In an assembly line with high labor proportion, the workforce planning and scheduling is a very complex problem. At the background of increasing labor costs, it is very important to increase workforce efficiency. It is essential for companies to remain competitive on global markets. Increasing efficiency is our motivation to work on simulation-based workforce scheduling for complex assembly lines. In this paper, we will focus on the heuristic algorithm in our simulation-based optimization approach. The objective is workforce quantity and slack reduction. To improve the objective, an algorithm assigns the number of workers for activities, scheduled in the simulation run. We will present three different strategies implemented in these optimization algorithms. They basically use the performance indicator slack time, work center utilization and a mix of both parameters. We will compare the algorithms according to their achieved objective and the required computation time.

Vibrography is a new low-risk technique for intraoperative imaging. In low-grade astrocytomas and oligodendrogliomas, this additional technique can be used to control resection. In other cortical and subcortical tumors (e. g. metastases), it can provide an impression of the intratumoral elasticities.

To make use of short-term simulation on an operational level, three aspects are essential. First, the simulation model needs to have a high level of detail to represent a small part of the wafer fab with sufficient precision. Second, the simulation model needs to be initialized very well with the current fab state. And third, the simulation results need to be available very fast, almost in real time. Unfortunately these conditions contradict each other. In particular, it takes a large amount of time to initialize a high precision full fab simulation model because of the huge amount of data. In this paper, we present the prototype of a fab driven simulation approach to overcome these time consuming limitations. We will show how it is possible to start a short-term simulation from the current fab state immediately, i.e., without further delay.

The usual forecast method in semiconductor industry is simulation. Due to the manufacturing environment, the number of processes and the multitude of disturbing factors the development of high-fidelity simulation model is time-consuming and requires a huge amount of high quality basic data. The simulation facilitates a detailed prediction possible, but in many cases this level of detail of the forecast information is not required. In this paper, we present an alternative forecast method. It is considerably faster and the results for a subset of parameters are comparable to simulation. The solution does not need a complete fab model but a limited mathematical system and some fast algorithms which make the forecast of important parameters or characteristics possible. The prediction is based completely on statistics extracted from historical lot data traces. It is already implemented and tested in a real semiconductor fab environment and we also present some validation results.

The ability to perform lot arrival forecast at work center level is a key requirement for pro-active FAB operation management. Visibility to this information enables preemptive resource allocation and bottleneck management. Today, the work center lot arrival forecast is achieved through the use of short term simulation technique in Infineon Dresden. High fidelity simulation model that includes detailed modeling feature such as attribute-based sampling procedure, dedication and temporary tool blocking is built automatically through the transformation of data queries from data sources. In this paper, we present the results of our model validation work, comparing the FAB and forecasted lot arrival of the defect density measurement work center. Due to the high capacity demand of automotive product that requires more than 20 inspection steps; engineering lots and preventive maintenance of DDM must be scheduled at the right time. This can only be achieved with high quality lot arrival forecast.