Notice of Pre-AIA or AIA Status
Claims 2-20 are currently presented for Examination.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
3. The amendment filed on 10/30/2025 has been entered and considered by the examiner. By the amendment, claims 2, 13-15, 18-19 are amended and claim 20 is new. In view of amendment made, the 101 rejection and the prior art rejection is still maintained. See office action.
Applicant 101 arguments
"When determining whether a claim integrates a judicial exception, into a practical application in Step 2A Prong Two..., examiners should consider whether the judicial exception is applied with, or by use of, a particular machine. "MPEP 2106.05(b). Amended claim 2 is directed to "operating [a] coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object." The selected changed measurement sequence is tied to the coordinate measuring machine, which imposes meaningful limits on the scope of the claim. Claims 13 and 14 further define the practical application of any alleged abstract idea. Amended claim 2 amounts to significantly more than any alleged abstract idea, because it improves measurement technology. "The courts have also found that improvements in technology beyond computer functionality may demonstrate patent eligibility." MPEP 2106.05(a)(II). Claim 2 does not simply recite software to be run on a general-purpose computer and instead improves measurement techniques that are beyond general computer functionality. "Examples that the courts have indicated may be sufficient to show an improvement in existing technology include ... vi. Components or methods, such as measurement devices or techniques, that generate new data...."App. No. 1. MPEP 2106.05(a)(II). Claim 2 is directed to measurement technology and more particularly to developing a measurement sequence to control operation of a coordinate measuring machine in measuring an object. For at least the above reasons, the Applicant respectfully asserts that claim 2 is directed to statutory subject matter. Independent claims 15, 18, and 19 are directed to statutory subject matter for at least similar reasons as independent claim 2. The remaining claims are dependent and likewise are directed to statutory subject matter.
Examiner response
Examiner respectfully disagrees with the applicant arguments. The claim limits the scope to a coordinate measuring machine (CMM), but fails to limit how that machine operates in a non-conventional way. The step merely uses the CMM to 'measure' using a 'specified position and alignment'—the exact, routine function for which CMMs were designed. The machine is still performing its intended, routine function: moving a sensor to specified points and taking measurements. The novel element is the order of the points visited, not the mechanism of visiting them. The CMM technology itself is unchanged and unenhanced by the optimization step. The Supreme Court has repeatedly held that generic computer implementation or conventional physical steps do not add significantly more to an abstract idea. This is a generic instruction to apply the result of the abstract idea, not a technological improvement to the machine itself. The optimization occurs abstractly, and the machine merely executes a list of standard movements. This does not transform the CMM into a 'particular machine' for eligibility purposes, as it is performing only routine functions. "The applicant asserts that claim 2 'improves measurement technology' and generates 'new data.' However, the claims themselves do not recite any specific, non-conventional steps that achieve this. The efficiency gained by optimizing the sequence is a computational improvement in scheduling, not a fundamental improvement in the underlying measurement technique or sensor technology." "For an 'improvement' to satisfy § 101, the claim must specify a technological solution beyond generic computing. The claims here simply describe using two algorithms to arrive at an optimized list of points to visit. The data gathered is the same type of data gathered by any CMM; the only difference is the order in which it's gathered. This is a claim to an abstract result (efficiency), not a claim to an improved technical process for measurement itself." "The claims remain directed to the abstract idea of optimizing the order of operations. The combination of conventional data gathering, conventional optimization algorithms run on a computer, and conventional operation of a standard CMM does not amount to 'significantly more' than the abstract idea itself. No inventive concept transforms the claim into patent-eligible subject matter." Thus, the claim limitation “operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object" is a post-solution activity that merely applies the result of the abstract calculation (the optimized sequence) using a conventional machine in a conventional manner. It does not integrate the abstract idea into a new, non-conventional technological process or an improvement to the CMM's technology itself.
Applicant 103 arguments
Amended claim 2 recites "the first algorithm and the second algorithm are performed at least partially in parallel." The Office Action acknowledges that Georgi fails to disclose this feature, but states that this feature is taught by Yoshida specifically, in paragraph [0206]. Yoshida does include the phrase "parallel algorithms" in a single paragraph as part of a series of definitions: "For easier understanding, definitions of terms used in this specification will be described below." Yoshida, [0187]. "Parallel algorithms: model in a distributed population." Yoshida, [0206]. There is no further description of this term in Yoshida, much less any discussion of performance of algorithms in parallel. Additionally, Yoshida is completely silent regarding performing algorithms in parallel that ascertain changed measurement sequences and assessment variables, as amended claim 2 recites.
Examiner response
Examiner respectfully disagrees with the applicant arguments and still maintains the rejection under the combination of Georgi and Yoshida. The instant specification ties the first and second algorithms to the Traveling Salesperson Problem (TSP) algorithm (see instant specification [0117]) and that the Yoshida discloses the first and second algorithms and their function (ascertaining changed measurement sequences and assessment variables). Yoshida discusses "finding a sequence of a short time indicating a measurement order of the chip areas and alignment marks AM" (para 116-117). Yoshida further teaches the use of "a linear programming method, a Lin and Kernighan's approach, a K-Opt method, or a genetic algorithm" (para 116-117) to achieve this goal, thus disclosing multiple algorithms. The process of using these search techniques to find a "sequence of a short time" (the assessment variable being the "short time" or overall movement time) fulfills this limitation. The examiner's position is that the feature of performing these algorithms "at least partially in parallel" is an obvious implementation choice based on common knowledge in the relevant art and the suggestion in Yoshida. Yoshida's mention of "Parallel algorithms: model in a distributed population" (in the context of GA optimization for TSP) serves as a further confirmation that this concept is within the scope of knowledge of a POSITA in this field. (see para 181-206) A POSITA would be motivated by a desire for improved efficiency and speed (a predictable result) to implement the algorithms in parallel. Thus, the rejection for claim 2 is still maintained.
Applicant arguments
Georgi does not teach or suggest that "the relative relationship specifies a maximum admissible time interval, within which the at least two surface regions are allowed to be measured when carrying out the changed measurement sequence," as recited in claim 15 (emphasis added). Instead, Georgi teaches optimizing an overall measurement time of the measurement sequence, such that the overall measurement time is as close to a target time as possible. See, for example, paragraphs [0037] and [0038] of Georgi. Optimizing an overall measurement time of a measurement sequence is very different from specifying a maximum admissible time interval between measuring two surface regions. Additionally, Georgi does not teach or suggest that "the relative relationship specifies a relative sequence of the at least two surface regions within the changed measurement sequence," as recited in claim 15 (emphasis added). Instead, Georgi teaches measuring "linkage elements, "which are features of the object to be measured which represent a spatial relationship between two or more geometric elements on the measured object. For example, a linkage element may be the distance between the edges of the two features on the measurement object. Georgi is silent on changing a measurement sequence based on the order in which surface regions are measured. Measuring the distance between the edges of the two features is very different from specifying a relative sequence (in other words, an order) for measuring two surface regions.
Examiner response
The applicant's argument that optimizing the overall measurement time is "very different" from specifying a maximum admissible time interval or a relative sequence between two specific regions for claim 15 and 19 is unpersuasive. These specific constraints are merely routine engineering parameters used to achieve the general time optimization goal explicitly taught by Georgi. In the case of measurements in a manufacturing environment, the measurement time, i.e. the time required for recording the measurement values, plays an important role in addition to the measurement accuracy." [Georgi, para 0038] This statement strongly suggests a need to control time. A person of ordinary skill in the art, when tasked with minimizing the overall measurement time (as taught by Georgi to meet a "defined target time"), would be motivated to set specific "maximum admissible time intervals" between features that are time-sensitive (e.g., if parts cool rapidly or vibrate) to ensure the required accuracy is maintained within the time limits. This is an obvious design choice explicitly motivated by the time-critical nature described in Georgi.
The applicant argues Georgi is silent on the order of surface regions and only discusses spatial relationships of "linkage elements." This applicant argument ignores the core of Georgi's disclosure, which is "generating the measurement sequence" [0037-0038]. A "sequence" is, by definition, a particular order in which related things follow each other. Optimizing a "measurement sequence" for time, as taught by Georgi, is fundamentally about finding the most efficient order of measurements. The "relative sequence" limitation is simply a description of the resulting order inherent in any time-optimized sequence generated by Georgi's method. The reference to "linkage elements" as features representing a "spatial relationship" does not negate the fact that these elements must still be measured in a specific, time-efficient order to meet the overall target time objective. Georgi suggests changing the control commands to find the most efficient path (order) between measurement points. It would be obvious for a skilled artisan to optimize the order (relative sequence) of measuring the two surface regions to achieve the overall "performance optimization" taught by the Georgi. Thus, claim rejection for claim 15 and 19 are still maintained.
Claim Rejections - 35 USC §101
4. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
5. Claims 2-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. These claims are directed to an abstract idea without significantly more.
(Step 1) Is the claims to a process, machine, manufacture, or composition of matter?
Claims: 2-17 and 20 are directed method or process, which falls on the one of the statutory category.
Claim 18-19 is directed to device or machine, which falls on the one of the statutory category.
(Step 2A) (Prong 1) Is the claim directed to a law of nature, a natural phenomenon, or an abstract idea? (Judicially recognized exceptions)?
Claim 2 and 18 recites:
changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using a first algorithm and using a second algorithm, wherein, with each change of the measurement sequence, the first and second algorithms each ascertain a changed measurement sequence and an assessment variable; (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Also, this limitation describes the abstract concept of optimization or a set of mathematical calculations (the "first and second algorithms" and "assessment variables") to determine an optimal order of operations. This algorithmic sequencing, assessment, and selection process can be performed in the human mind, possibly with pen and paper, or using general-purpose computing. It does not require a specific, unconventional physical implementation or a change in the fundamental operation of the physical machine itself beyond simply receiving a list of steps. The parallel processing also relates to computational efficiency, a generic computer function, rather than an improvement to a specific physical machine's technology. So, it falls under the combination of mental process and mathematical concepts of abstract ideas)
selecting one of the changed measurement sequences based on the assessment variables; (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas.)
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception
In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, claim 2 and 18 recites the additional elements of obtaining a plurality of surface regions of an object to be measured by a measurement sensor with respect to a specified property is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) The additional element of “wherein, to measure a respective surface region, the measurement sensor is arranged by the coordinate measuring machine according to at least one of a specified position and a specified alignment” describes the standard, conventional operation of a CMM probe moving in a 3D coordinate system. CMMs inherently move to specified positions and alignments as part of their intended, routine use. The additional elements of the first algorithm and the second algorithm are performed at least partially in parallel is a mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); The additional element of “operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object" is a generic instruction to apply the result of the abstract calculation (the selected sequence) or is a post-solution activity that merely applies the result of the abstract calculation (the optimized sequence) using a conventional machine in a conventional manner. Simply using a conventional machine to perform tasks in a newly calculated order does not transform an abstract optimization into a patent-eligible application, especially if the machine operates conventionally during the process. The additional elements of a computer device for setting a measurement sequence for a coordinate measuring machine, the computer device comprising: a memory; and at least one processor configured to execute instructions stored in the memory in claim 18 is also the mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); Thus, a method for controlling a coordinate measuring machine is no more than generally linking to the field of use as discussed on MPEP 2106.05(h). Therefore, claims 2 and 18 are directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of obtaining a plurality of surface regions of an object to be measured by a measurement sensor with respect to a specified property is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05(d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363,115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). The additional element of “wherein, to measure a respective surface region, the measurement sensor is arranged by the coordinate measuring machine according to at least one of a specified position and a specified alignment” describes the standard, conventional operation of a CMM probe moving in a 3D coordinate system. CMMs inherently move to specified positions and alignments as part of their intended, routine use. The additional elements of the first algorithm and the second algorithm are performed at least partially in parallel is a mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); The additional element of “operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object" is a generic instruction to apply the result of the abstract calculation (the selected sequence) or is a post-solution activity that merely applies the result of the abstract calculation (the optimized sequence) using a conventional machine in a conventional manner. Simply using a conventional machine to perform tasks in a newly calculated order does not transform an abstract optimization into a patent-eligible application, especially if the machine operates conventionally during the process. The additional elements of a computer device for setting a measurement sequence for a coordinate measuring machine, the computer device comprising: a memory; and at least one processor configured to execute instructions stored in the memory in claim 18 is also the mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Thus, a method for controlling a coordinate measuring machine is no more than generally linking to the field of use as discussed on MPEP 2106.05(h). Therefore, claims 2 and 18 are directed to abstract idea.
Claim 3 further recites wherein the measurement sensor is moved relative to the object for measuring successive surface regions so as to adopt the at least one position and/or alignment assigned to the surface regions in each case. It is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05(d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363,115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 4 further recites wherein the assessment variable is ascertained based on movements of the measurement sensor that are required to reach successive surface regions. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 5 further recites wherein: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm, and a measurement sequence with an at least local optimum of the assessment variable is able to be found more quickly with the first algorithm than with the second algorithm. This limitation is analyzing information by steps people go through in their minds, or by mathematical algorithms, without more,” are “within the realm of abstract ideas. So, it falls under the combination of mental process and mathematical concepts of abstract ideas. It is using generic computer can be considered a tool to perform mathematical/mental concepts of abstract idea. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 6 further recites wherein a probability of ascertaining a measurement sequence with a further, at least locally optimal assessment variable after a measurement sequence with an at least locally optimal assessment variable has already been found is greater with the second algorithm than with the first algorithm. This limitation is analyzing information by steps people go through in their minds, or by mathematical algorithms, without more,” are “within the realm of abstract ideas. So, it falls under the combination of mental process and mathematical concepts of abstract ideas. It is using generic computer can be considered a tool to perform mathematical/mental concepts of abstract idea. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 7 further recites wherein: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm; and a probability of ascertaining a measurement sequence with a further, at least locally optimal assessment variable after a measurement sequence with an at least locally optimal assessment variable has already been found is greater with the second algorithm than with the first algorithm. This limitation is analyzing information by steps people go through in their minds, or by mathematical algorithms, without more,” are “within the realm of abstract ideas. So, it falls under the combination of mental process and mathematical concepts of abstract ideas. It is using generic computer can be considered a tool to perform mathematical/mental concepts of abstract idea. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 8 further recites wherein: the first algorithm and the second algorithm are carried out at least partially in parallel; and the first algorithm and the second algorithm are similar but proceed from different initial measurement sequences. Algorithms are fundamentally a set of step-by-step instructions to solve a particular problem or perform a task. In mathematics, they serve as a way to formalize and execute mathematical procedures, making complex calculations more manageable. A generic computer, designed for a wide range of tasks, is equipped with a Central Processing Unit (CPU) or multiple cores that execute these algorithms. Thus, this limitation is a mathematical/optimization algorithm, without more,” are “within the realm of abstract ideas where a generic computer can be considered a tool to perform mathematical concepts of abstract idea. So, it falls under the mathematical concepts of abstract ideas. Performing parallel is a mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 9 further recites wherein: the first algorithm and the second algorithm are carried out at least partially in parallel; and the algorithms differ with respect to at least one of computational speeds of the algorithms and output frequencies of intermediate results of the algorithms. Algorithms are fundamentally a set of step-by-step instructions to solve a particular problem or perform a task. In mathematics, they serve as a way to formalize and execute mathematical procedures, making complex calculations more manageable. A generic computer, designed for a wide range of tasks, is equipped with a Central Processing Unit (CPU) or multiple cores that execute these algorithms. Thus, this limitation is a mathematical/optimization algorithm, without more,” are “within the realm of abstract ideas where a generic computer can be considered a tool to perform mathematical concepts of abstract idea. So, it falls under the mathematical concepts of abstract ideas. Performing parallel is a mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 10 further recites wherein a termination criterion for at least one of the algorithms is defined by a maximum admissible number of changes in the measurement sequence without finding an at least locally optimal assessment variable. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 11 further recites wherein a maximum admissible number of variations is selected based on a number of surface regions. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 12 further recites controlling the measurement sensor using the selected measurement sequence to measure the plurality of surface regions of the object. It is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05(d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363,115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 13 further recites operating the coordinate measuring machine includes at least one of moving the measurement sensor relative to the object and moving the object relative to the measurement sensor. It is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05(d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363,115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim 14 further recites wherein operating the coordinate measuring machine includes, for each point in an order specified by the selected measurement sequence, at least one of moving the measurement sensor relative to the object and moving the object relative to the measurement sensor. It describes that the machine is following the output of the abstract calculation. It confirms that the sequence generation is "pre-solution activity" and the machine operation is "post-solution activity." physical operation (moving the sensor/object) is a result-oriented application of the abstract idea, not an integration of the idea into the fundamental technology of the CMM itself. The machine is still just moving in its standard, routine manner. It is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05(d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363,115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Regarding claim 15 and 19
(Step 2A) (Prong 1) Is the claim directed to a law of nature, a natural phenomenon, or an abstract idea? (Judicially recognized exceptions)?
Claim 15 and 19 recites:
A method for selecting a measurement sequence for a coordinate measuring machine, the method comprising:
changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using at least one algorithm, wherein, with each change of the measurement sequence, the at least one algorithm respectively ascertains a changed measurement sequence and an assessment variable; (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Also, this limitation is analyzing information by steps people go through in their minds, or by mathematical algorithms, without more,” are “within the realm of abstract ideas. So, it falls under the mental process or mathematical concepts of abstract ideas)
selecting one of the changed measurement sequences based on the assessment variables, wherein: a relative relationship of at least two surface regions of the plurality of surface regions is specified as a condition to be observed by each of the changed measurement sequences, and at least one of: the relative relationship specifies a maximum admissible time interval, within which the at least two surface regions are allowed to be measured when carrying out the changed measurement sequence, and the relative relationship specifies a relative sequence of the at least two surface regions within the changed measurement sequence. (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas.)
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception
In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, claim 15 and 19 recites the additional elements of obtaining a plurality of surface regions of an object to be measured by a measurement sensor with respect to a specified property is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) The additional element of “wherein, to measure a respective surface region, the measurement sensor is arranged by the coordinate measuring machine according to at least one of a specified position and a specified alignment” describes the standard, conventional operation of a CMM probe moving in a 3D coordinate system. CMMs inherently move to specified positions and alignments as part of their intended, routine use. The additional element of “operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object" is a generic instruction to apply the result of the abstract calculation (the selected sequence) or is a post-solution activity that merely applies the result of the abstract calculation (the optimized sequence) using a conventional machine in a conventional manner. Simply using a conventional machine to perform tasks in a newly calculated order does not transform an abstract optimization into a patent-eligible application, especially if the machine operates conventionally during the process. The additional elements of a computer device, the computer device comprising: a memory; and at least one processor configured to execute instructions stored in the memory in claim 19 is the mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); Therefore, claim 19 is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of obtaining a plurality of surface regions of an object to be measured by a measurement sensor with respect to a specified property is recited at a high level of generality (i.e., as a general means of gathering data), and amounts to mere data gathering and falls under the insignificant extra solution activity. (See MPEP 2106.05(g)) and is well-understood, routine or conventional. ((See MPEP 2106.05(d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363,115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). The additional element of “wherein, to measure a respective surface region, the measurement sensor is arranged by the coordinate measuring machine according to at least one of a specified position and a specified alignment” describes the standard, conventional operation of a CMM probe moving in a 3D coordinate system. CMMs inherently move to specified positions and alignments as part of their intended, routine use. The additional element of “operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object" is a generic instruction to apply the result of the abstract calculation (the selected sequence) or is a post-solution activity that merely applies the result of the abstract calculation (the optimized sequence) using a conventional machine in a conventional manner. Simply using a conventional machine to perform tasks in a newly calculated order does not transform an abstract optimization into a patent-eligible application, especially if the machine operates conventionally during the process. The additional elements of a computer device, the computer device comprising: a memory; and at least one processor configured to execute instructions stored in the memory in claim 19 is also the mere instruction to do it on a computer with generic computer components (MPEP 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Thus, a method for controlling a coordinate measuring machine is no more than generally linking to the field of use as discussed on MPEP 2106.05(h). Therefore, claim 2, 15 and 19 are directed to abstract idea.
Claim 16 further recites wherein the relative relationship specifies a maximum admissible time interval, within which the at least two surface regions are allowed to be measured when carrying out the measurement sequence. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 15.
Claim 17 further recites wherein the relative relationship specifies a relative sequence of the at least two surface regions within the measurement sequence. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgment that could be performed in the human mind or with the aid of pencil and paper therefore falls within the “Mental Process” grouping of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 15.
Claim 20 further recites wherein the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm. It is further defining the relationship between two algorithms (one providing a "start sequence" for the other) that falls under mathematical concepts of abstract ideas. This is a classic example of an idea that can be performed in the human mind (mentally designing efficient algorithm handoffs) or using generic computer operations. The focus functioning and efficiency of the algorithms, which are mathematical procedures themselves. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 2.
Claim Rejections - 35 USC § 103
6. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
7. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
8. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
9. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
10. Claims 2-8 and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over GEORGI et al. (PUB NO: US 20180045511 A1), hereinafter GEORGI in view of Yoshida et al .(US 20010053962 A1)
Regarding claim 2 and 18
GEORGI teaches a method for controlling a coordinate measuring machine, (see para 56-The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement) the method comprising:
GEORGI teaches a method for selecting a measurement sequence for a coordinate measuring machine, (see para 56- The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement. Furthermore, the control unit 26 takes up the measurement values of the measuring head 16 and makes them available to an evaluation unit 28 for further evaluation. In the illustrated exemplary embodiment, the evaluation unit 28 is a PC, on which configuration and evaluation software is executed, such as e.g. the CALYPSO software specified at the outset, the latter, however, having been extended by a few capabilities. The configuration and evaluation software makes it possible, on the one hand, to generate a measurement sequence for carrying out an automated measurement on a measured object according to the novel method.) the method comprising:
Regarding claim 18- A computer device for setting a measurement sequence for at least one coordinate measuring machine, (see para 56- The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement. Furthermore, the control unit 26 takes up the measurement values of the measuring head 16 and makes them available to an evaluation unit 28 for further evaluation. In the illustrated exemplary embodiment, the evaluation unit 28 is a PC, on which configuration and evaluation software is executed, such as e.g. the CALYPSO software specified at the outset, the latter, however, having been extended by a few capabilities. The configuration and evaluation software makes it possible, on the one hand, to generate a measurement sequence for carrying out an automated measurement on a measured object according to the novel method.)
the computer device comprising: a memory; and at least one processor configured to execute instructions stored in the memory, (see claim 18)
obtaining a plurality of surface regions of an object to be measured by a measurement sensor with respect to a specified property, wherein, to measure a respective surface region, (see para 54-in this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement. See para 64-FIG. 2 shows the representation 32a of the measured object 32, which has a plurality of geometric elements. By way of example, some geometric elements are designated here by the reference numerals 46, 48, 50, 52. The geometric elements 46, 48 are cylindrical holes, for example, while the geometric element 50 is an octagonal pin that projects vertically from the observation plane)
the measurement sensor is arranged by the coordinate measuring machine according to at least one of a specified position and a specified alignment;(see para 35-36 and see fig 1-the measuring head for recording the measurement values is equipped with a defined sensor arrangement which is determined depending on the defined measurement uncertainty. In this refinement, the modification of the first measurement sequence comprises a modification of the measuring head and, in particular, a modification of the respectively used sensor arrangement. In other words, this refinement comprises selecting the sensor arrangement that is used within the scope of the second measurement sequence depending on the respectively achievable measurement uncertainty as a target variable. The refinement is advantageous in that very large changes in relation to the measurement uncertainty can be obtained by varying the sensor arrangement, which is why this refinement facilitates a very fast optimization. Secondly, this refinement profits from the advantages of the novel method and the device since a quantifiable target variable for modifying the sensor arrangement is provided by way of the defined measurement uncertainty. It is particularly advantageous if, within the scope of this refinement, a probe arrangement that is optimized in relation to the measurement uncertainty is selected for a tactile sensor in a systematic manner. See para 52-54- The device 10 comprises a coordinate measuring machine 12 having a workpiece receptacle 14 (here in the form of an x-y compound table) and a measuring head 16. The measuring head 16 is arranged on a column 18 and can be moved here relative to the workpiece receptacle 14 in a vertical direction along the column 18. This axis of movement is usually referred to as the z-axis. The workpiece receptacle 14 can be moved relative to the measuring head 16 in two orthogonal directions, which are usually referred to as x- and y-axes. Overall, the measuring head 16 here can thus be moved in three orthogonal spatial directions relative to the workpiece receptacle 14 in order to carry out a measurement on a measured object (not illustrated here). The three orthogonal spatial directions x, y, z here span a machine coordinate system, which in some exemplary embodiments serves as a reference coordinate system for the measurement point coordinates. In this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement.)
changing a measurement sequence, in which to measure the plurality of surface regions, ; (see para 21-22-In a preferred refinement of the invention, the defined measurement uncertainty is ascertained (preferably computationally as a numerical value) depending on the first control commands, wherein the first measurement sequence is modified depending on the ascertained measurement accuracy. Preferably, the defined measurement uncertainty is ascertained with the aid of the Virtual CMM software tool, which was already referred to further above. In general, it is preferred if the defined measurement uncertainty is ascertained with the aid of statistical simulations, for example using the methods of a Monte Carlo simulation. In this refinement, the defined measurement uncertainty is ascertained with the aid of statistical methods, wherein the first measurement sequence with the first control commands forms the basis for determining the measurement uncertainty. Subsequently, the first measurement sequence is modified and the defined measurement uncertainty is ascertained a new on the basis of the modified measurement sequence. Advantageously, this method is carried out iteratively until the defined measurement uncertainty reaches the target value underlying the optimization. See para 73-74 and fig 6 (measurement time)- In accordance with step 90, the measurement uncertainties are now determined for all selected test features, wherein use is preferably made of the Virtual CMM software tool from PTB. Alternatively, or additionally, it is possible to ascertain a measurement time on the basis of the first control commands, in particular using a computer-based simulation that uses the evaluation and control unit 26, 28)
and
selecting one of the changed measurement sequences based on the assessment variables, (see para 20-22- The novel method and the corresponding device simplify the generation of an optimized measurement sequence on the basis of an objective target criterion. As a consequence, even less experienced users can generate an optimized measurement sequence for a specific measurement. Likewise, an experienced user can arrive at an optimized measurement sequence in a quicker and more systematic manner. Depending on the acceptable manufacturing tolerances for the measured object, the second control commands facilitate a faster measurement with sufficient measurement accuracy or a higher measurement accuracy and/or better comparability of the measurement results. The refinement is advantageous in that the optimization is effectuated on the basis of a quantifiable and reproducible target variable and on the basis of a defined starting point, namely the first control commands, this facilitating a particularly good comparability of the respective measurement results. The aforementioned object is therefore achieved completely. see para 36-In this refinement, the modification of the first measurement sequence comprises a modification of the measuring head and, in particular, a modification of the respectively used sensor arrangement. In other words, this refinement comprises selecting the sensor arrangement that is used within the scope of the second measurement sequence depending on the respectively achievable measurement uncertainty as a target variable. The refinement is advantageous in that very large changes in relation to the measurement uncertainty can be obtained by varying the sensor arrangement, which is why this refinement facilitates a very fast optimization. Secondly, this refinement profits from the advantages of the novel method and the device since a quantifiable target variable for modifying the sensor arrangement is provided by way of the defined measurement uncertainty.)
and operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object. (see para 59- The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement. Furthermore, the control unit 26 takes up the measurement values of the measuring head 16 and makes them available to an evaluation unit 28 for further evaluation see para 69- By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object. see para 75- After completion of the iteration loops 94, the modified (second) measurement sequence is complete and can be transferred to the control unit 26 via the data link 42. In accordance with step 96, the control unit 26 records the measurement values on the basis of the second control commands and subsequently makes said measurement values available to the evaluation unit 28 for evaluation purposes)
Georgi does not teach changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using a first algorithm and using a second algorithm, wherein, with each change of the measurement sequence, the first and second algorithms each ascertain a changed measurement sequence and an assessment variable and wherein the first algorithm and the second algorithm are performed at least partially in parallel.
In the related field of invention, Yoshida teaches changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using a first algorithm and using a second algorithm, wherein, with each change of the measurement sequence, the first and second algorithms each ascertain a changed measurement sequence and an assessment variable; (see para 116-117-In the main control system 6, almost at the same time as the arithmetic section 61 sends the load command of wafer W described above, the arithmetic section 61 starts finding a sequence of a short time indicating a measurement order of the chip areas and alignment marks AM given in steps ST101 and ST103 by a search technique (a linear programming method, a Lin and Kernighan's approach, a K-Opt method, or a genetic algorithm) (step ST 109). The arithmetic executed in this arithmetic section 61 will be described hereinafter. Designed center coordinates of the respective chip areas and designed coordinates of the respective alignment marks AM are preliminarily recorded in the memory 63 in the main control system 6. Next, in step ST 111, the main control system 6 moves the XY stage according to the measurement order of the alignment marks AM obtained by the genetic algorithm in the arithmetic section 61. See para 162- Linear Programming Method: Nearest Neighbor Method (NN Method) and see also para 175)
the first algorithm and the second algorithm are performed at least partially in parallel. (see para 206-Parallel algorithms: model in a distributed population)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of measured object having a plurality of geometric elements as disclosed by GEORGI to include changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using a first algorithm and using a second algorithm, wherein, with each change of the measurement sequence, the first and second algorithms each ascertain a changed measurement sequence and an assessment variable wherein at least one of: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm and the first algorithm and the second algorithm are performed at least partially in parallel as taught by Yoshida in the system of GEORGI for determining method of movement sequence and an alignment apparatus, for example, for reducing the time of alignment between a pattern of an original plate and marks on a substrate in exposure apparatus, to a designing method and apparatus of an optical system such as a projection optical system of the exposure apparatus or a lens system for camera, and to a medium in which a program for realizing the designing method is recorded using an evolutionary computation method (genetic algorithm). (See para 002, Yoshida)
Regarding claim 3
Georgi further teaches wherein the measurement sensor is moved relative to the object for measuring successive surface regions so as to adopt the at least one position and/or alignment assigned to the surface regions in each case. (See para 52-54- The device 10 comprises a coordinate measuring machine 12 having a workpiece receptacle 14 (here in the form of an x-y compound table) and a measuring head 16. The measuring head 16 is arranged on a column 18 and can be moved here relative to the workpiece receptacle 14 in a vertical direction along the column 18. This axis of movement is usually referred to as the z-axis. The workpiece receptacle 14 can be moved relative to the measuring head 16 in two orthogonal directions, which are usually referred to as x- and y-axes. Overall, the measuring head 16 here can thus be moved in three orthogonal spatial directions relative to the workpiece receptacle 14 in order to carry out a measurement on a measured object (not illustrated here). The three orthogonal spatial directions x, y, z here span a machine coordinate system, which in some exemplary embodiments serves as a reference coordinate system for the measurement point coordinates. In this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement. And see fig 6)
Regarding claim 4
Georgi further teaches wherein the assessment variable is ascertained based on movements of the measurement sensor that are required to reach successive surface regions. (See para 35-36- In a further refinement, the measuring head for recording the measurement values is equipped with a defined sensor arrangement which is determined depending on the defined measurement uncertainty. In this refinement, the modification of the first measurement sequence comprises a modification of the measuring head and, in particular, a modification of the respectively used sensor arrangement. In other words, this refinement comprises selecting the sensor arrangement that is used within the scope of the second measurement sequence depending on the respectively achievable measurement uncertainty as a target variable. The refinement is advantageous in that very large changes in relation to the measurement uncertainty can be obtained by varying the sensor arrangement, which is why this refinement facilitates a very fast optimization. Secondly, this refinement profits from the advantages of the novel method and the device since a quantifiable target variable for modifying the sensor arrangement is provided by way of the defined measurement uncertainty. It is particularly advantageous if, within the scope of this refinement, a probe arrangement that is optimized in relation to the measurement uncertainty is selected for a tactile sensor in a systematic manner. See para 52-54 and fig 2- Overall, the measuring head 16 here can thus be moved in three orthogonal spatial directions relative to the workpiece receptacle 14 in order to carry out a measurement on a measured object. In this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement. See para 73- fig 6 (measurement time) n accordance with step 90, the measurement uncertainties are now determined for all selected test features, wherein use is preferably made of the Virtual CMM software tool from PTB. Alternatively, or additionally, it is possible to ascertain a measurement time on the basis of the first control commands, in particular using a computer-based simulation that uses the evaluation and control unit 26, 28. See also fig 6)
Regarding claim 5
Georgi does not teach the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm, and a measurement sequence with an at least local optimum of the assessment variable is able to be found more quickly with the first algorithm than with the second algorithm.
However, Yoshida further teaches the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm, and a measurement sequence with an at least local optimum of the assessment variable is able to be found more quickly with the first algorithm than with the second algorithm. (see para 14-The GA also has the feature of performing a search using a population of plural solution candidates and is drawing attention as a global search technique. Further, the GA is also drawing attention as a multi-objective optimization technique for handling the plural evaluation criteria explicitly and finding a Pareto optimal solution set by a single search. see para 18- First, the determining method of movement sequence in the measurement process carried out for alignment must obtain an optimum solution or a near-optimum solution to the permutation optimization problem within a shorter computation time. As described above, in the case of the movement sequence of the stage, an ideal process is to produce all possible measurement orders (movement sequences) of alignment mark positions and to find the shortest turnaround time (the overall movement time excluding the measurement times) as an optimum solution out of these candidates generated. see para 168- 176-Eighty-one solutions were generated by the NN method and the computation time for generation of the eighty-one solutions was about 0.03 sec. The NN method is a “generating method” to generate a solution from nothing, while the k-OPT method and LK method are so-called “improving methods” for initially giving a certain initial solution (here, in the case of the “constraint satisfying problem” to require an output solution to satisfy a specific constraint, a necessary condition is that the initial solution is a feasible basic solution) and successively improving the solution. Particularly, the LK method is a method for repetitively performing such an operation as to extract a part of a tour sequence of the initial solution and to invert the partial order, thereby effecting repetitive improvements even in a solution after improved, as long as an improvement is possible. In this embodiment the LK method is applied to near-optimum solutions obtained by the NN method. The computation time was about 0.14 sec for obtaining eighty-one solutions by applying the LK method to the all eighty-one solutions resulting from the forward search of the NN method.)
Regarding claim 6
Georgi does not teach wherein a probability of ascertaining a measurement sequence with a further, at least locally optimal assessment variable after a measurement sequence with an at least locally optimal assessment variable has already been found is greater with the second algorithm than with the first algorithm.
However, Yoshida further teaches wherein a probability of ascertaining a measurement sequence with a further, at least locally optimal assessment variable after a measurement sequence with an at least locally optimal assessment variable has already been found is greater with the second algorithm than with the first algorithm. (see para 176-179-In this embodiment the LK method is applied to near-optimum solutions obtained by the NN method. The LK method generates one improved solution per initial solution. Since one improved solution is generated per initial solution, the number of initial solutions should be determined preferably as high as possible. This embodiment employs an approach method for using eighty one solutions obtained by the NN method as initial solutions and improving them. The result of this experiment showed that when the solutions by the NN method were used as initial solutions of the LK method, the best solution was the solution of the movement sequence shown in FIG. 21 and the overall movement time of-the movement sequence was 49.117 sec. For example, supposing in the optimization problem of movement sequence there are three candidates X, Y, Z as solutions of movement sequences and their movement times are 10 sec, 20 sec, and 20 sec, respectively, it is contemplated that the inverse of the time is set as a fitness value of each solution. At this time, supposing one solution is selected out of these three solutions by roulette wheel selection, probabilities of selection of the solutions X, Y, and Z are 0.5, 0.25, and 0.25, respectively.)
Regarding claim 7
Georgi does not teach wherein: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm; and probability of ascertaining a measurement sequence with a further, at least locally optimal assessment variable after a measurement sequence with an at least locally optimal assessment variable has already been found is greater with the second algorithm than with the first algorithm.
However, Yoshida further teaches wherein: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm; (see para 14-The GA also has the feature of performing a search using a population of plural solution candidates and is drawing attention as a global search technique. Further, the GA is also drawing attention as a multi-objective optimization technique for handling the plural evaluation criteria explicitly and finding a Pareto optimal solution set by a single search. see para 18- First, the determining method of movement sequence in the measurement process carried out for alignment must obtain an optimum solution or a near-optimum solution to the permutation optimization problem within a shorter computation time. As described above, in the case of the movement sequence of the stage, an ideal process is to produce all possible measurement orders (movement sequences) of alignment mark positions and to find the shortest turnaround time (the overall movement time excluding the measurement times) as an optimum solution out of these candidates generated. see para 168- Eighty one solutions were generated by the NN method and the computation time for generation of the eighty one solutions was about 0.03 sec. see para 176- The computation time was about 0.14 sec for obtaining eighty one solutions by applying the LK method to the all eighty one solutions resulting from the forward search of the NN method.)
and a probability of ascertaining a measurement sequence with a further, at least locally optimal assessment variable after a measurement sequence with an at least locally optimal assessment variable has already been found is greater with the second algorithm than with the first algorithm. (see para 176-179-In this embodiment the LK method is applied to near-optimum solutions obtained by the NN method. The LK method generates one improved solution per initial solution. Since one improved solution is generated per initial solution, the number of initial solutions should be determined preferably as high as possible. This embodiment employs an approach method for using eighty one solutions obtained by the NN method as initial solutions and improving them. The result of this experiment showed that when the solutions by the NN method were used as initial solutions of the LK method, the best solution was the solution of the movement sequence shown in FIG. 21 and the overall movement time of-the movement sequence was 49.117 sec. For example, supposing in the optimization problem of movement sequence168 there are three candidates X, Y, Z as solutions of movement sequences and their movement times are 10 sec, 20 sec, and 20 sec, respectively, it is contemplated that the inverse of the time is set as a fitness value of each solution. At this time, supposing one solution is selected out of these three solutions by roulette wheel selection, probabilities of selection of the solutions X, Y, and Z are 0.5, 0.25, and 0.25, respectively)
Regarding claim 8
Georgi does not teach the first algorithm and the second algorithm are carried out at least partially in parallel; and the first algorithm and the second algorithm are similar but proceed from different initial measurement sequences.
However, Yoshida further teaches the first algorithm and the second algorithm are carried out at least partially in parallel; and the first algorithm and the second algorithm are similar but proceed from different initial measurement sequences. (see para 173-The NN method is a “generating method” to generate a solution from nothing, while the k-OPT method and LK method are so-called “improving methods” for initially giving a certain initial solution (here, in the case of the “constraint satisfying problem” to require an output solution to satisfy a specific constraint, a necessary condition is that the initial solution is a feasible basic solution) and successively improving the solution. Particularly, the LK method is a method for repetitively performing such an operation as to extract a part of a tour sequence of the initial solution and to invert the partial order, thereby effecting repetitive improvements even in a solution after improved, as long as an improvement is possible. see para 206-Parallel algorithms: model in a distributed population)
Regarding claim 10
Georgi further teaches wherein a termination criterion for at least one of the algorithms is defined by a maximum admissible number of changes in the measurement sequence without finding an at least locally optimal assessment variable. (See para 22-23-In this refinement, the defined measurement uncertainty is ascertained with the aid of statistical methods, wherein the first measurement sequence with the first control commands forms the basis for determining the measurement uncertainty. Subsequently, the first measurement sequence is modified and the defined measurement uncertainty is ascertained anew on the basis of the modified measurement sequence. Advantageously, this method is carried out iteratively until the defined measurement uncertainty reaches the target value underlying the optimization. The refinement is advantageous in that the optimization is effectuated on the basis of a quantifiable and reproducible target variable and on the basis of a defined starting point, namely the first control commands, this facilitating a particularly good comparability of the respective measurement results. In a further refinement, the second control commands are therefore determined on the basis of a plurality of iteration steps. See para 74-75 and fig 6-In some exemplary embodiments, the modified (second) control commands may contain a sensor change and/or a change of the probe system. In accordance with the loop 94, the determination of the measurement uncertainties and the determination of modified control commands can be repeated iteratively. After completion of the iteration loops 94, the modified (second) measurement sequence is complete)
Regarding claim 11
Georgi further teaches wherein a maximum admissible number of variations is selected based on a number of surface regions. (See para 64-69-FIG. 2 shows the representation 32a of the measured object 32, which has a plurality of geometric elements. By way of example, some geometric elements are designated here by the reference numerals 46, 48, 50, 52. The geometric elements 46, 48 are cylindrical holes, for example, while the geometric element 50 is an octagonal pin that projects vertically from the observation plane. The geometric element 52 is for example an oval depression in the surface of the measured object, which is illustrated merely schematically and by way of example here. The operator of the device 10 can then select individual geometric elements in the manner described below in order to cause the measurement sequence 40 to be generated automatically with the aid of the evaluation unit 28. By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object. And see fig 6)
Regarding claim 12
Georgi further teaches controlling the measurement sensor using the selected measurement sequence to measure the plurality of surface regions of the object. (See para 29-This refinement facilitates a very systematic optimization of the measurement sequence in relation to the contradictory demands for a high measurement accuracy and a high measurement speed. By modifying the respective movement parameters, it is possible to quite quickly obtain an ideal compromise between the contradictory demands. See para 63-64-In the preferred exemplary embodiments, an operator can generate a defined measurement sequence 40 for measuring a measured object 32 using the image on the image display appliance and transmit it to the control unit 26, which is indicated here by a data link 42. The measurement sequence 40 represents the plurality of control commands that cause the control unit 26 to move the measuring head 16 relative to the workpiece receptacle 14 and to record individual measurement values. FIG. 2 shows the representation 32 a of the measured object 32, which has a plurality of geometric elements. By way of example, some geometric elements are designated here by the reference numerals 46, 48, 50, 52)
Regarding claim 13
Georgi further teaches wherein operating the coordinate measuring machine includes at least one of moving the measurement sensor relative to the object and moving the object relative to the measurement sensor. (see para 54-55-In this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement. In all preferred exemplary embodiments, the measuring head supplies measurement values representing the position of at least one measurement point on the measured object relative to a coordinate measuring system 24. see para 63-In the preferred exemplary embodiments, an operator can generate a defined measurement sequence 40 for measuring a measured object 32 using the image on the image display appliance and transmit it to the control unit 26, which is indicated here by a data link 42. The measurement sequence 40 represents the plurality of control commands that cause the control unit 26 to move the measuring head 16 relative to the workpiece receptacle 14 and to record individual measurement values. See also para 77)
Regarding claim 14
Georgi further teaches wherein operating the coordinate measuring machine includes, for each point in an order specified by the selected measurement sequence, at least one of moving the measurement sensor relative to the object and moving the object relative to the measurement sensor. (see para 54-55-In this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement. In all preferred exemplary embodiments, the measuring head supplies measurement values representing the position of at least one measurement point on the measured object relative to a coordinate measuring system 24. see para 63-In the preferred exemplary embodiments, an operator can generate a defined measurement sequence 40 for measuring a measured object 32 using the image on the image display appliance and transmit it to the control unit 26, which is indicated here by a data link 42. The measurement sequence 40 represents the plurality of control commands that cause the control unit 26 to move the measuring head 16 relative to the workpiece receptacle 14 and to record individual measurement values. See also para 77)
Regarding claim 15 and 19
GEORGI teaches a method for selecting a measurement sequence for a coordinate measuring machine, (see para 56- The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement. Furthermore, the control unit 26 takes up the measurement values of the measuring head 16 and makes them available to an evaluation unit 28 for further evaluation. In the illustrated exemplary embodiment, the evaluation unit 28 is a PC, on which configuration and evaluation software is executed, such as e.g. the CALYPSO software specified at the outset, the latter, however, having been extended by a few capabilities. The configuration and evaluation software makes it possible, on the one hand, to generate a measurement sequence for carrying out an automated measurement on a measured object according to the novel method.) the method comprising:
Regarding claim 19- A computer device for selecting a measurement sequence for at least one coordinate measuring machine, (see para 56- The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement. Furthermore, the control unit 26 takes up the measurement values of the measuring head 16 and makes them available to an evaluation unit 28 for further evaluation. In the illustrated exemplary embodiment, the evaluation unit 28 is a PC, on which configuration and evaluation software is executed, such as e.g. the CALYPSO software specified at the outset, the latter, however, having been extended by a few capabilities. The configuration and evaluation software makes it possible, on the one hand, to generate a measurement sequence for carrying out an automated measurement on a measured object according to the novel method.)
the computer device comprising: a memory; and at least one processor configured to execute instructions stored in the memory, (see claim 18) wherein the instructions include
obtaining a plurality of surface regions of an object to be measured by a measurement sensor with respect to a specified property, wherein, to measure a respective surface region, (see para 54-in this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement. See para 64-FIG. 2 shows the representation 32a of the measured object 32, which has a plurality of geometric elements. By way of example, some geometric elements are designated here by the reference numerals 46, 48, 50, 52. The geometric elements 46, 48 are cylindrical holes, for example, while the geometric element 50 is an octagonal pin that projects vertically from the observation plane)
the measurement sensor is arranged by the coordinate measuring machine according to at least one of a specified position and a specified alignment;(see para 35-36 and see fig 1-the measuring head for recording the measurement values is equipped with a defined sensor arrangement which is determined depending on the defined measurement uncertainty. In this refinement, the modification of the first measurement sequence comprises a modification of the measuring head and, in particular, a modification of the respectively used sensor arrangement. In other words, this refinement comprises selecting the sensor arrangement that is used within the scope of the second measurement sequence depending on the respectively achievable measurement uncertainty as a target variable. The refinement is advantageous in that very large changes in relation to the measurement uncertainty can be obtained by varying the sensor arrangement, which is why this refinement facilitates a very fast optimization. Secondly, this refinement profits from the advantages of the novel method and the device since a quantifiable target variable for modifying the sensor arrangement is provided by way of the defined measurement uncertainty. It is particularly advantageous if, within the scope of this refinement, a probe arrangement that is optimized in relation to the measurement uncertainty is selected for a tactile sensor in a systematic manner. See para 52-54- The device 10 comprises a coordinate measuring machine 12 having a workpiece receptacle 14 (here in the form of an x-y compound table) and a measuring head 16. The measuring head 16 is arranged on a column 18 and can be moved here relative to the workpiece receptacle 14 in a vertical direction along the column 18. This axis of movement is usually referred to as the z-axis. The workpiece receptacle 14 can be moved relative to the measuring head 16 in two orthogonal directions, which are usually referred to as x- and y-axes. Overall, the measuring head 16 here can thus be moved in three orthogonal spatial directions relative to the workpiece receptacle 14 in order to carry out a measurement on a measured object (not illustrated here). The three orthogonal spatial directions x, y, z here span a machine coordinate system, which in some exemplary embodiments serves as a reference coordinate system for the measurement point coordinates. In this exemplary embodiment, the measuring head 16 has an optical sensor 20, by means of which a measured object (not illustrated here) can be measured in a non-contact manner. In some exemplary embodiments, the optical sensor 20 comprises a camera and a lens in order to record an image of the measured object. Furthermore, the coordinate measuring machine 12 in this exemplary embodiment also has a tactile sensor 22 with a star-shaped arrangement of styluses, which can be used to touch measurement points on a measured object in order to carry out a measurement.)
changing a measurement sequence, in which to measure the plurality of surface regions, multiple times (see para 21-22-In a preferred refinement of the invention, the defined measurement uncertainty is ascertained (preferably computationally as a numerical value) depending on the first control commands, wherein the first measurement sequence is modified depending on the ascertained measurement accuracy. Preferably, the defined measurement uncertainty is ascertained with the aid of the Virtual CMM software tool, which was already referred to further above. In general, it is preferred if the defined measurement uncertainty is ascertained with the aid of statistical simulations, for example using the methods of a Monte Carlo simulation. In this refinement, the defined measurement uncertainty is ascertained with the aid of statistical methods, wherein the first measurement sequence with the first control commands forms the basis for determining the measurement uncertainty. Subsequently, the first measurement sequence is modified and the defined measurement uncertainty is ascertained a new on the basis of the modified measurement sequence. Advantageously, this method is carried out iteratively until the defined measurement uncertainty reaches the target value underlying the optimization. See para 73-74 and fig 6 (measurement time)- In accordance with step 90, the measurement uncertainties are now determined for all selected test features, wherein use is preferably made of the Virtual CMM software tool from PTB. Alternatively, or additionally, it is possible to ascertain a measurement time on the basis of the first control commands, in particular using a computer-based simulation that uses the evaluation and control unit 26, 28)
and
selecting one of the changed measurement sequences based on the assessment variables, (see para 20-22- The novel method and the corresponding device simplify the generation of an optimized measurement sequence on the basis of an objective target criterion. As a consequence, even less experienced users can generate an optimized measurement sequence for a specific measurement. Likewise, an experienced user can arrive at an optimized measurement sequence in a quicker and more systematic manner. Depending on the acceptable manufacturing tolerances for the measured object, the second control commands facilitate a faster measurement with sufficient measurement accuracy or a higher measurement accuracy and/or better comparability of the measurement results. The refinement is advantageous in that the optimization is effectuated on the basis of a quantifiable and reproducible target variable and on the basis of a defined starting point, namely the first control commands, this facilitating a particularly good comparability of the respective measurement results. The aforementioned object is therefore achieved completely. see para 36-In this refinement, the modification of the first measurement sequence comprises a modification of the measuring head and, in particular, a modification of the respectively used sensor arrangement. In other words, this refinement comprises selecting the sensor arrangement that is used within the scope of the second measurement sequence depending on the respectively achievable measurement uncertainty as a target variable. The refinement is advantageous in that very large changes in relation to the measurement uncertainty can be obtained by varying the sensor arrangement, which is why this refinement facilitates a very fast optimization. Secondly, this refinement profits from the advantages of the novel method and the device since a quantifiable target variable for modifying the sensor arrangement is provided by way of the defined measurement uncertainty.)
wherein: a relative relationship of at least two surface regions of the plurality of surface regions is specified as a condition to be observed by each of the changed measurement sequences, (See para 68-70- Furthermore, in the preferred exemplary embodiments the evaluation unit 28 displays suitable linkage elements for the at least two selected geometric elements. In this exemplary embodiment, one suitable linkage element is the relative distance 64 between the two selected geometric elements 46′, 48′. A further suitable linkage element here is for example the lateral offset 66 of the midpoints of the two selected geometric elements 46′, 48′. A further linkage element may be the point 68 of symmetry between the two selected geometric elements 46′, 48′. Generally, linkage elements are features of the object to be measured which represent a spatial relationship between two or more geometric elements on the measured object. In the image in FIG. 4, two geometric elements 46′, 48′ of the measured object 32 are selected and the evaluation unit 28 offers suitable test features 56, 58, 60, 62 and linkage elements 64, 66, 68 with respect to the selected geometric elements 46′, 48′. With the selection of a test feature and/or linkage element, the evaluation unit 28 adopts the selected test feature and/or linkage element into the measurement sequence 40. By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object. With the selection of a test feature and/or linkage element, the evaluation unit 28 adopts the selected test feature and/or linkage element into the measurement sequence 40. By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object. In preferred exemplary embodiments, the measurement sequence 40 is generated after the conclusion of all selection steps automatically by the evaluation unit 28 by virtue of the fact that the evaluation unit 28 determines the control commands for the control unit 26 on the basis of the selected test features and/or linkage elements.)
and at least one of: the relative relationship specifies a maximum admissible time interval, within which the at least two surface regions are allowed to be measured when carrying out the changed measurement sequence, (See para 37-38-Preferably, a first measurement time is selected on the basis of the first control commands, in particular in a computer-based simulation, and a difference between the first measurement time and a defined target time is determined. Then, the second control commands are selected in such a way that this difference is minimal. Accordingly, generating the measurement sequence taking into account a defined measurement time as an objective target criterion leads to even further optimized results. There is a performance optimization in view of target time and demanded accuracy. see para 68-70- In preferred exemplary embodiments, the measurement sequence 40 is generated after the conclusion of all selection steps automatically by the evaluation unit 28 by virtue of the fact that the evaluation unit 28 determines the control commands for the control unit 26 on the basis of the selected test features and/or linkage elements.)
the relative relationship specifies a relative sequence of the at least two surface regions within the changed measurement sequence. (See para 37-38-Preferably, a first measurement time is selected on the basis of the first control commands, in particular in a computer-based simulation, and a difference between the first measurement time and a defined target time is determined. Then, the second control commands are selected in such a way that this difference is minimal. Accordingly, generating the measurement sequence taking into account a defined measurement time as an objective target criterion leads to even further optimized results. There is a performance optimization in view of target time and demanded accuracy. See para 68-70- Generally, linkage elements are features of the object to be measured which represent a spatial relationship between two or more geometric elements on the measured object. In the image in FIG. 4, two geometric elements 46′, 48′ of the measured object 32 are selected and the evaluation unit 28 offers suitable test features 56, 58, 60, 62 and linkage elements 64, 66, 68 with respect to the selected geometric elements 46′, 48′. With the selection of a test feature and/or linkage element, the evaluation unit 28 adopts the selected test feature and/or linkage element into the measurement sequence 40. By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object.)
and operating the coordinate measuring machine using the selected one of the changed measurement sequences to measure the plurality of surface regions of the object. (see para 59- The coordinate measuring machine 12 has a control unit 26, with the aid of which the drives (not provided with a designation here) for the workpiece receptacle 14 and the measuring head 16 are driven in order to carry out a measurement. Furthermore, the control unit 26 takes up the measurement values of the measuring head 16 and makes them available to an evaluation unit 28 for further evaluation see para 69- By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object. see para 75- After completion of the iteration loops 94, the modified (second) measurement sequence is complete and can be transferred to the control unit 26 via the data link 42. In accordance with step 96, the control unit 26 records the measurement values on the basis of the second control commands and subsequently makes said measurement values available to the evaluation unit 28 for evaluation purposes)
Georgi does not teach changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using at least one algorithm, wherein, with each change of the measurement sequence, the at least one algorithm respectively ascertains a changed measurement sequence and an assessment variable;
In the related field of invention, Yoshida teaches changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using at least one algorithm, wherein, with each change of the measurement sequence, the at least one algorithm respectively ascertains a changed measurement sequence and an assessment variable; (see para 116-117-In the main control system 6, almost at the same time as the arithmetic section 61 sends the load command of wafer W described above, the arithmetic section 61 starts finding a sequence of a short time indicating a measurement order of the chip areas and alignment marks AM given in steps ST101 and ST103 by a search technique (a linear programming method, a Lin and Kernighan's approach, a K-Opt method, or a genetic algorithm) (step ST 109). The arithmetic executed in this arithmetic section 61 will be described hereinafter. Designed center coordinates of the respective chip areas and designed coordinates of the respective alignment marks AM are preliminarily recorded in the memory 63 in the main control system 6. Next, in step ST 111, the main control system 6 moves the XY stage according to the measurement order of the alignment marks AM obtained by the genetic algorithm in the arithmetic section 61. See para 162- Linear Programming Method: Nearest Neighbor Method (NN Method) and see also para 175)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of measured object having a plurality of geometric elements as disclosed by GEORGI to include changing a measurement sequence, in which to measure the plurality of surface regions, multiple times using at least one algorithm, wherein, with each change of the measurement sequence, the at least one algorithm respectively ascertains a changed measurement sequence and an assessment variable as taught by Yoshida in the system of GEORGI for determining method of movement sequence and an alignment apparatus, for example, for reducing the time of alignment between a pattern of an original plate and marks on a substrate in exposure apparatus, to a designing method and apparatus of an optical system such as a projection optical system of the exposure apparatus or a lens system for camera, and to a medium in which a program for realizing the designing method is recorded using an evolutionary computation method (genetic algorithm). (See para 002, Yoshida)
Regarding claim 16
Georgi further teaches wherein the relative relationship specifies a maximum admissible time interval, within which the at least two surface regions are allowed to be measured when carrying out the measurement sequence. (See para 37-38-Preferably, a first measurement time is selected on the basis of the first control commands, in particular in a computer-based simulation, and a difference between the first measurement time and a defined target time is determined. Then, the second control commands are selected in such a way that this difference is minimal. Accordingly, generating the measurement sequence taking into account a defined measurement time as an objective target criterion leads to even further optimized results. There is a performance optimization in view of target time and demanded accuracy.see para 68-70)
Regarding claim 17
Georgi further teaches wherein the relative relationship specifies a relative sequence of the at least two surface regions within the measurement sequence. (See para 37-38-Preferably, a first measurement time is selected on the basis of the first control commands, in particular in a computer-based simulation, and a difference between the first measurement time and a defined target time is determined. Then, the second control commands are selected in such a way that this difference is minimal. Accordingly, generating the measurement sequence taking into account a defined measurement time as an objective target criterion leads to even further optimized results. There is a performance optimization in view of target time and demanded accuracy. See para 68-70- Generally, linkage elements are features of the object to be measured which represent a spatial relationship between two or more geometric elements on the measured object. In the image in FIG. 4, two geometric elements 46′, 48′ of the measured object 32 are selected and the evaluation unit 28 offers suitable test features 56, 58, 60, 62 and linkage elements 64, 66, 68 with respect to the selected geometric elements 46′, 48′. With the selection of a test feature and/or linkage element, the evaluation unit 28 adopts the selected test feature and/or linkage element into the measurement sequence 40. By means of multiple selection, the operator can thus configure an individual measurement sequence for a measured object.)
Regarding claim 25
Georgi does not teach wherein at least one of: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm.
In the related field of invention, Yoshida teaches wherein at least one of: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm; (see para 168-176- Eighty one solutions were generated by the NN method and the computation time for generation of the eighty one solutions was about 0.03 sec The LK method is famous as a quick near-optimum obtaining method for symmetric TSP (Traveling Salesman Problem), i.e., as a technique capable of obtaining a near-optimum solution in a very short turnaround time of computation and is a technique of development of the k-OPT method, which is the general name of the 2-OPT method and the 3-OPT method. The NN method is a “generating method” to generate a solution from nothing, while the k-OPT method and LK method are so-called “improving methods” for initially giving a certain initial solution (here, in the case of the “constraint satisfying problem” to require an output solution to satisfy a specific constraint, a necessary condition is that the initial solution is a feasible basic solution) and successively improving the solution. Particularly, the LK method is a method for repetitively performing such an operation as to extract a part of a tour sequence of the initial solution and to invert the partial order, thereby effecting repetitive improvements even in a solution after improved, as long as an improvement is possible. The computation time was about 0.14 sec for obtaining eighty one solutions by applying the LK method to the all eighty one solutions resulting from the forward search of the NN method. )
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of measured object having a plurality of geometric elements as disclosed by GEORGI to include wherein at least one of: the first algorithm ascertains an initial measurement sequence as a start sequence for the second algorithm and has a higher computational speed than the second algorithm as taught by Yoshida in the system of GEORGI for determining method of movement sequence and an alignment apparatus, for example, for reducing the time of alignment between a pattern of an original plate and marks on a substrate in exposure apparatus, to a designing method and apparatus of an optical system such as a projection optical system of the exposure apparatus or a lens system for camera, and to a medium in which a program for realizing the designing method is recorded using an evolutionary computation method (genetic algorithm). (See para 002, Yoshida)
11. Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over GEORGI et al. (PUB NO: US 20180045511 A1), hereinafter GEORGI in view of Yoshida et al. (US 20010053962 A1) and further in view of Soltani et al. ("Path planning in construction sites: performance evaluation of the Dijkstra, A∗, and GA search algorithms." Advanced engineering informatics 16.4 (2002))
Regarding claim 9
Georgi does not teach wherein: the first algorithm and the second algorithm are carried out at least partially in parallel; and the algorithms differ with respect to at least one of computational speeds of the algorithms and output frequencies of intermediate results of the algorithms.
However, Yoshida further teaches wherein: the first algorithm and the second algorithm are carried out at least partially in parallel; and the algorithms differ with respect to at least one of computational speeds of the algorithms (see para 168- Eighty one solutions were generated by the NN method and the computation time for generation of the eighty one solutions was about 0.03 sec. see para 176- The computation time was about 0.14 sec for obtaining eighty one solutions by applying the LK method to the all eighty one solutions resulting from the forward search of the NN method. see para 206-Parallel algorithms: model in a distributed population)
The combination of Georgi and Yoshida does not teach the algorithms differ with respect to output frequencies of intermediate results of the algorithms.
In the related field of invention, Soltani teaches the algorithms differ with respect to output frequencies of intermediate results of the algorithms. ( see fig 5 and Table 3. Predicted execution times with the varying number of intermediate points for GA)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of measured object having a plurality of geometric elements as disclosed by GEORGI to include the algorithms differ with respect to output frequencies of intermediate results of the algorithm as taught by Soltani in the system of GEORGI and Yoshida for evaluating the performance of three optimization algorithms namely: Dijkstra, A*, and Genetic algorithms that are used to find multi-criteria paths in construction sites based on transportation and safety-related cost. During a construction project, site planners need to select paths for site operatives and vehicles, which are characterized by short distance, low risks and high visibility. (See abstract, Soltani)
Conclusion
12. All Claims 2-20 are rejected.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20200072591 A1 HAGINO et al.
Discussing a measurement point determination method for determining the number or an arrangement of measurement points for a measurement apparatus that performs measurement processing of a measurement item at a plurality of measurement points.
US 20110211066 A1 Fujiki
ii. Discussing a technique for measuring the position and orientation of an object whose three-dimensional shape is given and, more particularly, to a position and orientation measurement apparatus which calculates the position and orientation of a target object based on a range image obtained by capturing an image of the target object, a position and orientation measurement method, and a storage medium.
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/PURSOTTAM GIRI/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
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