A system and method for measuring the operation of a device is disclosed. A plurality of virtual sensors which define a multi-dimensional virtual sensor space sense the operation of the device. A normal operation determiner determines at least one region of normal operation for the device. An abnormal condition determiner provides a warning when the operation does not fall within the normal operation region which is defined within the multi-dimensional virtual sensor space. A maintenance method and system are also disclosed for maintaining at least one device. The maintenance system includes a measurement system and an abnormality processor. The measurement system measures the operation of the device and provides an indication of when the device is not operating normally. The abnormality processor predicts, based on the output of the measurement system, when the device is likely to fail.

System and method for measuring the operation of a device

https://www.philadelphia.edu.jo/academics/ttutunji/uploads/Journal%20Mechatronic%20Systems%20Isermann.pdf

Mechatronic systems—Innovative products with embedded control

Traditionally, decisions on how to improve an operation are based on risk priority number (RPN) in the failure mode and effects analysis (FMEA) Many scholars questioned the RPN method and proposed some new methods to improve the decision process, but these methods are only measuring from the risks viewpoint while ignoring the importance of corrective actions The corrective actions may be interdependent; hence, if the implementation of corrective actions is in proper order, selection may maximize the improvement effect, bring favorable results in the shortest times, and provide the lowest cost This study aims to evaluate the structure of hierarchy and interdependence of corrective action by interpretive structural model (ISM), then to calculate the weight of a corrective action through the analytic network process (ANP), then to combine the utility of corrective actions and make a decision on improvement priority order of FMEA by utility priority number (UPN) Finally, it verifies the feasibility and effectiveness of this method by application to a case study

Utility Priority Number Evaluation for FMEA

Applications of artificial intelligence in power systems

An on-vehicle system for assessing an operator's efficiency of a vehicle, include sensors, an audiovisual display device, a processor and a data storage. The sensors measure or detect conditions of components of the vehicle, and convert the detected conditions into analog or digital information. The data storage stores program instructions, the analog or digital information from the sensors, and other data. The program instructions, when executed by the processor, control the on-vehicle system to determine a state of the vehicle within a vehicle's environment based on the analog or digital information from the sensors, determine whether one or more of a predetermined set of behaviors has occurred based on the determined state of a vehicle, assess performance of the determined one or more of the predetermined set of behaviors, and present the operator, via the audiovisual display device, a feedback based on the assessment.

System and method for in-vehicle operator training

The failure mode and effects analysis (FMEA) is a widely used analytical tool, it is especially useful in the conduct of reliability, maintainability, and safety analyses. Such analyses are commonly used to identify failures of significant consequence and those affecting system performance. The author investigated about 100 FMEA applications. That investigation revealed that the FMEA technique is useful in virtually every stage of the modern industrial process. Although FMEAs were most frequently used in the initial design and development stages of a project, they were also of value in the manufacturing stage. In support of manufacturing, FMEAs contributed in deriving the optimum construction method and schedule. Even after construction of the plant, FMEAs were again found to add value in the analyses of day-to-day plant operations and maintenance activities, or the use stage. The continuous application of the FMEA process over the life-cycle of a project is ensured by the preparation of the individual FMEA worksheets for each stage. Examples of such worksheets are presented and discussed in this paper FMEAs are evaluated by either of two methods: criticality or risk priority number (RPN). The criticality method is used primarily at the design, development, and construction stages; whereas, the RPN method is favored at the manufacturing and use stages. The elements which comprise the Criticality and RPN method are also presented in this paper.

Effective techniques of FMEA at each life-cycle stage

A comprehensive program with the aim of prevention of plant forced outage is presented. Unplanned shutdowns occur in the event of failure of critical equipment and systems during plant operation, including both primary and auxiliary equipment. A diagnostic system, failure detection methods, and life estimation systems for critical equipment have been developed. Good results have been obtained; forced outage rates have been reduced by the application of this program to thermal and nuclear power plants. >

A successful preventive maintenance program for an electric power plant

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Effective techniques of FMEA at each life-cycle stage

A successful preventive maintenance program for an electric power plant