are the key contributions in this thesis: From first principles we define a way to decompose an EPC downstream project into nine value streams. We use DSM to analyze a key value stream in detail and show the need for a value-stream-based organization. Using value streams and DSM we enable the implementation of TOC planning in EPC projects and show how these tools complement each other.by Krishnan Raghunathan.S.M.M.B.A

An Adaptive Simulation-based Decision-Making Framework for Small and Medium sized Enterprises

Abstract The rapid development of key mobile technology supporting the ‘Internet of Things’, such as 3G, Radio Frequency Identification (RFID), and Zigbee etc. and the advanced decision making methods have improved the Decision-Making System (DMS) significantly in the last decade. Advanced wireless technology can provide a real-time data collection to support DMS and the effective decision making techniques based on the real-time data can improve Supply Chain (SC) efficiency. However, it is difficult for Small and Medium sized Enterprises (SMEs) to effectively adopt this technology because of the complexity of technology and methods, and the limited resources of SMEs. Consequently, a suitable DMS which can support effective decision making is required in the operation of SMEs in SCs. This thesis conducts research on developing an adaptive simulation-based DMS for SMEs in the manufacturing sector. This research is to help and support SMEs to improve their competitiveness by reducing costs, and reacting responsively, rapidly and effectively to the demands of customers. An adaptive developed framework is able to answer flexible ‘what-if’ questions by finding, optimising and comparing solutions under the different scenarios for supporting SME-managers to make efficient and effective decisions and more customer-driven enterprises. The proposed framework consists of simulation blocks separated by data filter and convert layers. A simulation block may include cell simulators, optimisation blocks, and databases. A cell simulator is able to provide an initial solution under a special scenario. An optimisation block is able to output a group of optimum solutions based on the initial solution for decision makers. A two-phase optimisation algorithm integrated Conflicted Key Points Optimisation (CKPO) and Dispatching Optimisation Algorithm (DOA) is proposed for the condition of Jm|STsi,b with Lot-Streaming (LS). The feature of the integrated optimisation algorithm is demonstrated using a UK-based manufacture case study. Each simulation block is a relatively independent unit separated by the relevant data layers. Thus SMEs are able to design their simulation blocks according to their requirements and constraints, such as small budgets, limited professional staff, etc. A simulation block can communicate to the relative simulation block by the relevant data filter and convert layers and this constructs a communication and information network to support DMSs of Supply Chains (SCs). Two case studies have been conducted to validate the proposed simulation framework. An SME which produces gifts in a SC is adopted to validate the Make To Stock (MTS) production strategy by a developed stock-driven simulation-based DMS. A schedule-driven simulation-based DMS is implemented for a UK-based manufacturing case study using the Make To Order (MTO) production strategy. The two simulation-based DMSs are able to provide various data to support management decision making depending on different scenarios

A proposed model for servitization based collaboration in the UK Aerospace Defence industry

In many sectors customers are increasingly seeking service contracts rather than buying products. High tech capital equipment firms attracted by the potential revenue benefits are choosing to move from supplying product only to supplying product and services. This concept is known as ‘Servitization’. Through empirical evidence the academic literature has shown that businesses face challenges in undertaking the transformation from product to service provision and that organisational, cultural, commercial and operational challenges have the potential to erode the desired and expected benefits sought from such a transition. The research presented in this thesis investigates and identifies the features and challenges of servitization in the context of a complex engineering service provided by the UK Aerospace Defence industry. The research also explores the reported costs and front of mind costs for the provision of a complex engineering service. Particular attention is given to the problem of less than expected profitability during and post transformation to service. This research adopts a qualitative approach through the use of a single case study with multiple case examples of the complex engineering service. Findings identify a number of challenges associated with the transformation from product to service provision that include strategy, organisation and enterprise management, contracting, risk, culture and operations. Considering these findings holistically it is suggested that a paradigm shift needs to occur, changing both managers perspective and the business models employed if the firm is to provide a sustainable service offering. New ways of structuring and managing the enterprise to deliver the service value proposition will be required. This will include the development of performance management of all operations across the enterprise required as a minimum to ensure optimum performance of service delivery at lowest cost

System simulation and modeling of electronics demanufacturing facilities

Over the last decade, pressure on the electronic industry has been increasing as concerns for product take-back, product stewardship and global warming have continued to grow. Various end-of-life management options are being expanded including recycling to recapture values from basic materials through reengineering and recovery of subassemblies and individual components for remanufacturing. While progress has been reported on life cycle assessment (LCA), disassembly planning, design for disassembly, and design for environment (DFE), very little research has been focused on demanufacturing from a systems perspective. The objective of this thesis is to build an interface between the user who knows the demanufacturing operation and a software engine, which performs the simulation, collects detailed operational data, and displays results. This thesis bridges the gap between the requirement of hard core simulation knowledge and demanufacturing terminology to present a computerized software tool. Arena, a commercially available discrete event simulation software, acts as an engine for performing these simulations. The developed software tool for demanufacturing contains objects necessary for facility layout, systematic workflow and simulation of the facility. Each object refers to a specific demanufacturing activity and uses detailed simulation logic behind its design to perform that activity. The user selects and locates these objects to layout the facility for a graphical representation of the demanufacturing operation. Objects provide a user screen to input necessary data for the complete description of the activity and its operational characteristics. By simulating the facility for various scenarios, the demanufacturer can compare different options for improving operations, resource utilization, equipment and layout changes. To examine improvement options from an economic perspective a first-order model of demanufacturing costs has been developed and integrated with the simulation software. An activity based unit cost model is used to identify fixed and variable costs associated with each product demanufactured. A small electronics demanufacturing facility was observed and evaluated to validate the simulation modeling and operational logic. The application illustrates the usefulness of demanufacturing system simulation tool to manage and improve the overall efficiency of facilities for economical operation. In summary, a computer-base tool for simulating demanufacturing facility from a systems perspective has been developed and validated. An activity based cost model has been integrated with the simulation to give demanufacturers the ability to examine the full operational and economic trade-offs associated with the business

The responsive reply chain: the influence of the positioning of decoupling points

Manufacturing supply chains have been challenged by high competition, dynamic, and stochastic conditions. They have to be constantly responsive in today’s ever-changing manufacturing environment. The proper positioning of decoupling points for material flow and information flow has a significant potential for increasing responsiveness in a supply chain. Positioning the material decoupling point as close to the end consumer as possible whilst the information decoupling point is positioned upstream is the key to the industries’ ability to reduce lead time and enhance performance in the dynamic behaviour of the supply chain. [Continues.