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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.
Predictive maintenance differs from preventive maintenance because it does take into account the current condition of equipment (with measurements), instead of average or expected life statistics, to predict when maintenance will be required. Machine Learning approaches are adopted for the forecasting of its future states. [3]
The use of condition monitoring allows maintenance to be scheduled, or other actions to be taken to prevent consequential damages and avoid its consequences. Condition monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure.
Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future. [3] Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to ...
A discrete MPC scheme. MPC is based on iterative, finite-horizon optimization of a plant model. At time the current plant state is sampled and a cost minimizing control strategy is computed (via a numerical minimization algorithm) for a relatively short time horizon in the future: [, +].
Reliability-centered maintenance (RCM) is a concept of maintenance planning to ensure that systems continue to do what their users require in their present operating context. [1] Successful implementation of RCM will lead to increase in cost effectiveness, reliability, machine uptime, and a greater understanding of the level of risk that the ...
JasperReports is an open source reporting library that can be embedded into any Java application. Features include: Scriptlets may accompany the report definition, [3] which the report definition can invoke at any point to perform additional processing. The scriptlet is built using Java, and has many hooks that can be invoked before or after ...
The project is supported by an active community of users at BIRT Developer Center and developers at the Eclipse.org BIRT Project page. BIRT has two main components: a visual report designer within the Eclipse IDE for creating BIRT Reports, and a runtime component for generating reports that can be deployed to any Java environment.