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  2. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive model solutions can be considered a type of data mining technology. The models can analyze both historical and current data and generate a model in order to predict potential future outcomes. [14] Regardless of the methodology used, in general, the process of creating predictive models involves the same steps.

  3. Predictive maintenance - Wikipedia

    en.wikipedia.org/wiki/Predictive_maintenance

    Predictive maintenance evaluates the condition of equipment by performing periodic (offline) or continuous (online) equipment condition monitoring.The ultimate goal of the approach is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold.

  4. Intelligent maintenance system - Wikipedia

    en.wikipedia.org/wiki/Intelligent_Maintenance_System

    An intelligent maintenance system is a system that uses data analysis and decision support tools to predict and prevent the potential failure of machines. The recent advancement in information technology, computers, and electronics have facilitated the design and implementation of such systems.

  5. Failure mode, effects, and criticality analysis - Wikipedia

    en.wikipedia.org/wiki/Failure_Mode,_Effects,_and...

    This might include, for example: Standardized mission profile with specific fixed duration mission phases; Sources for failure rate and failure mode data; Fault detection coverage that system built-in test will realize; Whether the analysis will be functional or piece-part; Criteria to be considered (mission abort, safety, maintenance, etc.)

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. Predictive learning - Wikipedia

    en.wikipedia.org/wiki/Predictive_learning

    Predictive learning is a machine learning (ML) technique where an artificial intelligence model is fed new data to develop an understanding of its environment, capabilities, and limitations. This technique finds application in many areas, including neuroscience , business , robotics , and computer vision .

  8. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    For example, a large consumer organization such as a mobile telecommunications operator will have a set of predictive models for product cross-sell, product deep-sell (or upselling) and churn. It is also now more common for such an organization to have a model of savability using an uplift model. This predicts the likelihood that a customer can ...

  9. PackML - Wikipedia

    en.wikipedia.org/wiki/Packml

    The Manufacturing Automation Industry is broken down into three main categories; Continuous control, Batch control and Discrete control. [2] The batch control industry and the packaging industry (discrete control of packaging machines) are the focus of a set of standards and guidelines that are similar but have differences driven by equipment functionality.