Subject Matter Eligible: Yes
1. A computer implemented method for supply chain data analysis, the method comprising: storing supply chain data including test data, genealogy data, repair data, a plurality of factors and a plurality of items, in one or more databases;
integrating, by one or more computers, the stored supply chain data in a plurality of combinations, each combination including one or more items and five or more factors, wherein each factor comprises one of the group consisting of product, product category, product version, test, subtest, measurement, station, station type, operator, assembly line, site, building, software version, hardware version, component, join, board version, fail category, error message, component parent, component supplier, component child, fail code, defect code, repair type, component, location of a component on a product, part number, lot name, lot size, customer, site, product, call reason, operator, defect code, severity, and failed component;
receiving a minimum failure rate and sample size;
extracting, by the one or more computers, a portion of the plurality of combinations according to received minimum failure rate and sample size, by analyzing factor properties from the stored data, integrating a portion of the factor properties to find different combinations of factors, retrieving subtest data and matching the subset data with the different combinations, retrieving measurement data and matching the measurement data with the combinations, and determining test structure and test limits;
analyzing said extracted portion of the plurality of combinations, by the one or more computers, to detect a plurality of faulty combinations of factors and items that results in an unexpected change in a key performance index, according to said extracted portion of the plurality of combinations;
performing correlation analysis on said plurality of faulty combinations, by the one or more computers, to determine a root cause for each faulty combination;
generating, by the one or more computers, a subset of said plurality of faulty combinations, according to said root causes of said plurality of faulty combinations;
generating a root cause chart, by the one or more computers and according to the generated subset of said plurality of faulty combinations, that illustrates at least one parameter value that is a cause of the unexpected change in a key performance index; and
displaying or storing the root cause chart by the one or more computers.
Applying the first step of the methodology delineated in Alice Corp. Pty. Ltd. v. CLS Bank International, 134 S. Ct. 2347, 2355 (2014), the rejection states that the claims at issue are directed to an abstract idea- “a process for supply chain data analysis, including storing supply chain data, integrating the stored supply chain data in a plurality of combination[ s ], extracting a portion of the plurality of combinations, analyzing the extracted portion o[f] the plurality of combinations.” Final Action 5. According to the rejection, the abstract idea further includes the recited details of “receiving a minimum failure rate and a sample size, performing correlation analysis on the plurality of faulty combinations, and generating a subset of plurality of faulty combinations.” Id. at 5—6. Further, the identified concept is an abstract idea, because it “can be performed mentally or in a computer” and because it is the type of method for organizing human activity that courts have regarded as an abstract idea. Id. at 5. See also Answer 6-7.
The Examiner’s Answer states that “[ t ]he claims require the additional limitations of one or more computers and one or more databases,” which are characterized as “generic computer components” that “are claimed to perform their basic functions of supply chain data analysis.” Answer 7. “In other words,” the Answer explains, “the claims recite the additional limitations of using one or more computers to store, integrate, receive, extract, analyze, peiform, generate, and display data.” Answer 8. Yet, although the Examiner’s analysis appears to consider these referenced functions individually, there is no indication that the claimed elements have been considered sufficiently as an “ordered combination” under the second part of the Alice framework. See Alice, 134 S. Ct at 2355 (“[W]e consider the elements of each claim both individually and ‘as an ordered combination’ to determine whether the additional elements ‘transform the nature of the claim’ into a patent-eligible application.”) (quoting Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1298, 1297 (2012)). Critically, notwithstanding that the Examiner references the identified individual claim elements, “[ t ]he inventive concept inquiry requires more than recognizing that each claim element, by itself, was known in the art,” because an “inventive concept” that satisfies the second Alice step “can be found in the non-conventional and non-generic arrangement of known, conventional pieces.” BASCOM Global Internet Servs., Inc. v. AT&T Mobility LLC, 827 F.3d 1341, 1350 (Fed. Cir. 2016).