Abstract:
A method for predicting a source of semiconductor part deviation is disclosed. The method includes the steps of selecting at least one chart including part parameters and associating with each of the part parameters at least one fabrication process, which are stored in recipes, scanning the selected charts for deviations in the part parameters, wherein the deviations are determined by monitoring a trend of recent values of the part parameters, indicating the charts containing the part parameters wherein the part parameter values are determined as being outside of at least one trend tolerance value associated with the parameter, identifying, in each of the indicated charts at least one process associated with each of the part parameter deviations outside the at least one tread tolerance value, and determining a source of the parameter deviation by correlating each of the identified at least one processes. In one aspect of the invention, the selected chart includes the relationship between part parameters and processes.

Description:
BACKGROUND OF THE INVENTION  
       [0001]     1. Field of the Invention  
         [0002]     This invention relates generally to semiconductor manufacturing, and, more particularly, to a method for predicting or determining the source of part deviations.  
         [0003]     2. Description Of The Related Art  
         [0004]     With the advances in the semiconductor industry, manufacturers have been able to continue advances in circuit miniaturization in which the density of circuits doubles every year or two. Known as “Moore&#39;s Law,” it was predicted in 1965. that the number of transistors on a computer chip would double every year or two. Although Moore&#39;s Law has maintained relevance over the year, the pathway to the success of the semiconductor industry has been one that is forged through hard work and advances in research.  
         [0005]     In the manufacture of semiconductor parts, these advances have required that the processes by which the devices have been manufactured change and adapt to the sensitivities of a new generation of semiconductor devices in which manufacturing processes have become more complex and the tolerances afforded have shrunk. The net result is that as circuit density increases the margin for error, or deviation from nominal, decreases.  
         [0006]     One area of semiconductor manufacturing that has been affected by these changes is in the ability of engineers to predict or determine when minor changes in the manufacturing process will result in deviations in the parts that will render the parts defective and unusable. Today, engineers accomplish many of these tasks that direct the manufacturing or fabrication of partS in a combination of steps and materials that are referred to as recipes. However, the engineers do not necessarily coordinate all of their tasks as the tasks may be handled independently and in many instances manually. Thus, there is no standard procedure to determine when a deviation in the fabrication of the part will cause a part to be considered defective and unusable. There is also no adequate way to determine or predict which process or processes caused the deviation to occur. Presently, the task of determining part deviations resides in the largely manual process of checking part recipes and production reports, referred to as statistical process control (SPC) charts, to determine the cause of the part deviation. Thus, there is a need for a method to predict the source of part deviations.  
       SUMMARY OF THE INVENTION  
       [0007]     A method for predicting a source of semiconductor part deviation is disclosed. The method includes the steps of selecting at least one chart including part parameters and associating with each of the part parameters at least one fabrication process, which are stored in recipes, scanning the selected charts for deviations in the parts parameters wherein the deviations are determined by monitoring a trend of recent values of the part parameters, indicating the charts containing the part parameters wherein the part parameter values are determined as being outside of at least one trend tolerance value associated with the parameter, identifying, in each of the indicated charts at least one process associated with each of the part parameter deviations outside the at least one tread tolerance value, and determining a source of the parameter deviation by correlating each of the identified at least one processes. In one aspect of the invention, the selected chart includes the relationship between part parameters and processes. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0008]     Other aspects, advantages and novel features of the invention will become more apparent from the following detailed description of the invention when considered in conjunction with the accompanying drawings wherein:  
         [0009]      FIG. 1  is a block diagram of a process flow for predicting part deviations in accordance with the principles of the invention;  
         [0010]      FIG. 2  is a chart representative of the relationship between part characteristics and processes;  
         [0011]      FIG. 3  illustrates a flowchart for determining part deviation;  
         [0012]      FIG. 4  illustrates a flowchart for reviewing manufacturing operations;  
         [0013]      FIG. 5  illustrates a flowchart for identifying manufacturing process and part deviation; and  
         [0014]      FIG. 6  illustrates a flow chart for evaluating results of manufacturing processes in accordance with the principles of the present invention. 
     
    
       [0015]     It is to be understood that these drawings are solely for purposes of illustrating the concepts of the invention and are not intended as a definition of the limits of the invention. The embodiments shown in  FIGS. 1-6  and described in the accompanying detailed description are to be used as illustrative embodiments and should not be construed as the only manner of practicing the invention. Also, the same reference numerals, possibly supplemented with reference characters where appropriate, have been used to identify similar elements.  
       DETAILED DESCRIPTION  
       [0016]      FIG. 1  illustrates a process  100  incorporating a set of procedures that enables a user to predict the source of deviation of parts by checking the part recipes and SPC charts. The method unifies the way in which users can monitor and track production parameters in a way that allows for automated monitoring.  
         [0017]     At block  110 , a user selects one or more charts from a plurality of charts to be examined. At block  120 , a user defines a number of chart parameters and associated known tolerance values. Conventionally, these tolerance values are determined from previous experience of prior production processes of the same or substantially similar parts. At block  130 , a user defines the selected chart&#39;s recipes. At block  140 , a user defines the project steps in which the selected charts, selected recipes and selected parameters are combined for use in a production run. The relation between chart, recipe and parameter may also be amended to meet desired user or customer criteria. At block  150 , the production process is monitored with regard to the selected charts and parameters. At block  160 , a user may review selected chart parameters with regard to the production process. At block  170 , a user may review the number and type of part deviations and associated process steps that contribute to the part deviation in order to identify the source of the part deviation. At block  180 , a user is able to review the process recipes. And, at block  190 , a user is able to confirm the results of the manufacturing process.  
         [0018]     It will be recognized by those skilled in the art that the processing shown in blocks  110 - 150  may be performed before each step in the manufacture of a specific product or product lot. In another aspect of the invention, the operations of block  110 - 140  may be predetermined and repeated between different product runs or product lot runs. Hence, a database of chart, parameter and recipe definitions may be developed and relied upon for future production runs. The operations of blocks  150 - 190  are representative of tasks performed by a monitoring system based upon the inputs provided by blocks  110 - 140 . Thus, future production runs may, for example, begin from block  150  or may only require some of the steps described in steps  110 - 140 .  
         [0019]     A more detailed explanation of each of the process steps is set forth as follows. At block  110 , a user or engineer defines one or more charts that need to be monitored. A list of charts is provided or made available from which engineers may select one or more desired charts associated with the current production run for the desired part. The charts may be pre-determined and stored in a Manufacturing Execution System (MES). MES programs are well known in the art. For example, PROMIS is a commercial software MES program that combines planning, costing, document control, SPC, production and performance management in one comprehensive package. PROMIS is a registered trademark of Brooks Automation, Inc., Chelmsford, Mass., 01824  
         [0020]     From the provided list of charts, a user may select one or more charts suitable for the current operation or production run. The selected charts are referred to hereinafter as the monitored charts. The monitored charts may then be stored in a database for subsequent operation. The database may be a commercial database, such as ORACLE, or a self-developed or home-grown database. In a preferred embodiment, a commercial database is selected.  
         [0021]     At block  120 , the user is provided with a list of production parameters to select part parameters that relate to the “monitored charts.” Parameters may be selected from, but not limited to, the group consisting of thickness, uniformity of thickness, sputter rate, uniformity of sputter rate, deposition/sputter (D/S), uniformity of D/S, Refractive Index (RI), and stress. The user may pick or select one or more of these part parameters for each selected chart. Following the selection of the part parameters, the part parameters are stored in relation to the monitored chart for which they were selected.  
         [0022]     At block  130 , the user may select recipes associated with each monitored chart for fabricating the part or parts. The user may be provided with a list of known fabrication recipes for review. The user may select one or more of the recipes for each monitored chart. It will be appreciated that more complex parts may require a greater combination of recipes. Once the recipes have been selected they are stored in the database.  
         [0023]     Recipes are preferably stored in one or more databases, conventionally referred to as recipe databases. In some aspects, recipe databases may be commercial software databases that include information that is proprietary to the manufacturer or foundry. It will be appreciated by those skilled in the art that any recipe database may be easily adapted for use with the presently described invention. Recipes associated with methods for fabrication of integrated circuits are known in the art. In some cases, the recipes may be held as trade secrets that provide a commercial advantage to the owner of the recipe. Details of individual recipes are not discussed further herein as individual recipes are not relevant to the invention disclosed.  
         [0024]     At block  140 , a user may define the recipe&#39;s steps and parts parameters as they relate to each of the monitored charts. Thus the user may tailor the production process for the part or parts to be made. As each recipe may contribute some element of the process step, one skilled in the art would appreciate that a processing step may require one or more recipes to complete the desired process step.  
         [0025]     At block  150 , the user defines the monitoring criteria for each of the monitored charts. In this case, the user is provided with a list of predetermined rules from which monitoring parts parameters may be checked and validated. The rules may be determined in part on the tolerance values desired, other parameters of the part and the history of generating the desired part.  
         [0026]      FIG. 2  illustrates an exemplary relation, similar to that used in block  150  of  FIG. 1 , between parameters and processes to determine the process or processes that may contribute to part deviation. In this exemplary parameter/process relation, parameters may be selected from a group of part parameters such as thickness  205 , uniformity of thickness  210 , sputter rate  215 , dispersion/sputter (D/S)  225 , uniformity of D/S  230 , RI  235  and stress  240 , while processes that may contribute to deviations in the parts parameters may, for example, be selected from, but not limited to, the group consisting of Oxygen (O 2 ) seal  240 , RF  245 , Ar-top  250 , O 2  nozzle  260 , O 2  top  265 , O 2  side  270 , SiH 4 -nozzle  275 , SiH 4  top  280 , SiH 4  side  285  and pressure  290 . Thus, for the exemplary relation shown, deviation of a part thickness may be caused by errors in either RF process  245 , Ar-side process  255 , SiH 4  side process  285 , or pressure  290  and combinations thereof. Similarly, deviation in part parameter D/S  225  may be caused by errors in one or more of Ar-side process  255 , SiH 4 -side  285  and/or pressure  290 .  
         [0027]      FIG. 3  illustrates a flow chart for an exemplary process  300  for reviewing chart parameters identified in block  160  of  FIG. 1 . In the illustrative process  300 , the selected monitored charts are retrieved at block  305 . At block  310 , criteria associated with the selected monitored charts are obtained. At block  315 , one of the monitored charts is selected. At block  320 , a recent value associated with the parameters of the selected chart is obtained. At block  325 , the criteria, i.e., trend tolerance values, associated with the parameters in the selected chart are obtained. In this illustrated case, three trend tolerance values are selected. At block  330 , a determination is made whether the recent value of the parameter is within the first of the associated trend tolerance values. If the answer is in the affirmative, then processing continues at block  345 .  
         [0028]     However, if the answer is negative, then a determination is made whether the recent value is within the second of the associated trend tolerance values. If the answer is in the affirmative, then processing continues at block  345 .  
         [0029]     However, if the answer is negative, then a determination is made whether the recent parameter value is within the third of the associated trend tolerance values. If the answer is in the affirmative, then processing continues at block  345 . However, if the answer is in the negative, then the selected chart is marked to preclude its subsequent use.  
         [0030]     At block  345  the selected chart is included in a list of charts wherein the monitored parameters are within at least one tolerance value. In a preferred embodiment, the trend tolerance values are selected to be 3, 5 and 10 units of a measure of the part parameter tested. In this preferred embodiment, the trend of the deviation is compared to the tolerances established.  
         [0031]      FIG. 4  illustrates a flow chart for an exemplary process  400  for selecting charts marked at block  345  of  FIG. 3 . In this exemplary process  400 , a list of checked charts is displayed at block  410 . At block  420 , one of the displayed charts is selected. At block  430 , the parameters associated with the selected chart are obtained. As previously discussed, the parameters associated with a chart are stored in a database.  
         [0032]      FIG. 5  illustrates a flow chart of a process  500  for associating parameters with processes contributing to part deviation in accordance with the principles of the invention. In this exemplary process, at block  505  a determination is made whether the tolerances associated with the thickness parameters have been exceeded. If the answer is in the affirmative, then the processes associated with thickness parameters are marked at block  510 . At block  515  a determination is made whether the tolerance associated with the uniformity of thickness parameters has been exceeded. If the answer is in the affirmative, then the processes associated with uniformity of thickness parameters are marked at block  520 . At block  525  a determination is made whether the tolerance associated with the sputter rate parameters has been exceeded. If the answer is in the affirmative, then the processes associated with sputter rate parameters are marked at block  530 . At block  535  a determination is made whether the tolerance associated with the uniformity of sputter rate parameters has been exceeded. If the answer is in the affirmative, then the processes associated with uniformity of sputter rate parameters are marked at block  540 . At block  545  a determination is made whether the tolerance associated with the D/S parameters have been exceeded. If the answer is in the affirmative, then the processes associated with D/S parameters are marked at block  550 . At block  555  a determination is made whether the tolerance associated with the uniformity of D/S parameters has been exceeded. If the answer is in the affirmative, then the processes associated with uniformity of D/S parameters are marked at block  560 . At block  565  a determination is made whether the tolerance associated with the RI parameters has been exceeded. If the answer is in the affirmative, then the processes associated with RI parameters are marked at block  570 . At block  575  a determination is made whether the tolerance associated with the stress parameters has been exceeded. If the answer is in the affirmative, then the processes associated with stress parameters are marked at block  580 . At block  585 , a display of each of the marked processes is made available to the user. In one aspect of the invention the display may include a histogram of processes to determine the process common to the deviation part.  
         [0033]     Although  FIG. 5  illustrates a process wherein each of the exemplary part parameters is tested for deviations, it would be well within the skill of those in the art to develop a similar process using fewer or more part parameter tests or to devise means not to perform certain tests when a particular parameter is not selected. Such aspects of the invention, although not shown, are contemplated to be within the scope of the invention.  
         [0034]      FIG. 6  illustrates a flow chart of a process  600  for reviewing the processes associated with reviewing and predicting deviation parts, as shown at block  170  of  FIG. 1 . In this exemplary process, recipes associated with the selected chart are obtained at block  610 . At block  620 , versions of the selected recipes are obtained. At block  630  the steps and processes associated with each of the retrieved recipes are obtained. At block  640 , the steps and processes of the retrieved recipes are compared for differences. At block  650 , the results of the comparison are made available to the user.  
         [0035]     Although the invention has been described in terms of exemplary embodiments, it is not limited thereto. For example, although the present invention has been described with regard to a fixed number of parameters, it would be recognized by those skilled the art that the invention may be applied to less than or more than the parameters discussed herein. Similarly, the present invention may be used with one or more of the trend rules discussed herein.  
         [0036]     Accordingly, the appended claims should be construed broadly, to include other variants and embodiments of the invention, which may be made by those skilled in the art without departing from the scope and range of equivalents of the invention.