Design of A Condition-Based Analytical Decision Support Tool
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As manufacturing companies thrive to achieve global competitiveness, effective plant monitoring and short decision making time has proven to be a big contribution for them to achieve their goal. To cut operational costs and offer a competitive edge, the companies need not only to capture equipment failure but to predict the failure occurrence. The book discusses an analytical decision support tool for monitoring a generator thrust bearing of a hydro power station. The system consists of a distributed Multi-Agent System (MAS) comprising of agents. The diagnosis agent is responsible for obtainin...
As manufacturing companies thrive to achieve global competitiveness, effective plant monitoring and short decision making time has proven to be a big contribution for them to achieve their goal. To cut operational costs and offer a competitive edge, the companies need not only to capture equipment failure but to predict the failure occurrence. The book discusses an analytical decision support tool for monitoring a generator thrust bearing of a hydro power station. The system consists of a distributed Multi-Agent System (MAS) comprising of agents. The diagnosis agent is responsible for obtaining the parameter readings from the sensors using a Siemens PLC and an OPC server. The decision alarm agent uses a rule base to monitor the parameters obtained from the diagnosis agent and make decisions on equipment availability. The desired action and equipment performance trends are then conveyed to the user by the distribution agent. The decision support tool is developed using the Java Agent Development framework (JADE). The proposed system showed an increase in machine availability and reduction in the maintenance scheduling time and parts inventory.
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