Abstract: A heating system includes a plurality of heater elements, a plurality of switches connected to the plurality of heater elements, a set of predetermined performance information including heater information specific for each heater element, at least one temperature sensor measuring temperature of at least one heater element from among the plurality of heater elements, and a heater control unit in communication with the temperature sensor(s). The heater control unit controls the heater elements differently, via the switches, based on the heater information and the measured temperature from the temperature sensor(s).

Abstract: A method, computer program product, and a system where a processor(s), in a computing environment comprised of multiple containers comprising modules, includes a processor(s) continuously obtaining pressure data from pressure sensors embedded in electrostatic dissipative (ESD) footwear. The processor(s) determines that the obtained pressure data indicates a pressure level of a pre-determined threshold and the given threshold is sustained for a pre-determined interval of time in some of the items. The processor(s) accesses one or more voltage sensors embedded in each item of the items and obtains voltage data by utilizing an ESD floor that the items are in contact with as a ground reference. The processor(s) validates functionality of some of the items and functionality of the ESD floor, based on monitoring the voltage data from the one or more voltage sensors.

Abstract: An enhanced prediction model utilizing product life cycle segmentation and historic prediction data for generating more accurate future failure rates. Input data is segmented into groups based on failure modes of a corresponding life cycle. A prediction model such as Weibull analysis is implemented for each segmented group. Historical prediction data is also segmented into groups. Prediction parameters for each group of segmented historical prediction data are compared with one another and the comparisons are then used to adjust the prediction parameters generated from the segmented groups of input data. Updated parameters for the input data are then output thereby generating a new future failure rate.

Abstract: Embodiments of the present disclosure related to automated static control. A set of static sensor data may be obtained from two or more static sensors. The set of static sensor data may be analyzed to determine whether a static condition exists. In response to a determination that a static condition exists, a set of mobile static unit data may be collected from one or more mobile static units. The set of mobile static unit data may be analyzed to select a mobile static unit of the one or more mobile static units. An action may be transmitted to the selected mobile static unit, and the selected mobile static unit may be deployed to mitigate the static condition.

Abstract: A method, computer program product, and a system where a processor(s), in a computing environment comprised of multiple containers comprising modules, includes a processor(s) continuously obtaining pressure data from pressure sensors embedded in electrostatic dissipative (ESD) footwear. The processor(s) determines that the obtained pressure data indicates a pressure level of a pre-determined threshold and the given threshold is sustained for a pre-determined interval of time in some of the items. The processor(s) accesses one or more voltage sensors embedded in each item of the items and obtains voltage data by utilizing an ESD floor that the items are in contact with as a ground reference. The processor(s) validates functionality of some of the items and functionality of the ESD floor, based on monitoring the voltage data from the one or more voltage sensors.

Abstract: A method, computer program product, and a system where a processor(s), in a computing environment comprised of multiple containers comprising modules, includes a processor(s) continuously obtaining pressure data from pressure sensors embedded in electrostatic dissipative (ESD) footwear. The processor(s) determines that the obtained pressure data indicates a pressure level of a pre-determined threshold and the given threshold is sustained for a pre-determined interval of time in some of the items. The processor(s) accesses one or more voltage sensors embedded in each item of the items and obtains voltage data by utilizing an ESD floor that the items are in contact with as a ground reference. The processor(s) validates functionality of some of the items and functionality of the ESD floor, based on monitoring the voltage data from the one or more voltage sensors.

Abstract: A method, computer program product, and a system where a processor(s) obtains data comprising trends recognized by an observer of the system over time; data comprised of more than one vintage. The processor(s) transforms the data measurable dimensions and assigns the transformed data to vintages and to distinct periods of time. The processor(s) generates an image from the transformed data that represents the trends, organized by the distinct periods of times and the vintages.

Abstract: A method, computer program product, and a system where a processor(s) obtains data comprising trends recognized by an observer of the system over time; data comprised of more than one vintage. The processor(s) transforms the data measurable dimensions and assigns the transformed data to vintages and to distinct periods of time. The processor(s) generates an image from the transformed data that represents the trends, organized by the distinct periods of times and the vintages.

Abstract: A heating system includes a plurality of heater elements, a plurality of switches connected to the plurality of heater elements, a set of predetermined performance information including heater information specific for each heater element, at least one temperature sensor measuring temperature of at least one heater element from among the plurality of heater elements, and a heater control unit in communication with the temperature sensor(s). The heater control unit controls the heater elements differently, via the switches, based on the heater information and the measured temperature from the temperature sensor(s).

Abstract: A heater control module of the present disclosure controls exhaust temperature in an exhaust after treatment system. The heater control module includes a heating mode determination module and a heater operating module. The heating mode determination module is configured to select a desired heating mode from a plurality of heating modes based on an engine load and a status of a component of the exhaust aftertreatment system. The heater operating module is configured to operate an electric heater based on the desired heating mode. The plurality of modes includes at least a passive regeneration heating mode and an active regeneration heating mode. The electric heater is operated in the passive regeneration heating mode to heat an exhaust gas to a predetermined temperature to increase NO2 generation when an engine load is less than or equal to approximately 25%.

Abstract: An enhanced prediction model utilizing product life cycle segmentation and historic prediction data for generating more accurate future failure rates. Input data is segmented into groups based on failure modes of a corresponding life cycle. A prediction model such as Weibull analysis is implemented for each segmented group. Historical prediction data is also segmented into groups. Prediction parameters for each group of segmented historical prediction data are compared with one another and the comparisons are then used to adjust the prediction parameters generated from the segmented groups of input data. Updated parameters for the input data are then output thereby generating a new future failure rate.

Abstract: A method, computer program product, and a system where a processor(s), in a computing environment comprised of multiple containers comprising modules, includes a processor(s) continuously obtaining pressure data from pressure sensors embedded in electrostatic dissipative (ESD) footwear. The processor(s) determines that the obtained pressure data indicates a pressure level of a pre-determined threshold and the given threshold is sustained for a pre-determined interval of time in some of the items. The processor(s) accesses one or more voltage sensors embedded in each item of the items and obtains voltage data by utilizing an ESD floor that the items are in contact with as a ground reference. The processor(s) validates functionality of some of the items and functionality of the ESD floor, based on monitoring the voltage data from the one or more voltage sensors.

Abstract: Embodiments of the present disclosure related to automated static control. A set of static sensor data may be obtained from two or more static sensors. The set of static sensor data may be analyzed to determine whether a static condition exists. In response to a determination that a static condition exists, a set of mobile static unit data may be collected from one or more mobile static units. The set of mobile static unit data may be analyzed to select a mobile static unit of the one or more mobile static units. An action may be transmitted to the selected mobile static unit, and the selected mobile static unit may be deployed to mitigate the static condition.

Abstract: Embodiments of the present disclosure related to automated static control. A set of static sensor data may be obtained from two or more static sensors. The set of static sensor data may be analyzed to determine whether a static condition exists. In response to a determination that a static condition exists, a set of mobile static unit data may be collected from one or more mobile static units. The set of mobile static unit data may be analyzed to select a mobile static unit of the one or more mobile static units. An action may be transmitted to the selected mobile static unit, and the selected mobile static unit may be deployed to mitigate the static condition.

Abstract: Embodiments of the present disclosure related to automated static control. A set of static sensor data may be obtained from two or more static sensors. The set of static sensor data may be analyzed to determine whether a static condition exists. In response to a determination that a static condition exists, a set of mobile static unit data may be collected from one or more mobile static units. The set of mobile static unit data may be analyzed to select a mobile static unit of the one or more mobile static units. An action may be transmitted to the selected mobile static unit, and the selected mobile static unit may be deployed to mitigate the static condition.

Abstract: A heater control module of the present disclosure controls exhaust temperature in an exhaust after treatment system. The heater control module includes a heating mode determination module and a heater operating module. The heating mode determination module is configured to select a desired heating mode from a plurality of heating modes based on an engine load and a status of a component of the exhaust aftertreatment system. The heater operating module is configured to operate an electric heater based on the desired heating mode. The plurality of modes includes at least a passive regeneration heating mode and an active regeneration heating mode. The electric heater is operated in the passive regeneration heating mode to heat an exhaust gas to a predetermined temperature to increase NO2 generation when an engine load is less than or equal to approximately 25%.

Abstract: A method of heating an exhaust gas in an exhaust after treatment system includes selecting a heating mode between a plurality of heating modes based on an engine load and a status of a component of the exhaust aftertreatment system. The method further comprises heating the exhaust gas by operating the electric heater in the selected heating mode, and operating the electric heater in a passive regeneration heating mode to heat an exhaust gas to a predetermined temperature to increase NO2 generation when an engine load is less than or equal to approximately 25%.

Abstract: A method of heating an exhaust gas in an exhaust after treatment system includes selecting a heating mode between a plurality of heating modes based on an engine load and a status of a component of the exhaust aftertreatment system. The method further comprises heating the exhaust gas by operating the electric heater in the selected heating mode, and operating the electric heater in a passive regeneration heating mode to heat an exhaust gas to a predetermined temperature to increase NO2 generation when an engine load is less than or equal to approximately 25%.

Abstract: A method of heating an exhaust gas in an exhaust aftertreatment system by selecting a heating mode between different heating modes based on an engine load and a status of a component of the exhaust aftertreatment system. The method includes heating the exhaust gas by operating the electric heater in the selected heating mode and heating the exhaust gas to reduce an exhaust temperature gradient across the exhaust conduit.

Abstract: A method of heating an exhaust gas in an exhaust aftertreatment system by selecting a heating mode between different heating modes based on an engine load and a status of a component of the exhaust aftertreatment system. The method includes heating the exhaust gas by operating the electric heater in the selected heating mode and heating the exhaust gas to reduce an exhaust temperature gradient across the exhaust conduit.