Abstract: The types of faults that can be detected using the proposed scheme are tank leaks, pump failure, valve failure… etc. In the first step of the proposed scheme, the data will be collected at the normal mode of the process. These data will be clustering according to its source. This stage directs these data to the second-stage that comprises local models. The Fault Diagnostic and Detection [FDD] stage will detect and isolate faults (if any) and recommend the solution for the detected fault. The existing maintenance methods used nowadays are planned maintenance, corrective maintenance, preventive maintenance, fault reporting, condition-based-maintenance (CBM), etc. CBM may be the best one used in recent years. The FDD proposed to the Embedded Condition Based Maintenance [ECBM] will use the existing modules in DCS and/or SCADA systems to improve the CBM used today. Compared with the CBM, the proposed ECBM scheme will be lower in cost, and will be faster in fault detection. The Scheme used in the proposed ECBM performs on-line maintenance instead of planned maintenance or CBM. The usage of Embedded technology within CBM raises lots of challenges to be explored and new methods to deduced Key Words: Diagnostics and Prognostics Signals, Petri nets, Clustering Techniques, Online Fault Detection [OFD], CBM, ECBM, FDI, FDD, AEM and CMMS
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