US 11,537,923 B2Granted

Predictive methodology to identify potential unknown sweet spots

AssigneeFord Global Technologies, LLC

InventorsHossein Jacob Sadri, Steven Torey, Stephen Juszczyk, Lance David Marsac, Sueha Elmir Salame

Life of this patent

Estimating the term…

Loading patent…

Abstract

To identify the sweet spot for criteria attributes (i.e., variables) within a complex system, a data source having objectively acceptable values or ranges of values for the criteria attributes for each variant of the system is generated. The identification system used to analyze the complex system to identify the sweet spot receives measurement values from a testing system that measures values of the criteria attributes from variants of the complex system and provides the measurement values to the identification system. The criteria attributes may be prioritized for determination of the sweet spot, including a selection of a value or range of values that are to be used for the most highly prioritized criteria attribute. The prioritized criteria attributes and objectively acceptable values can be used to filter the measurement values to identify the sweet spot for the variants of the complex system.

Claims19

Dependent claims

A computer-implemented method, comprising:

receiving, from a measurement system, measurement values for a subset of a plurality of criteria attributes for each of a subset of a plurality of variants of an object being tested to generate a plurality of measurement value sets, each measurement value set comprising the measurement values for each of the subset of criteria attributes for a variant of the plurality of variants of the object;
prioritizing the subset of criteria attributes;
accessing a data store comprising objective values for each of the plurality of criteria attributes for each of the plurality of variants of the object;
setting cross-functional variants for at least a portion of the plurality of criteria attributes in the data store;
filtering the plurality of measurement value sets based on the objective values for each criteria attribute of the prioritized subset of criteria attributes;
for each criteria attribute among the filtered prioritized subset of criteria attributes:
compare the criteria attribute against other criteria attributes in the filtered prioritized subset of criteria attributes using a sequential computing algorithm to identify parallel relationships within and between the filtered prioritized subset of criteria attributes;
and
identify a sweet spot for each criteria attribute in the filtered prioritized subset of criteria attributes for each variant of the object based on the identified parallel relationships.

6 more elements

A system, comprising:

one or more processors;
and
a memory having stored thereon instructions that, when executed by the one or more processors, cause the one or more processors to:
receive, from a measurement system, measurement values for a subset of a plurality of criteria attributes for each of a subset of a plurality of variants of an object being tested to generate a plurality of measurement value sets, each measurement value set comprising the measurement values for each of the subset of criteria attributes for a variant of the plurality of variants of the object;
prioritize the subset of criteria attributes;
access a data store comprising objective values for each of the plurality of criteria attributes for each of the plurality of variants of the object;
and
set cross-functional variants for at least a portion of the plurality of criteria attributes in the data store;
filter the plurality of measurement value sets based on the objective values for each criteria attribute of the prioritized subset of criteria attributes;
for each criteria attribute among the filtered prioritized subset of criteria attributes:
compare the criteria attribute against other criteria attributes in the filtered prioritized subset of criteria attributes using a sequential computing algorithm to identify parallel relationships within and between the filtered prioritized subset of criteria attributes;
and
identify a sweet spot for each criteria attribute in the filtered prioritized subset of criteria attributes for each variant of the object based on the identified parallel relationships.

10 more elements

A non-transitory memory device having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to:

receive, from a measurement system, measurement values for a subset of a plurality of criteria attributes for each of a subset of a plurality of variants of an object being tested to generate a plurality of measurement value sets, each measurement value set comprising the measurement values for each of the subset of criteria attributes for a variant of the plurality of variants of the object;
prioritize the subset of criteria attributes;
access a data store comprising objective values for each of the plurality of criteria attributes for each of the plurality of variants of the object;
and
set cross-functional variants for at least a portion of the plurality of criteria attributes in the data store;
filter the plurality of measurement value sets based on the objective values for each criteria attribute of the prioritized subset of criteria attributes;
for each criteria attribute among the filtered prioritized subset of criteria attributes:
compare the criteria attribute against other criteria attributes in the filtered prioritized subset of criteria attributes using a sequential computing algorithm to identify parallel relationships within and between the filtered prioritized subset of criteria attributes;
and
identify a sweet spot for each criteria attribute in the filtered prioritized subset of criteria attributes for each variant of the object based on the identified parallel relationships.

7 more elements

Dependencies are inferred from the claim text.