# US 2020/0401052 A1 · Method for evaluating control strategies in a semiconductor manufacturing process > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401052 A1 - Document ID: US20200401052A1 - Status: Published application - Kind: A1 - Application number: 16/979,056 - Filed: 2019-02-13 - Published: 2020-12-24 - Earliest claimed: 2018-03-29 - Assignees: ASML Netherlands B.V. - Applicants: Asml Netherlands B.V. - Inventors: Ivo Matteo Leonardus WEIJDEN; Jeroen VAN DONGEN; Cornelis Johannes Henricus LAMBREGTS; Theo Wilhelmus Maria THIJSSEN; Ruud Rudolphus Johannes Catharinus DE WIT; Hans Marinus STRUIJS; Erik Mathijs Maria CROMBAG; Roy WERKMAN; Maria Helena SCHUT; Erwin RIEMENS; Menno MEELDIJK - Web page: https://patentgrep.com/patent/US20200401052A1 ## CPC - G03F 7/70491: {Information management, e.g. software; Active and passive control, e.g. details of controlling exposure processes or exposure tool monitoring processes} - G03F 7/70525: {Controlling normal operating mode, e.g. matching different apparatus, remote control or prediction of failure} - G01N 21/9501: {Semiconductor wafers (manufacturing processes per se of semiconductor devices implementing a measuring step H10P74/20)} - G03F 7/70616: {Monitoring the printed patterns} - G03F 9/7092: {Signal processing} - H10P 74/203: {Structural properties, e.g. testing or measuring thicknesses, line widths, warpage, bond strengths or physical defects} - H10P 74/23: {characterised by multiple measurements, corrections, marking or sorting processes} - G03F: PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR; (phototypographic composing devices B41B; photosensitive materials or processes for photographic purposes G03C; electrophotography, sensitive layers or processes therefor G03G) - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - H10P: GENERIC PROCESSES OR APPARATUS FOR THE MANUFACTURE OR TREATMENT OF DEVICES COVERED BY CLASS H10 ## Abstract A method for determining a preferred control strategy relating to control of a manufacturing process for manufacturing an integrated circuit. The method includes: obtaining process data associated with a design of said integrated circuit; and obtaining a plurality of candidate control strategies configured to control the manufacturing process based on the process data, each candidate control strategy including an associated cost metric based on an associated requirement to implement the candidate control strategy. A quality metric related to an expected performance of the manufacturing process is determined for each candidate control strategies, and a preferred control strategy is selected based on the determined quality metrics and associated cost metrics for each candidate control strategy. ## Claims ### Claim 1 A method for determining a preferred control strategy relating to control of a manufacturing process for manufacturing an integrated circuit, the method comprising: obtaining process data associated with a layout of the integrated circuit and/or with a process window associated with a feature comprised within the integrated circuit; obtaining a plurality of candidate control strategies configured to control the manufacturing process based on the process data and on cost metric data, the cost metric data comprising associated cost metrics for the candidate control strategies; determining quality metric data comprising a quality metric related to an expected performance of the manufacturing process for each candidate control strategy; and selecting a preferred control strategy, by a hardware computer system, based on the determined quality metric data and associated cost metric data for each candidate control strategy. ### Claim 2 (depends on 1) The method as claimed in claim 1, wherein the cost metric data comprises an associated cost metric for each candidate control strategy which is based on an associated requirement to implement the candidate control strategy. ### Claim 3 (depends on 2) The method as claimed in claim 2, wherein the associated cost metric for each candidate control strategy is related to a metrology requirement indicative of a required metrology effort to implement each candidate control strategy and/or a cost of one or more components required to implement the candidate control strategy. ### Claim 4 (depends on 3) The method as claimed in claim 3, wherein the required metrology effort is determined as a function of one or more selected from: a required metrology sampling scheme, a required metrology type and/or an estimated required metrology time. ### Claim 5 (depends on 3) The method as claimed in claim 3, comprising setting a priority to maximizing quality or minimizing metrology effort and the priority is used in the selection of a preferred control strategy. ### Claim 6 (depends on 1) The method as claimed in claim 1, wherein the cost of one or more components required to implement the candidate control strategy relates to a licensing, purchasing, running and/or implementation financial cost of the one or more components. ### Claim 7 (canceled) ### Claim 8 (depends on 1) The method as claimed in claim 1, wherein the selecting is based on an evaluation step evaluating each of the candidate control strategies based on the determined quality metrics and the cost metric data for each candidate control strategy. ### Claim 9 (depends on 8) The method according to claim 8, wherein the determining a quality metric and the evaluation step is implemented using an artificial intelligence network. ### Claim 10 (depends on 9) The method according to claim 9, further comprising training the artificial intelligence network using training data comprising at least process data and quality metric data. ### Claim 11 (depends on 9) The method according to claim 9, wherein the artificial intelligence network outputs the candidate control strategies, and the evaluation step further comprises evaluating the effect of each of the candidate control strategies on the quality metric. ### Claim 12 (depends on 8) The method as claimed in claim 8, wherein the evaluating is based on a consideration of variation of the quality metric against the cost metric for each candidate control strategy. ### Claim 13 (depends on 12) The method as claimed in claim 12, further comprising outputting the variation of the quality metric against the cost metric for at the preferred candidate control strategy. ### Claim 14 (depends on 8) The method as claimed in claim 8, further comprising: enabling: amendment or removal of one more of the candidate control strategies, inclusion of one more additional candidate control strategies, and/or amendment of one or more models for determining the quality metric data; and repeating the evaluation step. ### Claim 15 (canceled) ### Claim 16 (depends on 3) The method as claimed in claim 3, wherein each cost metric is calculated based on a cost function having one or both of the following arguments: the metrology requirement and/or the cost of one or more components. ### Claim 17 (depends on 10) The method as claimed in claim 10, further comprising validating the preferred control strategy using validation data, the validation data being greater in volume than the training data. ### Claim 18 (depends on 13) The method as claimed in claim 13, wherein the output is presented graphically. ### Claim 19 (depends on 13) The method as claimed in claim 13, wherein the output also comprises required components to implement each candidate control strategy. ### Claim 20 (depends on 1) The method as claimed in claim 1, wherein the determining a quality metric is further based on characteristics of individual control mechanisms utilized within each candidate control strategy. ### Claim 21 (depends on 1) The method as claimed in claim 1, wherein the process data further comprises process specification metrics which define process bounds and/or define target values for one or more parameters of the manufacturing process. ### Claim 22 (depends on 21) The method as claimed in claim 21, wherein the process specification metrics are defined per functional area for at least a subset of the one or more parameters of the manufacturing process. ### Claim 23 (depends on 1) The method as claimed in claim 1, wherein the quality metric comprises a measure of maximal yield. ### Claim 24 A computer program product comprising program instructions therein, the instructions, upon execution by a computer system, configured to cause the computer system to at least: obtain process data associated with a layout of an integrated circuit and/or with a process window associated with a feature comprised within the integrated circuit; obtain a plurality of candidate control strategies configured to control a manufacturing process for manufacturing the integrated circuit based on the process data and on cost metric data, the cost metric data comprising associated cost metrics for the candidate control strategies; determine quality metric data comprising a quality metric related to an expected performance of the manufacturing process for each candidate control strategy; and select a preferred control strategy based on the determined quality metric data and associated cost metric data for each candidate control strategy.