Abstract: The invention relates to an anti-microbial composition [composition (C), herein after], wherein said composition (C) comprises from 60.00 to 94.45% by weight (wt. %) of at least one monocarboxylic acid having from 1 to 5 carbon atoms, or a salt, or mixtures thereof; from 5.00 to 25.00% by weight (wt. %) of at least one medium-chain fatty acid comprising from 6 to 12 carbon atoms or derivatives thereof, from 0.05 to 2.50% by weight (wt. %) of at least one monoterpene; wherein said composition (C) is substantially free of aliphatic aldehydes having from 1 to 12 carbon atoms and wherein all wt. % are relative to the total weight of the composition (C).

Abstract: Methods for monitoring a machine are described. In one aspect, a method includes receiving information on a plurality of events associated with the machine, determining a severity value for at least one event of the plurality of events, the severity value based on at least one of a safety value, a hierarchy value, a time-to-repair value, and a cost-of-repair value, and outputting an alert includes the severity value if the severity value exceeds a predetermined threshold associated with the at least one event. Systems and machine-readable media are also described.

Abstract: Methods for monitoring a machine are described. In one aspect, a method includes receiving information on a plurality of events associated with the machine, determining a severity value for at least one event of the plurality of events, the severity value based on at least one of a safety value, a hierarchy value, a time-to-repair value, and a cost-of-repair value, and outputting an alert includes the severity value if the severity value exceeds a predetermined threshold associated with the at least one event. Systems and machine-readable media are also described.

Abstract: Methods for monitoring a machine are described. In one aspect, a method includes receiving information on a plurality of events associated with the machine, determining a severity value for at least one event of the plurality of events, the severity value based on at least one of a safety value, a hierarchy value, a time-to-repair value, and a cost-of-repair value, and outputting an alert includes the severity value if the severity value exceeds a predetermined threshold associated with the at least one event. Systems and machine-readable media are also described.

Abstract: Methods for monitoring a machine are described. In one aspect, a method includes receiving information on a plurality of events associated with the machine, determining a severity value for at least one event of the plurality of events, the severity value based on at least one of a safety value, a hierarchy value, a time-to-repair value, and a cost-of-repair value, and outputting an alert includes the severity value if the severity value exceeds a predetermined threshold associated with the at least one event. Systems and machine-readable media are also described.

Abstract: Methods for predicting a machine event are described. In one aspect, a method includes receiving data for current events for the machine, and determining whether the data for the current events is within operational limits. The method also includes, when the data for the current events is within operational limits, determining, using a predetermined model, whether an anomaly exists, and generating an alert including information on the anomaly when the anomaly exists. Systems and machine-readable media are also described.

Abstract: Methods for decomposing event information for a machine are described. In one aspect, a method includes receiving event data identifying events associated with a machine on a first communications channel, and receiving trend data for the machine associated with the identified events on a second communications channel separate from the first communications channel. Systems and machine-readable media are also described.

Abstract: Methods for predicting a machine event are described. In one aspect, a method includes receiving data for current events for the machine, and determining whether the data for the current events is within operational limits. The method also includes, when the data for the current events is within operational limits, determining, using a predetermined model, whether an anomaly exists, and generating an alert including information on the anomaly when the anomaly exists. Systems and machine-readable media are also described.

Abstract: Methods for decomposing event information for a machine are described. In one aspect, a method includes receiving event data identifying events associated with a machine on a first communications channel, and receiving trend data for the machine associated with the identified events on a second communications channel separate from the first communications channel. Systems and machine-readable media are also described.

Abstract: Methods for monitoring a machine are described. In one aspect, a method includes receiving information on a plurality of events associated with the machine, determining a severity value for at least one event of the plurality of events, the severity value based on at least one of a safety value, a hierarchy value, a time-to-repair value, and a cost-of-repair value, and outputting an alert includes the severity value if the severity value exceeds a predetermined threshold associated with the at least one event. Systems and machine-readable media are also described.