Browsing by Subject "Semiconductor industry--Production control"

Now showing 1 - 4 of 4

Adaptive run-to-run control of overlay in semiconductor manufacturing
(2002) Martinez, Victor Manuel; Edgar, Thomas F.
Advanced process control and optimal sampling in semiconductor manufacturing
(2008-08) Lee, Hyung Joo, 1979-; Edgar, Thomas F.
Semiconductor manufacturing is characterized by a dynamic, varying environment and the technology to produce integrated circuits is always shifting in response to the demand for faster and new products, and the time between the development of a new profitable method of manufacturing and its transfer to tangible production is very short. The semiconductor industry has adopted the use of advanced process control (APC), namely a set of automated methodologies to reach desired process goals in operating individual process steps. That is because the ultimate motivation for APC is improved device yield and a typical semiconductor manufacturing process can have several hundred unit processes, any of which could be a yield limiter if a given unit procedure is out of control. APC uses information about the materials to be processed, metrology data, and the desired output results to choose which model and control plan to employ. The current focus of APC for semiconductor manufacturers is run-to-run control. Many metrology applications have become key enablers for the conventionally labeled “value-added” processing steps in lithography and etch and are now integral parts of these processes. The economic advantage of effective metrology applications increases with the difficulty of the manufacturing process. Frequent measurement facilitates products reaching its target but it increases the cost and cycle time. If lots of measurements are skipped, the product quality does not be guaranteed due to process error from uncompensated drift and step disturbance. Thus, it is necessary to optimize the sampling plan in order to quickly identify the sources of prediction errors and decrease the metrology cost and cycle time. The goal of this research intend to understand the relationship between metrology and advanced process control (APC) in semiconductor manufacturing and develop an enhanced sampling strategy in order to maximize the value of metrology and control for critical wafer features.
Just-in-time adaptive disturbance estimation for run-to-run control in semiconductor processes
(2002-12) Firsth, Stacy Kay; Edgar, Thomas F.
As run-to-run control has become more widely used throughout the semiconductor industry, it has become apparent that some of the unique characteristics of discrete parts manufacturing are driving the need for enhanced algorithm development. One such trait is the high mix of products made in a single factory (such as an ASIC fab or foundry). Variations in product quality often are functions of the product being produced as well as the manufacturing tools being used. Therefore, control systems are often designed to use only feedback data from lots that are the same product and have experienced the same upstream process flow as the lot currently being processed. In high-mix fabs with many products, some of the feedback loops may operate with hours or even days between data points in the feedback loop. This long delay results in a loss of information about the process tool’s contribution to the variance in that specific product. Solving the problem of product quality dependence on manufacturing context for photolithography overlay is much more difficult as there are many more factors which may contribute to variation. Because overlay is a relative measurement between two processing layers, overlay control systems generally segregate the control loops not only by tool and product, but also by substrate characteristics (reference layer tool, reticle, etc.). It can be easily imagined how a high-volume, high-mix fab operating in a mix-and-match lithography mode can generate hundreds of combinations of manufacturing contexts that result in a scarcity of feedback information for any given lot. Just-in-time Adaptive Disturbance Estimation (JADE) uses recursive weighted least-squares parameter estimation to identify the contributions to variation that are dependent upon manufacturing context such as tool, product, reference tool, and reference reticle. In using JADE, the run-to-run controller may use all available feedback data and does not ignore the fact that many lots may have been run since the last time a particular product was processed. The application of JADE, as well as traditional control techniques, is demonstrated on lithography overlay and chemical mechanical planarization (CMP) data taken from high-mix production facilities. The strengths and weaknesses of the JADEalgorithm are demonstrated on a series of test cases developed to separate the various disturbances and processing issues a control system would be expected to encounter. Although JADEhas been applied to an overlay process and a CMP process, this estimation technique should be applicable to any process area in the fab.
The stability and performance of the EWMA and double-EWMA run-to-run controllers with metrology delay
(2004) Good, Richard Paul; Qin, S. Joe
Because of the ever-increasing demands on product quality, feedback con- trol has become a necessary enabling component in the manufacture of modern semiconductor devices. The nature of semiconductor manufacturing is such that measurements of device quality characteristics are not available during the processing of the product. Measurements are not made until after the product is processed and necessary changes to tool setting can only be made to subsequent production runs. This control scheme, termed run-to-run control, has become the cornerstone of process control in the semiconductor manufacturing industry. In addition to the ever-increasing demands on product quality, the semi- conductor manufacturing industry continues to see stringent growth in throughput requirements. Because of the demands on production throughput, it is rarely possi- ble to perform quality measurements on a batch of wafers before processing begins on the following batch of wafers. The delay between product manufacturing and product metrology coupled with inaccurate process models can lead to process in- stabilities and deterioration in controller performance. This dissertation investigates the robust stability requirements of processes controlled with EWMA and double- EWMA run-to-run controllers with delays between processing and metrology. In addition, the effects of model mismatch and metrology delay on the closed-loop performance of the EWMA and double-EWMA run-to-run controllers are derived by extending the robust stability methodology. Finally, these robust performance requirements are used to find the optimal tuning parameters for the double-EWMA controller. These tuning parameters allow for the largest model uncertainty while guaranteeing a predetermined minimum closed-loop transient performance.