Abstract: One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.

Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

Abstract: One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.

Abstract: A power source is configured to supply power to one or more components of an electronic device. A processing device that is in communication with the power source can be configured to determine an estimated power requirement of the mobile electronic device during a time period, to determine a charge state of the power source, and to produce an indication of the remaining use time of the electronic device based on the estimated power requirement and the charge state of the power source.

Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

Abstract: A method includes accessing feature values representing a historical population of assembly units assembled on an assembly line; and accessing a failure status of the assembly unit at a target test on the assembly line. The method also includes, for each feature: deriving a correlation between values of the feature and failure status at the target test; deriving an effective limit of the feature based on scope of feature values in the historical population of assembly units; and calculating an action score for the feature based on the correlation and a width of the effective limit. The method further includes: selecting a particular feature exhibiting greatest action score; defining a preemptive test for the particular feature upstream of the target test during a next assembly period; and assigning a target limit, narrower than an effective limit of the particular feature, to the preemptive test.

Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

Abstract: One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.

Abstract: One variation of an optical inspection kit includes: an enclosure defining an imaging volume; an optical sensor adjacent the imaging volume and defining a field of view directed toward the imaging volume; a nest module defining a receptacle configured to locate a surface of interest on a first unit of a first part within the imaging volume at an image plane of the optical sensor; a dark-field lighting module adjacent and perpendicular to the nest module and including a dark-field light source configured to output light across a light plane and a directional light filter configured to pass light output by the dark-field light source normal to the light plane and to reject light output by the dark-field light source substantially nonparallel to the light plane; and a bright-field light source proximal the optical sensor and configured to output light toward the surface of interest.

Abstract: One variation of an optical inspection kit includes: an enclosure defining an imaging volume; an optical sensor adjacent the imaging volume and defining a field of view directed toward the imaging volume; a nest module defining a receptacle configured to locate a surface of interest on a first unit of a first part within the imaging volume at an image plane of the optical sensor; a dark-field lighting module adjacent and perpendicular to the nest module and including a dark-field light source configured to output light across a light plane and a directional light filter configured to pass light output by the dark-field light source normal to the light plane and to reject light output by the dark-field light source substantially nonparallel to the light plane; and a bright-field light source proximal the optical sensor and configured to output light toward the surface of interest.

Abstract: One variation of a method for automatically generating a common measurement across multiple assembly units includes: displaying a first image—recorded at an optical inspection station—within a user interface; receiving manual selection of a particular feature in a first assembly unit represented in the first image; receiving selection of a measurement type for the particular feature; extracting a first real dimension of the particular feature in the first assembly unit from the first image according to the measurement type; for each image in a set of images, identifying a feature—analogous to the particular feature—in an assembly unit represented in the image and extracting a real dimension of the feature in the assembly unit from the image according to the measurement type; and aggregating the first real dimension and a set of real dimensions extracted from the set of images into a digital container.

Abstract: One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.

Abstract: A method includes: displaying a first image of a first assembly unit within a user interface; locating a first virtual origin at a first feature on the first assembly unit; displaying a first subregion of the first image within the user interface responsive to a change in a view window of the first image; recording a geometry and a position of the first subregion relative to the first virtual origin; locating a second virtual origin at a second feature—analogous to the first feature—on a second assembly unit represented in the second image; projecting the geometry and the position of the first subregion onto the second image according to the second virtual origin to define a second subregion of the second image; and, in response to receipt of a command to advance from the first image to the second image, displaying the second subregion within the user interface.

Abstract: A power source is configured to supply power to one or more components of an electronic device. A processing device that is in communication with the power source can be configured to determine an estimated power requirement of the mobile electronic device during a time period, to determine a charge state of the power source, and to produce an indication of the remaining use time of the electronic device based on the estimated power requirement and the charge state of the power source.

Abstract: One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.

Abstract: A power source is configured to supply power to one or more components of an electronic device. A processing device that is in communication with the power source can be configured to determine an estimated power requirement of the mobile electronic device during a time period, to determine a charge state of the power source, and to produce an indication of the remaining use time of the electronic device based on the estimated power requirement and the charge state of the power source.

Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.