Inotera Memories, Inc.

Wei Jun Chen

Yun-Zong Tian

Chun Chi Chen

Yi Feng Lee

Cheng-Hao Chen

Yij Chieh Chu

Tsung-Wei Lin

Shih Chang Kao

Shih-Chang Kao

A specification establishing method for controlling semiconductor process, the steps includes: sampling a plurality of sample groups from a population, each sample group being a non-normal distribution; filtering the sample groups; summarizing the filtered sample groups to form a non-normal distribution diagram; getting a value-at-risk and a median by calculating from the non-normal distribution diagram; getting a critical value by calculating the value-at-risk and the median with a critical formula; getting a plurality of state values by calculating the filtered sample groups with a proportion formula; and getting an index value by calculating the non-normal distribution diagram with the proportion formula. Thus, the state values indicate the states of the sample groups are abnormal or not by comparing the state values to the index value.

Specification establishing method for controlling semiconductor process

A method of adjusting wafer process sequence includes steps of collecting production parameters for a plurality of lots; selecting a plurality of key parameters from the production parameters, wherein the key parameters at least includes a processing sequence; defining a formula to obtain an epsilon value; categorizing the lots into groups according to the epsilon value and the minimum point number by using density-based spatial clustering of application with noise (DBSCAN); and adjusting the processing sequences of the lots in the groups. Thereby, the lots with the same process recipe can be continuously or simultaneously sent into a machine, thereby reducing replacement of process recipes or shortening machine idle time.

Method of adjusting wafer processing sequence

A method for evaluating efficacy of prevention maintenance for a tool includes the steps of: choosing a tool which has been maintained preventively and choosing a productive parameter of the tool; collecting values of the productive parameter generated from the tool during a time range for building a varying curve of the productive parameter versus time, modifying the varying curve with a moving average method; transforming the varying curve into a Cumulative Sum chart; and judging whether the values of the productive parameter generated from the tool after the prevention maintenance are more stable, compared with the values of the productive parameter generated from the tool before the prevention maintenance, according to the Cumulative Sum chart. Thereby, if the varying of the values of the productive parameter after the prevention maintenance isn't stable, then the efficacy of this prevention maintenance for the tool is judged not good.

Method for evaluating efficacy of prevention maintenance for a tool

A method for planning a semiconductor manufacturing process based on users' demands includes the steps of: establishing a genetic algorithm model and inputting data; establishing a fuzzy system and setting one output parameter representing percent difference of each cost function in neighbor generations; setting to have a modulation parameter corresponding to each input parameter for adjusting fuzzy sets of the output parameter; executing genetic algorithm actions; executing fuzzy inference actions; eliminating chromosomes that produce output parameter smaller than a defined lower limit, and the remaining chromosomes that produces the largest output parameter is defined as the optimum chromosome, wherein the genetic algorithm actions stops being executed upon the optimum chromosome; then determining whether or not a defined number of generations has been reached, if yes, executing the optimum chromosome of the last generation; if no, continuing executing the genetic algorithm actions, thereby finding the optimum semiconductor manufacturing process for users.

Method for planning a semiconductor manufacturing process based on users' demands using a fuzzy system and a genetic algorithm model

A method for finding the correlation between tool PM (prevention maintenance) and the product yield of the tool is disclosed. The method uses a moving average method to magnify a curve trend that is formed by the product yield data that is captured during a predetermined days before PM and after PM. The magnified curve trend is shown by a Cumulative sum chart. The Cumulative sum chart is analyzed for informing related workers of the effect between the tool PM and the product yield, so as to accurately estimate PM timing. Thereby, via the method, the effect between the tool PM and the product yield may be determined, which serves as an important reference for workers to execute further PM.

Method for finding the correlation between the tool PM and the product yield

A method for monitoring fabrication parameters comprises steps of: obtaining a normal parameter variance curve and a comparing parameter variance curve; defining a plurality of normal parameter points on the normal parameter variance curve; defining a plurality of comparing parameter points on the comparing parameter variance curve; finding out the corresponding comparing parameter points nearest to the normal parameter points; calculating the distances between the normal parameter points and the corresponding comparing parameter points thereof; summing up the distances so as to receive a total distance; and determining whether or not the total distance exceeds a limit. Via this arrangement, when fabrication parameter of tool is abnormal, it can be efficiently and immediately determined.

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Taichung County, Taiwan

Wei Jun Chen