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

MODELING AND SIMULATION OF A SEMICONDUCTOR MANUFACTURING FAB FOR CYCLE TIME ANALYSIS

The goal of the thesis is to conduct a study of the effects of scheduling policies and machine failures on the manufacturing cycle time of the Integrated Circuit (IC) manufacturing process for two processor chips, namely Skylake and Kabylake, manufactured by Intel. The fab simulation model was developed as First in First Out (FIFO), Shortest Processing Time (SPT), Priority based (PB), and Failure FIFO (machine failures) model, and the average cycle times and queue waiting times under the four scheduling policy models were compared for both the Skylake and Kabylake wafers. The study revealed that scheduling policies SPT and PB increased the average cycle time for Skylake wafers while decreasing the average cycle time for the Kabylake wafers, when compared to the base FIFO model. Machine failures increased the average cycle time for both types of wafers

Scheduling and discrete event control of flexible manufacturing systems based on Petri nets

A flexible manufacturing system (FMS) is a computerized production system that can simultaneously manufacture multiple types of products using various resources such as robots and multi-purpose machines. The central problems associated with design of flexible manufacturing systems are related to process planning, scheduling, coordination control, and monitoring. Many methods exist for scheduling and control of flexible manufacturing systems, although very few methods have addressed the complexity of whole FMS operations. This thesis presents a Petri net based method for deadlock-free scheduling and discrete event control of flexible manufacturing systems. A significant advantage of Petri net based methods is their powerful modeling capability. Petri nets can explicitly and concisely model the concurrent and asynchronous activities, multi-layer resource sharing, routing flexibility, limited buffers and precedence constraints in FMSs. Petri nets can also provide an explicit way for considering deadlock situations in FMSs, and thus facilitate significantly the design of a deadlock-free scheduling and control system. The contributions of this work are multifold. First, it develops a methodology for discrete event controller synthesis for flexible manufacturing systems in a timed Petri net framework. The resulting Petri nets have the desired qualitative properties of liveness, boundedness (safeness), and reversibility, which imply freedom from deadlock, no capacity overflow, and cyclic behavior, respectively. This precludes the costly mathematical analysis for these properties and reduces on-line computation overhead to avoid deadlocks. The performance and sensitivity of resulting Petri nets, thus corresponding control systems, are evaluated. Second, it introduces a hybrid heuristic search algorithm based on Petri nets for deadlock-free scheduling of flexible manufacturing systems. The issues such as deadlock, routing flexibility, multiple lot size, limited buffer size and material handling (loading/unloading) are explored. Third, it proposes a way to employ fuzzy dispatching rules in a Petri net framework for multi-criterion scheduling. Finally, it shows the effectiveness of the developed methods through several manufacturing system examples compared with benchmark dispatching rules, integer programming and Lagrangian relaxation approaches

A product mix and a material flow problem concerning the semiconductor manufacturing industry

Das zentrale Thema dieser Arbeit behandelt die Optimierung der Programm- und Ablaufplanung in der Halbleiterindustrie. Die Diplomarbeit besteht aus zwei separaten Teilen. Der erste Abschnitt befasst sich mit einem Unternehmen aus dieser Branche namens Infineon Technologies AG. Dieser internationale Konzern dient als Beispiel für den theoretischen Hintergrund des Halbleiter-Fertigungsprozesses mit seinen spezifischen Anforderungen. Das zugrunde liegende Verfahren zeichnet sich durch große Anfälligkeit der Produkte während des Produktionsprozesses und enorme Komplexität aus. Da die gesamte Fertigung nicht als Ganzes betrachtet und optimiert werden kann, werden in der Diplomarbeit zwei unterschiedliche Problemstellungen angeführt: ein Produkt-Mix und ein Material-Flow-Problem. Dabei wird einerseits versucht, den Profit zu maximieren, andererseits soll die gesamte Herstellungszeit innerhalb einer Werkstatt minimiert werden. Diese beiden Sachverhalte werden zunächst theoretisch diskutiert und in weiterer Folge wird die mathematische Modellierung mit Xpress optimal gelöst. Das Produkt-Mix Teilproblem erfordert lediglich die Umsetzung in Xpress, da die generierten Ergebnisse Optimalität aufweisen und die Rechenzeit sich um 0 Sekunden in jedem Durchlauf bewegt. Daher wird kein weiterer Vergleich mit einer anderen Software-Implementierung dargestellt. Die generierten Lösungen des Materialfluss-Problems aus Xpress werden mit den heuristischen Ergebnissen anhand der Implementierung in C++ verglichen. Diese Ergebnisse erreichen die Optimalität nicht, sondern bieten eine gute und praktikable Lösung für eine größere Auswahl von Fällen in angemessener Rechenzeit

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques

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

Cost based rescheduling approach to handle disruptions in flexible manufacturing systems

Rescheduling is an essential operating task to efficiently tackle uncertainties and unexpected events frequently encountered in today's complex and flexible manufacturing systems. The main purpose of this thesis is to develop a real time reactive scheduling methodology in order to respond to such disturbances and uncertainties in a cost efficient manner. In order to assess the impact of schedule changes, a compound rescheduling cost function is developed based on machine, job, and material related rescheduling activities. A Total Rescheduling (TR) approach based on the Filtered-Beam-Search-heuristic algorithm (FBS) is proposed to generate a prespecified number of cost efficient suboptimal schedules by using the proposed cost function in case of each disruption. Thereafter, the current schedule is replaced by the alternative schedule which causes the minimum rescheduling cost. Responding to each single disruption with TR may cause system nervousness and increase the operational cost. Hence, a partial rescheduling approach is developed by a Modified Filtered-Beam-Search-heuristic algorithm (MFBSR) in order to generate a prespecified number of sub optimal cost-efficient schedules with a lower rescheduling cost and fewer deviations than TR. In order to validate the performance of the proposed methodologies, TR and MFBSR, different case studies and experimental designs have been performed considering various disruption scenarios. The performance of the suggested methods in terms of rescheduling cost, makespan efficiency and stability have been compared with similar rescheduling and repair methods in the literature. The results reveal that the proposed methodologies could be considered as competitive methods in responding to disruptions in flexible manufacturing system

Design and implementation of a decision support framework for evaluating manufacturing alternatives

To be competitive in domestic and international markets, manufacturing management is routinely faced with the decision to automate or replace existing production facilities with advanced manufacturing technologies. Installation of advanced manufacturing technologies requires high capital investment, and there is much evidence to suggest that automation for automation's sake has proven to be costly and ineffective for many organizations. What makes the justification task more challenging is the lack of decision tools and methodologies that incorporate the intangible benefits from such investments. This research develops a decision support framework for modeling the evaluation and selection of manufacturing system investments. A multi-attribute decision approach is used to capture the quantitative and qualitative aspects of the decision problem. Based on data collected from slected sample from industry, this research synthesized attributes typically considered important in selection of manufacturing alternatives and established their relative importance. The effectiveness of the decision framework was evaluated using a case study, representative of an industrial application. A computer implementation of the decision framework provides a simulation model for structuring alternatives and estimating performance measures (attributes). This is integrated with a multi-attribute evaluation model for comparison of alternatives. Unlike commercial simulation systems that requires user understanding of the simulation system or language, the system developed in this research uses a natural language interface enabling its use without the need to understand the underlying programming structure. This research has two implications, practically and academically. It can assist decision makers to better understand and apply the justification process and the system behavior under different manufacturing scenarios. Academically, it can be used also as an educational tool for students to understand the justification process, and its tradeoffs and complexities

A Digital Twin Framework for Production Planning Optimization: Applications for Make-To-Order Manufacturers

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing the limitations in accurately representing production environments. The consequence has been a serious gap between theory advancement and industry practice. The major goal of this dissertation is to develop a framework that allows for practical testing, evaluation, and implementation of new approaches for seamless industry adoption. We develop this framework as a modular software package and emphasize the practicality and configurability of the framework, such that minimal modelling effort is required to apply the framework to a multitude of optimization problems and manufacturing systems. Throughout this dissertation, we emphasize the importance of the underlying scheduling problems which provide the basis for additional operational decision making. We focus on the computational evaluation and comparisons of various modeling choices within the developed frameworks, with the objective of identifying models which are both effective and computationally efficient. In Part 1 of this dissertation, we consider a class of Production Planning and Execution problems faced by job shop manufacturing systems. In Part 2 of this dissertation, we consider a class of scheduling problems faced by manufacturers whose production system is dominated by a single operation

Computer Controlled Urban Transportation: A Survey of Concepts, Methods, and International Experiences

This book is concerned with the present and future traffic problems in the developing and developed world. It examines possible solutions to those problems based on technological innovations and implementing large-scale computerized traffic and transportation control systems. It discusses the basic concepts and methods for control and automation that have been proposed, developed, and implemented, and experience from real applications of these in different cities and nations