Abstract: Based on an analysis of asset attribute data associated with a plurality of assets, a platform may detect a locality that is a possible instance of a given type of environment, such as a mine or construction site. In response, the platform may obtain image data associated with the detected locality and input that image data into a model that outputs likelihood data indicating a likelihood that any portion of the detected locality comprises a given feature of the given type of environment (e.g., a boundary, navigation route, hazard, etc.), where this model is defined based on training data. Based on the likelihood data, the platform may then generate output data indicating a location of any portion of the detected locality that is likely to comprise the given feature. In turn, the platform may use the output data to simulate asset operation in the detected locality.

Abstract: A computing system may be configured to simplify a complex dataset of nodes representing an operational environment. To that end, the computing system (a) associates nodes with a respective set of asset data related to how assets operate when located in proximity to the given node, where the respective asset data includes a respective value of at least one given asset-data variable, (b) evaluates whether any nodes can be eliminated using a divergence function that determines a maximum divergence between (i) one set of values including an original value of the given asset-data variable for each candidate node and (ii) another set of values including an imputed value of the given variable for each candidate node, (c) removes nodes from the dataset identified for elimination, thereby generating a reduced dataset, and (d) uses the reduced dataset to evaluate the operation of assets in the environment defined by the reduced dataset.

Abstract: Based on an analysis of asset attribute data associated with a plurality of assets, a platform may detect a locality that is a possible instance of a given type of environment, such as a mine or construction site. In response, the platform may obtain image data associated with the detected locality and input that image data into a model that outputs likelihood data indicating a likelihood that any portion of the detected locality comprises a given feature of the given type of environment (e.g., a boundary, navigation route, hazard, etc.), where this model is defined based on training data. Based on the likelihood data, the platform may then generate output data indicating a location of any portion of the detected locality that is likely to comprise the given feature. In turn, the platform may use the output data to simulate asset operation in the detected locality.

Abstract: A computer-implemented method for simulating a facility to achieve one or more business goals is disclosed. The method includes receiving, by a processor, one or more input parameters for a discrete event simulator (DES) module for a facility, a plurality of business goals for the facility, and a selection of a goal optimization technique. The method also includes generating, by the processor, a DES output that simulates processes occurring within the facility based on the one or more input parameters and simultaneously achieves the business goals in accordance with the selected goal optimization technique.

Abstract: A computer-implemented method for simulating movement of materials within a facility using predefined software objects is disclosed. The method includes storing a plurality of predefined software objects in a computer memory, each of the predefined software objects including one or more discrete event simulator commands and representing a process performed at a facility. The method also includes receiving, by one or more processors, an instruction to simulate movement of a material within a facility, and linking, by the one or more processors, two or more of the predefined software objects together to represent the movement of the material within the facility. The method further includes executing, by the one or more processors, the linked predefined software objects using a discrete event simulator to simulate the movement of the material within the facility.

Abstract: A computer-implemented method for automatically communicating updates between a computer-aided-design (CAD) module that generates a representation of the physical structure of a facility and a discrete event simulator (DES) module that simulates processes occurring within the facility is disclosed. The method may include establishing a communication link between the CAD module and the DES module.