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 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.