Sven Horn

Simulation based scheduling system in a semiconductor backend facility

The semiconductor manufacturing process is usually divided in two parts: frontend and backend. In contrast to the frontend, where the manufacturing process is dominated by cluster-tools and cyclic routes, the backend has a predominant linear structure. In contrast to the frontend flow which is mostly controlled by dispatch rules, the backend process is suitable for real scheduling. A scheduling system for the backend of Infineon Technologies Dresden based on a discrete event simulation (DES) system was developed and tested in the real industrial environment. The simulation model is automatically generated from the databases of the manufacturer. The system is used for short term scheduling - from one shift up to one week. The paper will focus on the aspect of optimizing the process flow and calculating exact release dates for lots. The basic principles are applicable not only in the semiconductor industry but also in other industrial sectors

Design and validation of heuristic algorithms for simulation-based scheduling of a semiconductor Backend facility

A simulation-based scheduling system is discussed which was developed for a semiconductor Backend facility. Apart from usual dispatching rules it uses heuristic search strategies for the optimisation of the operating sequences. In practice hereby multiple objectives have to be considered, e.g. concurrent minimisation of mean cycle time, maximisation of throughput and due date compliance. Because the simulation model is very complex and simulation time itself is not negligible, we emphasise to increase the convergence of heuristic optimisation methods, consequentially reducing the number of necessary iterations. Several realised strategies are presented.

Simulations-based and solver-based optimization approaches for batch processes in semiconductor manufacturing

Scheduling is one of the key factors for semiconductor fabrication productivity. Objectives like lot cycle time and throughput must be optimized to push the technological development and secure the existence on the rapid growing global market. But especially in the frontend the manufacturing process is dominated by cluster-tools and reentrance flows which makes a production planning and optimization very hard. The workflow here is mostly controlled only by dispatch rules. To get a further improvement in manufacturing planning strategies, there is an increasing request of exact or simulation-based solution methods for specified work centers or bottleneck machine groups. One example of this is the semiconductor oven process. Here, complex batch processes with a lot of restrictions have to be scheduled. A reduction of cycle time in this section by optimized manufacturing strategies has a great influence on all global optimization objectives. Two approaches are investigated in this paper.

Optimization of manufacturing processes by distributed simulation

The paper describes a simulation-based optimization system for manufacturing processes. The principle suitability of simple Threshold Accepting and Great Deluge Algorithms for optimizing practical manufacturing systems is shown, as well as the possibility of parallelizing of these algorithms. A special IP Multicast architecture is introduced which allows the simulation model to be extended to multiple clients and so the efficiency of the optimization algorithms to be increased by concurrent simulation. Each client can log on or log out at an optimization server at any time so that it should be possible to use the idle computer capacity of a single production department or a whole company. The optimization server is implemented as an experimental option in the simulation system simcron MODELLER®, which is particularly used in electronics and semiconductor manufacturing.

Investigation of modified heuristic algorithms for simulation-based optimization

For optimization of manufacturing processes in electronics and semiconductor production, simulation-based optimization algorithms become more and more important. In addition to the usual dispatching rules we use iterative local search algorithms for scheduling. In this paper we focus on highly complex manufacturing models with difficult technological operational sequences. In particular, these contain cost extensive machine setups with a limited number of tools. So it is our aim to optimize the manufacturing workflow by minimizing the setup and machine idle times. This was realized by modifying the generally used control variables (job sequences, priorities, etc..) to model-specific product mixture control variables. Furthermore we describe some extensions of known heuristic search algorithms to increase their efficiency. We also developed a Matlab-based visualization tool to better evaluate the effectiveness of the investigated optimization processes.

Heuristic optimization strategies for scheduling of manufacturing processes

Discrete Event Simulation (DES) is a suitable method for scheduling manufacturing processes, particularly in the case of finite capacity resources. In practice mostly special dispatching rules are used for optimizing the process. In addition several heuristic optimization algorithms were developed to get better results by changing control variables in connection with repeated simulation runs. In a manufacturing process the most important control variables are permutations (of jobs, priorities etc.). The convergence behavior of the algorithms strongly depends on the distance measurement in the control space because this decides about the increment of the search steps. Some special distance measurements for permutations are developed and they are investigated for diverse structures of manufacturing systems, such as flowshops and jobshops.

Simulation aided optimisation of manufacturing processes in university education

Simulation methods become more and more important in practical applications of scheduling, analysis and optimisation of manufacturing processes. One consequence is that the event discrete simulation systems and their application become part of the fundamentals of engineering education, even if the students should not become specialists in simulation methods. In our paper we show how the simulation of manufacturing processes can be used to make the theory clearer. The simulation models are simple but the need further development towards more complex and more practical models becomes apparent. This paper is also a field report about experiences with the simcron MODELLER in education.

Application of Simulation-Based Scheduling in a Semiconductor Backend Facility

A simulation-based interactive scheduling system for the backend facility of a semiconductor manufacturer was developed and tested under practical conditions. The special characteristic of the so called backendplanner is the automated model generation from existent production databases. The deterministic simulation model considers dispatch and setup rules and additionally includes a heuristic optimization component. The planning horizon reaches from one shift to one week. The fast simulator and the efficient data coupling strategy allows the re-scheduling anytime, e.g. after machine breakdowns or other unpredictable events. Several additional analyze tools report important parameters of the manufacturing process, such as machine utilization, throughput time or work in process. The basic principles are applicable not only in the semiconductor industry but also in other industrial sectors

Data coupling strategies in production environments

To provide real-time scheduling in production environments a very close data coupling between the data world of the production and the scheduling software is necessary. The most significant requests are high performance and guaranteed reliability. This is essential if you do not plan a simulation-based study, but a simulation-based real-time production planning system. We developed two strategies of data coupling which meet these criteria: a replication strategy with incremental data update and a caching strategy. Both strategies are tested for performance and proved under common production conditions. We explain the concept and specify the realization as database coupling technique in the paper. The results of the performance measurements are also included and outlined with illustrations

Simulationsgestützte Optimierung von Fertigungsprozessen in der Halbleiterindustrie

Der Beitrag beschreibt die Entwicklung und Umsetzung eines simulationsgestutzten Optimierungssystems fur den Backendbereich eines Halbleiterherstellers. Typisch fur eine Halbleiterfertigung ist ein breites Produktspektrum mit Produkten aus unterschiedlichen Produktlebenszyklen. Daraus folgen unterschiedliche Zielanforderungen fur einzelne Prozessschritte bzw. Produkte die daruber hinaus durch Marktschwankungen einer starken zeitlichen Dynamik ausgesetzt sind. Da insbesondere im Backend-Bereich ein Hochstmas an (Ablauf-) Flexibilitat gefordert ist, ist ein simulationsgestutztes Scheduling-System gegenuber einer auf starren Regeln basierenden Steuerung im Vorteil. Im Ergebnis des Projekts entstand eine Software, die in der Fertigung im 7 ´ 24-Regime eingesetzt wurde.