# US 12,118,491 B2 · Rapid operational analysis application for supply chain management > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,118,491 B2 - Document ID: US12118491B2 - Status: Granted - Kind: B2 - Application number: 17/636,102 - Filed: 2020-09-11 - Published: 2022-11-10 - Granted: 2024-10-15 - Earliest claimed: 2019-09-13 - Assignees: Throughput, Inc. - Applicants: ThroughPut, Inc. - Inventors: Ali Hussan Raza; Bhaskar Subbarao Ballapragada; Seth Rom Page; Anzar Kamdar - Web page: https://patentgrep.com/patent/US12118491B2 ## CPC - G06Q 10/0633: Workflow analysis - G06Q 50/04: Manufacturing - G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) - G06Q 10/06312: {Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling} - G06Q 10/06313: {Resource planning in a project environment} - G06Q 10/06334: {using forecasting or predicting} - Y02P 90/30: Computing systems specially adapted for manufacturing - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - Y02P: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS ## Abstract An improved industrial process includes: receiving in a processor a plurality of data items related to an industrial process, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time; analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable; setting a statistical control parameter as an achievable quantity for the at least one variable; identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define at least one excess; and eliminating the at least one excess by shifting resources or altering the process related to the at least one quantity, the shifting or altering being a function of the analyzing of the plurality of data items. Methods related to achievable opportunities for improvement and to identifying contributing factors are also provided. ## Claims ### Claim 1 An improved industrial process comprising: receiving in a processor a plurality of data items related to an industrial process, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time; analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable, the at least one variable representing manufactured parts having defects, the analyzing including identifying duplicates, null values, negative values and/or outliers; setting a statistical control parameter as an achievable quantity for the at least one variable; identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define at least one excess of defective manufactured parts; and eliminating the at least one excess of defective manufactured parts by shifting resources for manufacturing the parts related to the at least one quantity, the shifting being a function of the analyzing of the plurality of data items. ### Claim 2 (depends on 1) The improved industrial process as recited in claim 1 wherein the at least one variable is a number of defects within a time period. ### Claim 3 (depends on 1) The improved industrial process as recited in claim 1 wherein the statistical control parameter is based on standard deviations from the mean value. ### Claim 4 (depends on 1) The improved industrial process as recited in claim 1 is a function of past performance of the industrial process. ### Claim 5 (depends on 1) The improved industrial process as recited in claim 1 the statistical control parameter is dynamic. ### Claim 6 (depends on 1) The improved industrial process as recited in claim 1 the excess is supplied as a number of defects or other industrial process negative issue. ### Claim 7 (depends on 1) The improved industrial process as recited in claim 1 the excess is supplied as a cost. ### Claim 8 (depends on 1) The improved industrial process as recited in claim 1 wherein due to the shifting, the at least one variable related to a time period decreases, and the at least one variable related to a further time period increases, the at least one variable related to the time period and the at least one variable related to the further time period both remaining under the statistical control parameter. ### Claim 9 (depends on 8) The improved industrial process as recited in claim 8 wherein the shifting is a function of a second statistical control parameter, the at least one variable being less than the second statistical control parameter before the shifting. ### Claim 10 (depends on 1) The improved industrial process as recited in claim 1 wherein the shifting is a function of a second statistical control parameter, the at least one variable being less than the second statistical control parameter before the shifting. ### Claim 11 (depends on 1) The improved industrial process as recited in claim 1 wherein wherein the shifting occurs stepwise in a control loop. ### Claim 12 (depends on 11) The improved industrial process as recited in claim 11 wherein the at least one excess includes a plurality of excesses, the shifting eliminating the excesses. ### Claim 13 (depends on 11) The improved industrial process as recited in claim 11 wherein the at least one excess includes a plurality of excesses, the shifting eliminating all excesses. ### Claim 14 (depends on 1) The improved industrial process as recited in claim 1 wherein the at least one excess includes a plurality of excesses, the shifting eliminating the excesses. ### Claim 15 (depends on 1) The improved industrial process as recited in claim 1 wherein the at least one excess includes a plurality of excesses, the shifting eliminating all excesses. ### Claim 16 A system for an improved industrial process comprising: a processor capable of receiving a plurality of data items related to an industrial process, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time; an analyzer analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable, the at least one variable representing manufactured parts having defects, the analyzing including identifying duplicates, null values, negative values and/or outliers; an input for setting a statistical control parameter as an achievable quantity for the at least one variable; the processor identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define an excess of defective manufactured parts; the system eliminating the excess of defective manufactured parts by shifting resources for manufacturing the parts related to the at least one quantity, the shifting being a function of the analyzing of the plurality of data items. ### Claim 17 An improved industrial process comprising: receiving in a processor a plurality of data items related to an industrial process, each data item being time stamped so that each data item includes time stamp and industrial process data regarding an industrial process occurring at a time; analyzing the plurality of data items in a processor via a plurality of rules, the analyzing identifying deviations of at least one variable of the plurality of data items from a mean value of the variable, the at least one variable representing manufactured parts having defects, the analyzing including generating both derived and latent features and analyzing time stamped data across the derived and latent features to identify which features contributes towards a defect rate; setting a statistical control parameter as an achievable quantity for the at least one variable; identifying the plurality of data items where the at least one variable exceeds the statistical control parameter to define at least one excess of defective manufactured parts; and eliminating the at least one excess of defective manufactured parts by shifting resources related to the at least one quantity to a time period associated with at least one excess of defective manufactured parts, the shifting being a function of the analyzing of the plurality of data items.