Define Dataset

Explanation

This activity is used to define the datasets that will be used within a company to transfer data to the Scheduling Engine. A dataset will contain information on how data should be scheduled. That is, the type of scheduling that should take place and the time horizon for the scheduling. There are four types of scheduling that can be assigned to a dataset, Static, Dynamic, Distributed and Appointment. Static scheduling is generally used for long term rough scheduling such as the resource capacity for a year, while Dynamic scheduling is used for short term detail scheduling with the focus on optimizing the utilization of resources.Distributed process type is a special processing type to allow large volumes of input data to be split between a smaller dynamic schedule and one or more static schedules.This can be used, for example, to combine dynamic scheduling with capacity planning. And the Appointment scheduling is used when the Appointment Booking Engine is requested to generate appointment slots based on available resources.

The time horizon for which the data should be transferred and scheduled should be entered in days. For instance, if the number of days is set to 7, all work tasks, schedules, resources, breaks and HR bookings, for the site(s), that should be scheduled within the given time interval (7 days in this example) will be sent to and scheduled by the Scheduling Engine. In addition an appointment work days duration can also be specified; the appointment work days duration will follow on from the scheduling work days duration to return a less accurate but faster schedule for a longer period. For example entering an appointment work days duration of 10 days and a scheduling work days duration of 5 days will make the Scheduling Engine schedule activities for 15 days ahead from the system date, with a high accuracy in the first 5 days and rest with a less accuracy. Further, a calendar can be entered as an input reference so that the scheduling work days duration will determined based on the working days of the calendar only. For example entering a 5 working days per week calendar, with 7 scheduling days and 14 appointment days will send a total scheduling window of 27 days(7+2 and 14+4 = 27). This calculation may differ when process type is selected as Distributed (Separate date calculation is used for date calculation of population period).

You can set up the dataset to be applicable for one or more sites within the company. Following is a list of data that will be transferred for scheduling from the relevant site(s):

Note: In Planning and Scheduling Optimization (PSO), permission groups define which users are allowed to view a set of resources (employees in IFS Applications) and activities (work tasks - resource demands). These permission groups are called object groups. In the integration, object groups have the equivalence of sites in IFS Cloud. This means that in order for a PSO user to be able to view information like resources and activities belonging to a particular site, the user must be connected to the corresponding object group. The object groups for activities and resources are transferred automatically from IFS Cloud to PSO, but object groups for the PSO users must be set up and granted to the users manually from the Scheduling Workbench. The user must also be granted to the dataset itself manually in Scheduling Workbench. It is possible to turn off the functionality to transfer object groups to scheduling by setting the parameter Object Group Filter to None in Service and Maintenance/Scheduling/Basic Data/Scheduling Configuration.

Default values can be entered for the work tasks in the dataset. From these, the default activity type, maximum base value per hour and appointment scheduling type must be entered when setting up the dataset. If a work task is missing a primary scheduling type, secondary scheduling type or an activity type, or if it is an appointment work task which is missing a scheduling type, the default values from the dataset will be assigned automatically to the work task. If a location is missing its do on location incentive value, the default value entered in the dataset will be retrieved to the work task. It is possible to define the lowest status from which work tasks in the dataset can be transferred for scheduling. The default work task status for all datasets is Released and is set for the parameter Dataset Schedule from Work Task Status (Scheduling/Basic Data/Scheduling Configuration). The parameter value can be changed if required and you can also choose to configure this per dataset. Values need to be entered for HR activities, i.e., Lunch and Break, in the dataset as well. The values will be assigned to all lunches and breaks and will be used as an input when scheduling the activities.

It is possible to connect a Modelling Dataset ID to the scheduling dataset. A modelling dataset allows combining modelling data configured in the Advanced Resource Planner (ARP) to be used with the scheduling dataset. Modelling datasets are set up in Scheduling Workbench - Administration and the modelling data is set up in Scheduling Workbench - Planning - Data Management. The scheduling dataset must specify a Modelling Dataset ID to extract and utilize the modelling data.

Scheduling Dispatch Service (DSP) can be Activate/Deactivate from scheduling dataset page - The Schedule Dispatch Service will commit/uncommit (assign/unassign) work task activities automatically, once they have been allocated by the DSE, and the broadcast for this allocation type will be used to communicate with the DSP. For the DSP to operate, it requires a rule set. These are stored as a rules in ARP.

Plannable Task Types

The dataset controls task types to be sent for scheduling:

Child Dataset

If Process type is selected as Distributed, the user can enter data into Child Dataset. It needs to be one Primary dataset with Process Type Dynamic or Appointment one or more static datasets.

Prerequisites

System Effects