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

Polymeric Microsensors for Intraoperative Contact Pressure Measurement

Biocompatible sensors have been demonstrated using traditional microfabrication techniques modified for polymer substrates and utilize only materials suitable for implantation or bodily contact. Sensor arrays for the measurement of the load condition of polyethylene spacers in the total knee arthroplasty (TKA) prosthesis have been developed. Arrays of capacitive sensors are used to determine the three-dimensional strain within the polyethylene prosthesis component. Data from these sensors can be used to give researchers a better understanding of component motion, loading, and wear phenomena for a large range of activities. This dissertation demonstrates both analytically and experimentally the fabrication of these sensor arrays using biocompatible polymer substrates and dielectrics while preserving industry-standard microfabrication processing for micron-level resolution. An array of sensors for real-time measurement of pressure profiles is the long-term goal of this research. A custom design using capacitive-based sensors is an excellent selection for such measurement, giving high spatial resolution across the sensing surface and high load resolution for pressures applied normal to that surface while operating at low power

Novel Applications of a Thermally Tunable Bistable Buckling Silicon-on-Insulator (SOI) Microfabricated Membrane

Buckled membranes are commonly used microelectromechanical systems (MEMS) structures. Recent work has demonstrated that the deflection and stiffness of these membranes can be tuned through localized joule heating. These devices were implemented into the design and fabrication of two novel device applications, a tunable pressure sensor and a steerable micromirror. A differential pressure across the membrane causes de reflection, up or down, which can be measured and related to a specific pressure. By tuning the stiffness of the membrane, its pressure response is varied providing a wider range of application for the pressure sensor. A 2.0mm by 2.0mm square membrane demonstrated a 60 percent decrease in pressure sensitivity from 1.433m/psi to 0.55m/psi. A steerable micromirror was realized by selectively heating a single quadrant of a buckled membrane, localized heating results in membrane de deflection constrained to that quadrant

Journal of Microelectronic Research - May 2003

https://scholarworks.rit.edu/meec_archive/1012/thumbnail.jp

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

Stochastic optimization of product-machine qualification in a semiconductor back-end facility

abstract: In order to process a product in a semiconductor back-end facility, a machine needs to be qualified, first by having product-specific software installed and then running test wafers through it to verify that the machine is capable of performing the process correctly. In general, not all machines are qualified to process all products due to the high machine qualification cost and tool set availability. The machine qualification decision affects future capacity allocation in the facility and subsequently affects daily production schedules. To balance the tradeoff between current machine qualification costs and future potential backorder costs due to not enough machines qualified with uncertain demand, a stochastic product–machine qualification optimization model is proposed in this article. The L-shaped method and acceleration techniques are proposed to solve the stochastic model. Computational results are provided to show the necessity of the stochastic model and the performance of different solution methods.This is an Author's Accepted Manuscript of an article published as Fu, Mengying, Askin, Ronald, Fowler, John, & Zhang, Muhong (2015). Stochastic optimization of product-machine qualification in a semiconductor back-end facility. IIE TRANSACTIONS, 47(7), 739-750. DOI: 10.1080/0740817X.2014.964887. Copyright Taylor & Francis, available online at: http://www.tandfonline.com/doi/abs/10.1080/0740817X.2014.96488