processing_time.RdProvides summary statistics about the processing time of the process.
processing_time(eventlog, level, append, units, ...) # S3 method for eventlog processing_time(eventlog, level = c("log", "trace", "case", "activity", "resource", "resource-activity"), append = F, units = c("hours", "days", "weeks", "mins", "secs"), ...) # S3 method for grouped_eventlog processing_time(eventlog, level = c("log", "trace", "case", "activity", "resource", "resource-activity"), append = F, units = c("hours", "days", "weeks", "mins"), ...)
| eventlog | The dataset to be used. Should be a (grouped) eventlog object.
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| level | Level of granularity for the analysis: log, case, trace, activity, resource or resource-activity.
For more information, see |
| append | Logical, indicating whether to append results to original event log. Ignored when level is log or trace. |
| units | Time units to be used |
| ... | Deprecated arguments |
In contrast to the throughput time of the cases in an event log, the metrics concerning the active time or the actual processing time provide summary statistics on the processing time of events on the level of the complete event log, the specific cases, traces, the activities, and the resource-activity combinations.
On log level, this metric calculates the summary statistics of the actual processing time per case, summarised over the complete event log.
On case level, a list of cases with their processing time are provided.
On trace level, the summary statistics of processing time can be calculated for each possible sequence of activities that appears in the event log.
Duration can also be calculated on the level of each activity. For each activity, an overview of the average processing time -or the service time- of this activity can be of interest.
We can also look at the processing time per case on the level of each separate resource. This way, a company gets an overview of the amount of time each resource spends on a case and which resources spend more time on cases than others.
On the resource-activity level, finally, we can have a look at the efficiency of resources by looking at the combination of each resource with each activity.
eventlog: Compute processing time for event log
grouped_eventlog: Compute processing time on grouped eventlog
Swennen, M. (2018). Using Event Log Knowledge to Support Operational Exellence Techniques (Doctoral dissertation). Hasselt University.