Honeywell International Inc.

David Joachim Germann

Gregory Edward Stewart

Marc Light

Dinkar A Mylaraswamy

Sharath Venkatesha

Daniel Pachner

Jonathan T Grunow

Greg Stewart

Jan Zirnstein

A method includes identifying costs associated with different outcomes of a failure prediction algorithm. The algorithm is configured to predict one or more faults with at least one piece of industrial equipment. The different outcomes include both successful and unsuccessful predictions by the algorithm. The method also includes identifying a threshold value for the algorithm using the costs, where the threshold value is used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed. The method further includes providing the threshold value to the algorithm. The threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. In addition, the method can include generating a signal indicating whether maintenance is needed based on a comparison of an indicator value calculated using the algorithm and the threshold value.

Cost-driven system and method for predictive equipment failure detection

A method includes identifying a statistical performance of a monitoring rule associated with an asset monitoring system. The monitoring rule includes logic configured to identify one or more faults with at least one asset, and the statistical performance includes an effectiveness of the monitoring rule in identifying the one or more faults. The method also includes identifying an economic performance of the monitoring rule, where the economic performance is based on costs associated with different outcomes of the monitoring rule. The method further includes updating or replacing the monitoring rule based on the economic performance.

Calibration technique for rules used with asset monitoring in industrial process control and automation systems

A method includes receiving information associated with operation of multiple pieces of industrial equipment at multiple sites. The multiple pieces of industrial equipment are of a same or similar type, and the information represents different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment. The method also includes analyzing the information to identify correlations in the information associated with one or more conditions involving the pieces of industrial equipment. The method further includes, based on the analyzing, generating one or more monitoring rules or routines to be used to identify the one or more conditions. The multiple pieces of industrial equipment could include machines with rotating components, machines with heat transfer equipment, or general process equipment.

System and method for asset fleet monitoring and predictive diagnostics using analytics for large and varied data sources

An inferential sensor module is incorporated into an engine simulation model. One or more parameters for the inferential sensor module are calibrated using one or more of engine measurement data and the engine simulation model. The calibration is performed such that a difference between an inferred signal predicted by the inferential sensor module and a signal measured on an engine is minimized. The inferential sensor module and the one or more calibrated parameters are loaded into an engine control unit in order to predict inferred variables.

Model based calibration of inferential sensing

A method and system for configuring a model of a process. A model of a process is provided, which follows a particular sequence. Such a model includes a plurality of component sub-models, wherein each component sub-model among the component sub-models includes one or more input variables and one or more output variables. Such a method and system also generally includes automatically assigning one or more output variables to one or more input variables based on information associated with the particular sequence of the process.

System and method for configuring a simulation model utilizing a tool for automatic input/output assignment

A selective catalytic reduction system includes a catalyst, a device to measure an amount of nitrogen oxide (NO), a device to measure an amount of nitrogen dioxide (NO), a device to add an ammonia source, and a control unit to calculate the amount of ammonia source to add as a function of a ratio of an amount of nitrogen oxide and an amount of nitrogen dioxide or an absolute amount of nitrogen oxide and an absolute amount of nitrogen dioxide.

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David Joachim Germann