Abstract: The present disclosure relates to chromium-on-alumina dehydrogenation catalyst materials, to methods for making such catalysts, and to methods for dehydrogenating hydrocarbons using such catalysts. In one aspect, the disclosure provides a method for preparing a dehydrogenation catalyst material, the method comprising impregnating a chromium-on-alumina material with ascorbic acid, one or more of sodium, lithium and potassium (e.g., sodium), and chromium; and calcining the impregnated material to provide the dehydrogenation catalyst material comprising chromium in the range of 2.5 wt. % to about 35 wt. % and having no more than 100 ppm chromium(VI).

Abstract: The present disclosure relates to chromium-on-alumina dehydrogenation catalyst materials, to methods for making such catalysts, and to methods for dehydrogenating hydrocarbons using such catalysts. In one aspect, the disclosure provides a method for preparing a dehydrogenation catalyst material, the method comprising impregnating a chromium-on-alumina material with ascorbic acid, one or more of sodium, lithium and potassium (e.g., sodium), and chromium; and calcining the impregnated material to provide the dehydrogenation catalyst material comprising chromium in the range of 2.5 wt. % to about 35 wt. % and having no more than 100 ppm chromium(VI).

Abstract: Embodiments are directed towards enabling users to customize data collection and analysis. A collection computer may automatically detect and dynamically update each of a plurality of sensors that may be currently providing real-time data regarding at least one characteristic of a machine. At least one sensor may be selected for local storage of its corresponding real-time data at the collection computer. And at least one sensor may be selected for remote storage of its corresponding real-time data by a server computer. A template may be employed to remotely display at least one characteristic of the machine based on current real-time data provided by at least one of the sensors identified by the template. In response to the user selecting at least one sensor for remote display, the template may be modified to include the remote display of the at least one sensor's corresponding current real-time data.

Abstract: Embodiments are directed towards modular power plants that provide power to operate machines. A power plant is a combustion-electric hybrid power plant that includes at least one or more engines, one or more generators, and one or more battery arrays. The battery arrays include one or more modular batteries. Rather than the engine directly providing power to the machine, the engine and generators charge the batteries. The batteries provide the power required to operate the machine. A user may vary the maximum power output of the power plant by varying the number and/or type of modular batteries included in the one or more battery arrays. The specific configuration of the batteries may be based on the power requirements of the machine's expected usage or operation. The power plant is configured to a specific machine application by installing and/or removing batteries from the battery arrays based on the machine's power requirements.

Abstract: Embodiments are directed towards providing analytics and marketplace data to members of a user community. In some embodiments, the analytics and marketplace data are generated based on machine data provided by the members. The analytics and marketplace data may enable automatically identifying, configuring, monitoring, controlling, managing, and/or maintaining a machine or a collection/system of machine components. The analytics may include, but are not limited to analytics related to machine component reliability, machine maintenance conditions, machine prohibited conditions, machine usages, machine alert conditions, and the like. The marketplace data may include information relating to the maintenance of the machine, replacement components or alternative components for the machine, and the like for various machines. Marketplace data may include an aggregation of electronic (e)-commerce data.

Abstract: Embodiments are directed towards automatically identifying, configuring, monitoring, controlling, managing, and maintaining a machine, via collection computers in communication with the machine components. The components include ID Tags that store identification data, such as a component type and a unique identifier. Interrogation of the ID Tags enables the automatic identification and configuration of the machine. Data provided by the sensors, during usage of the machine, enables the remote monitoring and managing of the usage, as well as maintaining of the machine. Machine maintenance includes automatically predicting and scheduling the replacement of various components. Embodiments provide suggestions for suppliers of replacement components, as well as suggestions for alternative components that may be better optimized for the configuration and usage of the machine.

Abstract: Embodiments are directed towards modular power plants that provide power to operate machines. A power plant is a combustion-electric hybrid power plant that includes at least one or more engines, one or more generators, and one or more battery arrays. The battery arrays include one or more modular batteries. Rather than the engine directly providing power to the machine, the engine and generators charge the batteries. The batteries provide the power required to operate the machine. A user may vary the maximum power output of the power plant by varying the number and/or type of modular batteries included in the one or more battery arrays. The specific configuration of the batteries may be based on the power requirements of the machine's expected usage or operation. The power plant is configured to a specific machine application by installing and/or removing batteries from the battery arrays based on the machine's power requirements.

Abstract: Embodiments are directed towards enabling users to customize data collection and analysis. A collection computer may automatically detect and dynamically update each of a plurality of sensors that may be currently providing real-time data regarding at least one characteristic of a machine. At least one sensor may be selected for local storage of its corresponding real-time data at the collection computer. And at least one sensor may be selected for remote storage of its corresponding real-time data by a server computer. A template may be employed to remotely display at least one characteristic of the machine based on current real-time data provided by at least one of the sensors identified by the template. In response to the user selecting at least one sensor for remote display, the template may be modified to include the remote display of the at least one sensor's corresponding current real-time data.

Abstract: Embodiments are directed towards providing analytics and marketplace data to members of a user community. In some embodiments, the analytics and marketplace data are generated based on machine data provided by the members. The analytics and marketplace data may enable automatically identifying, configuring, monitoring, controlling, managing, and/or maintaining a machine or a collection/system of machine components. The analytics may include, but are not limited to analytics related to machine component reliability, machine maintenance conditions, machine prohibited conditions, machine usages, machine alert conditions, and the like. The marketplace data may include information relating to the maintenance of the machine, replacement components or alternative components for the machine, and the like for various machines. Marketplace data may include an aggregation of electronic (e)-commerce data.

Abstract: Embodiments are directed towards automatically identifying, configuring, monitoring, controlling, managing, and maintaining a machine, via collection computers in communication with the machine components. The components include ID Tags that store identification data, such as a component type and a unique identifier. Interrogation of the ID Tags enables the automatic identification and configuration of the machine. Data provided by the sensors, during usage of the machine, enables the remote monitoring and managing of the usage, as well as maintaining of the machine. Machine maintenance includes automatically predicting and scheduling the replacement of various components. Embodiments provide suggestions for suppliers of replacement components, as well as suggestions for alternative components that may be better optimized for the configuration and usage of the machine.

Abstract: Embodiments are directed towards providing analytics and marketplace data to members of a user community. In some embodiments, the analytics and marketplace data are generated based on machine data provided by the members. The analytics and marketplace data may enable automatically identifying, configuring, monitoring, controlling, managing, and/or maintaining a machine or a collection/system of machine components. The analytics may include, but are not limited to analytics related to machine component reliability, machine maintenance conditions, machine prohibited conditions, machine usages, machine alert conditions, and the like. The marketplace data may include information relating to the maintenance of the machine, replacement components or alternative components for the machine, and the like for various machines. Marketplace data may include an aggregation of electronic (e)-commerce data.

Abstract: Embodiments are directed towards automatically identifying, configuring, monitoring, controlling, managing, and maintaining a machine, via collection computers in communication with the machine components. The components include ID Tags that store identification data, such as a component type and a unique identifier. Interrogation of the ID Tags enables the automatic identification and configuration of the machine. Data provided by the sensors, during usage of the machine, enables the remote monitoring and managing of the usage, as well as maintaining of the machine. Machine maintenance includes automatically predicting and scheduling the replacement of various components. Embodiments provide suggestions for suppliers of replacement components, as well as suggestions for alternative components that may be better optimized for the configuration and usage of the machine.

Abstract: Embodiments are directed towards a collection computer that automatically detects and monitors each of a plurality of sensors that are currently providing real-time data regarding characteristics of a first machine. A pattern in the provided real-time data may be determined based on a comparison to another pattern from previously provided real-time data from other sensors associated with a second machine. The comparison is employed to identify an event that previously occurred at the second machine, where a positive comparison may be employed as a prediction that the event corresponding to the second machine is about to happen to the first machine. Based on this prediction, an alert may be provided to at least one user of the first machine. The alert may include information, such as a component has failed, is currently failing, or is about to fail.

Abstract: Embodiments are directed towards enabling users to customize data collection and analysis. A collection computer may automatically detect and dynamically update each of a plurality of sensors that may be currently providing real-time data regarding at least one characteristic of a machine. At least one sensor may be selected for local storage of its corresponding real-time data at the collection computer. And at least one sensor may be selected for remote storage of its corresponding real-time data by a server computer. A template may be employed to remotely display at least one characteristic of the machine based on current real-time data provided by at least one of the sensors identified by the template. In response to the user selecting at least one sensor for remote display, the template may be modified to include the remote display of the at least one sensor's corresponding current real-time data.

Abstract: A wireless input device having an outward appearance resembling a standard ballpoint pen operates as both a standard ballpoint pen or similar writing instrument as well as an input device. The pen includes directional sensors for determining the direction and length of each pen stroke. A transmitter is provided in the pen barrel for transmitting the stroke signals directly to a computer for input and processing each stroke to provide an accurate representation of the pen stroke as it is being made. The transmitter may be a wireless device for transmitting a low frequency radio signal to a receiver associated with the computer. This permits the pen to be utilized anywhere within the transmitting range of the device, and in any orientation, with the computer picking up, processing and storing the signal representing the pen strokes.

Abstract: A wireless input device having an outward appearance resembling a standard ballpoint pen operates as both a standard ballpoint pen or similar writing instrument as well as an input device. The pen includes directional sensors for determining the direction and length of each pen stroke. A transmitter is provided in the pen barrel for transmitting the stroke signals directly to a computer for input and processing each stroke to provide an accurate representation of the pen stroke as it is being made. The transmitter may be a wireless device for transmitting a low frequency radio signal to a receiver associated with the computer. This permits the pen to be utilized anywhere within the transmitting range of the device, and in any orientation, with the computer picking up, processing and storing the signal representing the pen strokes.