Achieving good uniformity process control in chemical mechanical polishing (CMP) requires a representative uniformity metric and strong models relating this metric to process tunable inputs. Previous efforts in CMP uniformity control have yielded acceptable results utilizing a center-to-edge (CTE) first order nonuniformity metric. Closer analysis of post CMP process nonuniformity, however, reveals significant higher order nonuniformity components such as the center “dimple” and outer “doughnut” regions. These nonuniformity characteristics are due in part to upstream chemical vapor deposition (CVD) processing. Utilizing a multizone approach to uniformity modeling, a more accurate mathematical model of CMP uniformity has been identified. The model has been utilized to customize a thickness and uniformity multivariate run-to-run software control solution for the process. The controller is based on the generic cell controller structure, which is a proven enabler for run-to-run control for a number of processes including CMP, vapor phase epitaxy, and etch. The control algorithm is a zeroth order adjustable linear approximation two-stage algorithm with exponentially weighted moving average noise filtering. This algorithm, which supports first order linear and nonlinear models, has been demonstrated to be effective in CMP CTE and thickness multivariate control. The control solution has been enhanced to utilize both pre and post CMP process metrology along with process models to suggest process recipe modifications on a run-to-run basis. Results indicate improved control of CMP process nonuniformity qualities of interest. Further, the results quantify the significant benefit of utilizing premetrology (feedforward) information in addition to traditional postmetrology (feedback) in determining control recipe advice.

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This paper describes the design and development of run-to-run control solution for an Indium Tin Oxide (ITO) deposition process. ITO deposition is an inherently complex process making it hard to simultaneously optimize the many characteristics of the ITO film such as optical transmission, resistivity, stresses in the film etc. With the run-to-run control solution, post-process measurements made after every run are used along with e mpirical process models and drift compe nsation and noise rejection techniques to suggest new equipme nt settings for the next run. Theoretical models and simulation results show that this approach gives very stable ITO characteristics. Some of the methods that improve the control algorithm are discussed and future work is explored.

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