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Query the KPI service

📝The KPI service is currently provided through a separate Helm chart. If you want to use for your Rhize installation, get in touch.

The KPI service offers a federated GraphQL interface to query KPI values. This guide provides information on the different querying interfaces.

Root level queries

The KPI service offers two root-level queries:

  • GetKPI()
  • GetKPIByShift()

GetKPI()

The GetKPI() query is the base-level KPI Query. You can use it to input an equipment ID or hierarchy-scope ID, a time range, and a list of desired KPIs. The result is a single KPI object per requested KPI.

GetKPI() - Definition

    query:

    query GetKPI($filterInput: KPIFilter!, $startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean) {
  GetKPI(filterInput: $filterInput, startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime) {
    name
    to
    from
    error
    value
    units
  }
}

    input:

    {
  "filterInput": {
    "equipmentIds": ["MachineA", "MachineB"],
    "hierarchyScopeId": "Enterprise1.SiteA.Line1"
  },
  "startDateTime": "2024-09-01T00:00:00Z",
  "endDateTime": "2024-09-01T18:00:00Z",
  "kpi": ["ActualProductionTime","Availability", "GoodQuantity", "ProducedQuantity", "Effectiveness", "QualityRatio", "ActualCycleTime", "OverallEquipmentEffectiveness"],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false,
  "onlyIncludeActiveJobResponses": false
}

    {
  "data": {
    "GetKPI": [
      {
        "name": "ActualProductionTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
      {
        "name": "ActualUnitDelayTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
      {
        "name": "PlannedDownTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
      {
        "name": "Availability",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "%"
      },
      {
        "name": "GoodQuantity",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "units"
      },
      {
        "name": "ProducedQuantity",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "units"
      },
      {
        "name": "Effectiveness",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 100,
        "units": "%"
      },
      {
        "name": "QualityRatio",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 100,
        "units": "%"
      },
      {
        "name": "ActualCycleTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds per unit"
      },
      {
        "name": "OverallEquipmentEffectiveness",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "%"
      }
    ]
  }
}

    Example 1.

    Imagine a scenario where Machine A produces parts at a planned cycle time of 10-seconds per part. The order starts at 09:00 and finishes at 12:00 with 30 minutes of unplanned downtime in between (this could be from loading materials, unplanned maintenance, switching tools, and so on). After the operation finishes, the user has registered 800 Good parts and 200 scrap parts. The tables in time series appear as follows:

      EquipmentIdISO22400Statetime
      Machine AAPT2024-09-03T09:00:00Z
      Machine AADET2024-09-03T10:30:00Z
      Machine AAPT2024-09-03T11:00:00Z
      Machine AADOT2024-09-03T12:00:00Z
      EquipmentIdOriginQtyTypeProductionTypeQtytime
      Machine AUserDeltaGood8002024-09-03T12:00:00Z
      Machine AUserDeltaScrap2002024-09-03T12:00:00Z
      EquipmentIdJobOrderIdPlanningCyleTimetime
      Machine AOrder A102024-09-03T09:00:00Z
      Machine ANONE02024-09-03T12:00:00Z

      Calling this KPI Query appears as follows:

        query:

        query GetKPI($filterInput: KPIFilter!, $startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean) {
  GetKPI(filterInput: $filterInput, startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime) {
    name
    to
    from
    error
    value
    units
  }
}

        input:

        {
  "filterInput": {
    "equipmentIds": ["MachineA"]
  },
  "startDateTime": "2024-09-03T09:00:00Z",
  "endDateTime": "2024-09-03T12:00:00Z",
  "kpi": ["ActualProductionTime","Availability", "GoodQuantity", "ProducedQuantity", "Effectiveness", "QualityRatio", "ActualCycleTime", "OverallEquipmentEffectiveness"]
}

        {
  "data": {
    "GetKPI": [
      {
        "_comment": "This is the total time spent in APT",
        "name": "ActualProductionTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 9000,
        "units": "seconds"
      },
      {
        "_comment": "This is the total time spent in ADET",
        "name": "ActualUnitDelayTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 1800,
        "units": "seconds"
      },
      {
        "_comment": "This is the total time spent in PDOT",
        "name": "PlannedDownTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
      {
        "_comment": "This is APT/PBT",
        "name": "Availability",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 83.3333333,
        "units": "%"
      },
      {
        "_comment": "This is the total recorded good quantity",
        "name": "GoodQuantity",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 800,
        "units": "units"
      },
      {
        "_comment": "This is the total quantity produced in the order",
        "name": "ProducedQuantity",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 1000,
        "units": "units"
      },
      {"_comment": "This is (ProducedQuantity * PlannedCycleTime)/APT",
        "name": "Effectiveness",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 111.111111,
        "units": "%"
      },
      {
        "_comment": "This is GoodQuantity/ProducedQuantity",
        "name": "QualityRatio",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 80,
        "units": "%"
      },
      {
        "_comment": "This is APT/ProducedQuantity",
        "name": "ActualCycleTime",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 10.8,
        "units": "seconds per unit"
      },
      {
        "_comment": "This is Availability * Effectiveness * QualityRatio",
        "name": "OverallEquipmentEffectiveness",
        "to": "2024-09-01T18:00:00Z",
        "from": "2024-09-01T00:00:00Z",
        "error": null,
        "value": 74.074,
        "units": "%"
      }
    ]
  }
}

        GetKPIByShift()

        The GetKPIByShift() query is another base-level KPI Query. It is similar to GetKPI(), but rather than returning a single result per KPI query, it also accepts WorkCalendarEntryProperty IDs to filter against and return a result for each instance of a shift.

        GetKPIByShift() - Definition

          query:

          query GetKPIByShift($filterInput: GetKPIByShiftFilter!, $startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean, $groupByShift: Boolean, $groupByEquipment: Boolean, $onlyIncludeActiveJobResponses: Boolean) {
  GetKPIByShift(filterInput: $filterInput, startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime, groupByShift: $groupByShift, groupByEquipment: $groupByEquipment, OnlyIncludeActiveJobResponses: $onlyIncludeActiveJobResponses) {
    name
    equipmentIds
    shiftsContained
    from
    to
    error
    value
    units
  }
}

          input:

          {
  "filterInput": {
    "shiftFilter": [
      {
        "propertyName": "Shift Name",
        "eq": "Morning"
      }
    ],
    "equipmentIds": ["Machine A", "Machine B"],
    "hierarchyScopeId": "Enterprise1.SiteA.Line1"
  },
  "startDateTime": "2024-09-01T00:00:00Z",
  "endDateTime": "2024-09-03T18:00:00Z",
  "kpi": ["ActualProductionTime", "OverallEquipmentEffectiveness"],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false,
  "onlyIncludeActiveJobResponses": false,
  "groupByShift": false,
  "groupByEquipment": true
}

          {
  "data": {
    "GetKPIByShift": [
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Sunday.Morning"],
        "from": "2024-09-01T09:00:00Z",
        "to": "2024-09-01T17:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Monday.Morning"],
        "from": "2024-09-02T00:00:00Z",
        "to": "2024-09-02T17:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Tuesday.Morning"],
        "from": "2024-09-03T00:00:00Z",
        "to": "2024-09-03T17:00:00Z",
        "error": null,
        "value": 0,
        "units": "seconds"
      },
       {
        "name": "OverallEquipmentEffectiveness",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Sunday.Morning"],
        "from": "2024-09-01T09:00:00Z",
        "to": "2024-09-01T17:00:00Z",
        "error": null,
        "value": 0,
        "units": "%"
      },
      {
        "name": "OverallEquipmentEffectiveness",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Monday.Morning"],
        "from": "2024-09-02T00:00:00Z",
        "to": "2024-09-02T17:00:00Z",
        "error": null,
        "value": 0,
        "units": "%"
      },
      {
        "name": "OverallEquipmentEffectiveness",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Tuesday.Morning"],
        "from": "2024-09-03T00:00:00Z",
        "to": "2024-09-03T17:00:00Z",
        "error": null,
        "value": 0,
        "units": "%"
      },
    ]
  }
}

          Example 2

          Following on from Example 1. Machine A exists on a production line alongside Machine B, they both produce parts with a planned cycle time of 10 seconds per part and runs on the same shift pattern. The work calendar service is configured with 3 distinct daily shifts:

          • Morning (06:00-14:00)
          • Afternoon (14:00 - 22:00)
          • Night (22:00-06:00)

          Which results in the following tables:

            EquipmentIdISO22400Statetime
            Machine AAPT2024-09-01T06:00:00Z
            Machine BAPT2024-09-01T06:00:00Z
            Machine AADET2024-09-01T10:30:00Z
            Machine BADET2024-09-01T10:30:00Z
            Machine AAPT2024-09-01T11:00:00Z
            Machine BAPT2024-09-01T11:00:00Z
            Machine AADOT2024-09-01T14:00:00Z
            Machine BADOT2024-09-01T14:00:00Z
            Machine AAPT2024-09-01T14:00:00Z
            Machine BAPT2024-09-01T14:00:00Z
            Machine AADET2024-09-01T17:30:00Z
            Machine BADET2024-09-01T17:30:00Z
            Machine AAPT2024-09-01T18:00:00Z
            Machine BAPT2024-09-01T18:00:00Z
            Machine AADOT2024-09-01T22:00:00Z
            Machine BADOT2024-09-01T22:00:00Z
            Machine AAPT2024-09-01T22:00:00Z
            Machine BAPT2024-09-01T22:00:00Z
            Machine AADET2024-09-02T04:00:00Z
            Machine BADET2024-09-02T04:00:00Z
            Machine AAPT2024-09-02T04:30:00Z
            Machine BAPT2024-09-02T04:30:00Z
            Machine AADOT2024-09-02T06:00:00Z
            Machine BADOT2024-09-02T06:00:00Z
            Machine AAPT2024-09-02T06:00:00Z
            Machine BAPT2024-09-02T06:00:00Z
            Machine AADET2024-09-02T10:30:00Z
            Machine BADET2024-09-02T10:30:00Z
            Machine AAPT2024-09-02T11:00:00Z
            Machine BAPT2024-09-02T11:00:00Z
            Machine AADOT2024-09-02T14:00:00Z
            Machine BADOT2024-09-02T14:00:00Z
            Machine AAPT2024-09-02T14:00:00Z
            Machine BAPT2024-09-02T14:00:00Z
            Machine AADET2024-09-02T18:30:00Z
            Machine BADET2024-09-02T18:30:00Z
            Machine AAPT2024-09-02T19:00:00Z
            Machine BAPT2024-09-02T19:00:00Z
            Machine AADOT2024-09-02T22:00:00Z
            Machine BADOT2024-09-02T22:00:00Z
            Machine AAPT2024-09-02T22:00:00Z
            Machine BAPT2024-09-02T22:00:00Z
            Machine AADET2024-09-03T04:30:00Z
            Machine BADET2024-09-03T04:30:00Z
            Machine AAPT2024-09-03T05:00:00Z
            Machine BAPT2024-09-03T05:00:00Z
            Machine AADOT2024-09-03T06:00:00Z
            Machine BADOT2024-09-03T06:00:00Z
            EquipmentIdOriginQtyTypeProductionTypeQtytime
            Machine AUserDeltaGood8002024-09-01T14:00:00Z
            Machine AUserDeltaScrap2002024-09-01T14:00:00Z
            Machine BUserDeltaGood7002024-09-01T14:00:00Z
            Machine BUserDeltaScrap3002024-09-01T14:00:00Z
            Machine AUserDeltaGood9002024-09-01T22:00:00Z
            Machine AUserDeltaScrap1002024-09-01T22:00:00Z
            Machine BUserDeltaGood9502024-09-01T22:00:00Z
            Machine BUserDeltaScrap502024-09-01T22:00:00Z
            Machine AUserDeltaGood9992024-09-01T06:00:00Z
            Machine AUserDeltaScrap12024-09-01T06:00:00Z
            Machine BUserDeltaGood9002024-09-01T06:00:00Z
            Machine BUserDeltaScrap1002024-09-01T06:00:00Z
            Machine AUserDeltaGood8502024-09-02T14:00:00Z
            Machine AUserDeltaScrap1502024-09-02T14:00:00Z
            Machine BUserDeltaGood8002024-09-02T14:00:00Z
            Machine BUserDeltaScrap2002024-09-02T14:00:00Z
            Machine AUserDeltaGood7002024-09-02T22:00:00Z
            Machine AUserDeltaScrap3002024-09-02T22:00:00Z
            Machine BUserDeltaGood7502024-09-02T22:00:00Z
            Machine BUserDeltaScrap2502024-09-02T22:00:00Z
            Machine AUserDeltaGood6002024-09-02T06:00:00Z
            Machine AUserDeltaScrap4002024-09-02T06:00:00Z
            Machine BUserDeltaGood7502024-09-02T06:00:00Z
            Machine BUserDeltaScrap2502024-09-02T06:00:00Z
            EquipmentIdJobOrderIdPlanningCyleTimetime
            Machine AOrder A1102024-09-01T06:00:00Z
            Machine BOrder A2102024-09-01T06:00:00Z
            Machine ANONE02024-09-01T14:00:00Z
            Machine BNONE02024-09-01T14:00:00Z
            Machine AOrder B1102024-09-01T14:00:00Z
            Machine BOrder B2102024-09-01T14:00:00Z
            Machine ANONE02024-09-01T22:00:00Z
            Machine BNONE02024-09-01T22:00:00Z
            Machine AOrder C1102024-09-01T22:00:00Z
            Machine BOrder C2102024-09-01T22:00:00Z
            Machine ANONE02024-09-02T06:00:00Z
            Machine BNONE02024-09-02T06:00:00Z
            Machine AOrder D1102024-09-02T06:00:00Z
            Machine BOrder D2102024-09-02T06:00:00Z
            Machine ANONE02024-09-02T14:00:00Z
            Machine BNONE02024-09-02T14:00:00Z
            Machine AOrder E1102024-09-02T14:00:00Z
            Machine BOrder E2102024-09-02T14:00:00Z
            Machine ANONE02024-09-02T22:00:00Z
            Machine BNONE02024-09-02T22:00:00Z
            Machine AOrder F1102024-09-02T22:00:00Z
            Machine BOrder F2102024-09-02T22:00:00Z
            Machine ANONE02024-09-03T06:00:00Z
            Machine BNONE02024-09-03T06:00:00Z
            EquipmentIdWorkCalendarDefinitionIDWorkCalendarDefinitionEntryIdEntryTypetime
            Machine AShiftCalendarShiftCalendar.Sunday.MorningSTART2024-09-01T06:00:00Z
            Machine BShiftCalendarShiftCalendar.Sunday.MorningSTART2024-09-01T06:00:00Z
            Machine AShiftCalendarShiftCalendar.Sunday.MorningEND2024-09-01T14:00:00Z
            Machine BShiftCalendarShiftCalendar.Sunday.MorningEND2024-09-01T14:00:00Z
            Machine AShiftCalendarShiftCalendar.Sunday.AfternoonSTART2024-09-01T14:00:00Z
            Machine BShiftCalendarShiftCalendar.Sunday.AfternoonSTART2024-09-01T14:00:00Z
            Machine AShiftCalendarShiftCalendar.Sunday.AfternoonEND2024-09-01T22:00:00Z
            Machine BShiftCalendarShiftCalendar.Sunday.AfternoonEND2024-09-01T22:00:00Z
            Machine AShiftCalendarShiftCalendar.Sunday.NightSTART2024-09-01T22:00:00Z
            Machine BShiftCalendarShiftCalendar.Sunday.NightSTART2024-09-01T22:00:00Z
            Machine AShiftCalendarShiftCalendar.Sunday.NightEND2024-09-02T06:00:00Z
            Machine BShiftCalendarShiftCalendar.Sunday.NightEND2024-09-02T06:00:00Z
            Machine AShiftCalendarShiftCalendar.Monday.MorningSTART2024-09-02T06:00:00Z
            Machine BShiftCalendarShiftCalendar.Monday.MorningSTART2024-09-02T06:00:00Z
            Machine AShiftCalendarShiftCalendar.Monday.MorningEND2024-09-02T14:00:00Z
            Machine BShiftCalendarShiftCalendar.Monday.MorningEND2024-09-02T14:00:00Z
            Machine AShiftCalendarShiftCalendar.Monday.AfternoonSTART2024-09-02T14:00:00Z
            Machine BShiftCalendarShiftCalendar.Monday.AfternoonSTART2024-09-02T14:00:00Z
            Machine AShiftCalendarShiftCalendar.Monday.AfternoonEND2024-09-02T22:00:00Z
            Machine BShiftCalendarShiftCalendar.Monday.AfternoonEND2024-09-02T22:00:00Z
            Machine AShiftCalendarShiftCalendar.Monday.NightSTART2024-09-02T22:00:00Z
            Machine BShiftCalendarShiftCalendar.Monday.NightSTART2024-09-02T22:00:00Z
            Machine AShiftCalendarShiftCalendar.Monday.NightEND2024-09-03T06:00:00Z
            Machine BShiftCalendarShiftCalendar.Monday.NightEND2024-09-03T06:00:00Z

            You can run this query in multiple ways:

            • groupByEquipment = false and groupByShift = false - returns a separate result per shift instance per equipment

              query:

              query GetKPIByShift($filterInput: GetKPIByShiftFilter!, $startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean, $groupByShift: Boolean, $groupByEquipment: Boolean, $onlyIncludeActiveJobResponses: Boolean) {
  GetKPIByShift(filterInput: $filterInput, startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime, groupByShift: $groupByShift, groupByEquipment: $groupByEquipment, OnlyIncludeActiveJobResponses: $onlyIncludeActiveJobResponses) {
    name
    equipmentIds
    shiftsContained
    from
    to
    error
    value
    units
  }
}

              input:

              {
  "filterInput": {
    "shiftFilter": [
      {
        "propertyName": "Shift Name",
        "eq": "Morning"
      }
    ],
    "equipmentIds": ["Machine A", "Machine B"],
  },
  "startDateTime": "2024-09-01T00:00:00Z",
  "endDateTime": "2024-09-03T18:00:00Z",
  "kpi": ["ActualProductionTime"],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false,
  "onlyIncludeActiveJobResponses": false,
  "groupByShift": false,
  "groupByEquipment": false
}

              {
  "data": {
    "GetKPIByShift": [
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A"],
        "shiftsContained": ["Shift.Sunday.Morning"],
        "from": "2024-09-01T06:00:00Z",
        "to": "2024-09-01T14:00:00Z",
        "error": null,
        "value": 27000,
        "units": "seconds"
      },
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine B"],
        "shiftsContained": ["Shift.Sunday.Morning"],
        "from": "2024-09-01T06:00:00Z",
        "to": "2024-09-01T14:00:00Z",
        "error": null,
        "value": 27000,
        "units": "seconds"
      },
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A"],
        "shiftsContained": ["Shift.Monday.Morning"],
        "from": "2024-09-02T06:00:00Z",
        "to": "2024-09-02T14:00:00Z",
        "error": null,
        "value": 27000,
        "units": "seconds"
      },
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine B"],
        "shiftsContained": ["Shift.Monday.Morning"],
        "from": "2024-09-02T06:00:00Z",
        "to": "2024-09-02T14:00:00Z",
        "error": null,
        "value": 27000,
        "units": "seconds"
      }
    ]
  }
}
              • groupByEquipment = true and groupByShift = false - returns a separate result per shift instance containing all equipment

                query:

                query GetKPIByShift($filterInput: GetKPIByShiftFilter!, $startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean, $groupByShift: Boolean, $groupByEquipment: Boolean, $onlyIncludeActiveJobResponses: Boolean) {
  GetKPIByShift(filterInput: $filterInput, startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime, groupByShift: $groupByShift, groupByEquipment: $groupByEquipment, OnlyIncludeActiveJobResponses: $onlyIncludeActiveJobResponses) {
    name
    equipmentIds
    shiftsContained
    from
    to
    error
    value
    units
  }
}

                input:

                {
  "filterInput": {
    "shiftFilter": [
      {
        "propertyName": "Shift Name",
        "eq": "Morning"
      }
    ],
    "equipmentIds": ["Machine A", "Machine B"],
  },
  "startDateTime": "2024-09-01T00:00:00Z",
  "endDateTime": "2024-09-03T18:00:00Z",
  "kpi": ["ActualProductionTime"],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false,
  "onlyIncludeActiveJobResponses": false,
  "groupByShift": false,
  "groupByEquipment": true
}

                {
  "data": {
    "GetKPIByShift": [
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Sunday.Morning"],
        "from": "2024-09-01T06:00:00Z",
        "to": "2024-09-01T14:00:00Z",
        "error": null,
        "value": 54000,
        "units": "seconds"
      },
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Monday.Morning"],
        "from": "2024-09-02T06:00:00Z",
        "to": "2024-09-02T14:00:00Z",
        "error": null,
        "value": 54000,
        "units": "seconds"
      }

    ]
  }
}
                • groupByEquipment = true and groupByShift = true - groups shifts and equipment together

                  query:

                  query GetKPIByShift($filterInput: GetKPIByShiftFilter!, $startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean, $groupByShift: Boolean, $groupByEquipment: Boolean, $onlyIncludeActiveJobResponses: Boolean) {
  GetKPIByShift(filterInput: $filterInput, startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime, groupByShift: $groupByShift, groupByEquipment: $groupByEquipment, OnlyIncludeActiveJobResponses: $onlyIncludeActiveJobResponses) {
    name
    equipmentIds
    shiftsContained
    from
    to
    error
    value
    units
  }
}

                  input:

                  {
  "filterInput": {
    "shiftFilter": [
      {
        "propertyName": "Shift Name",
        "eq": "Morning"
      }
    ],
    "equipmentIds": ["Machine A", "Machine B"],
  },
  "startDateTime": "2024-09-01T00:00:00Z",
  "endDateTime": "2024-09-03T18:00:00Z",
  "kpi": ["ActualProductionTime"],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false,
  "onlyIncludeActiveJobResponses": false,
  "groupByShift": true,
  "groupByEquipment": true
}

                  {
  "data": {
    "GetKPIByShift": [
      {
        "name": "ActualProductionTime",
        "equipmentIds": ["Machine A", "Machine B"],
        "shiftsContained": ["Shift.Sunday.Morning","Shift.Monday.Morning"],
        "from": "2024-09-01T06:00:00Z",
        "to": "2024-09-01T14:00:00Z",
        "error": null,
        "value": 108000,
        "units": "seconds"
      }

    ]
  }
}

                  Federated Queries

                  The KPI service extends the equipment, work schedule, work request, job order, and job response GraphQL entities with a KPI object. This makes KPIs easier to query.

                  Query Equipment

                  Extending the equipment type allows the equipment ID to be inferred from parent equipment type

                    query:

                    query QueryEquipment($startDateTime: DateTime!, $endDateTime: DateTime!, $kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean) {
  queryEquipment {
    id
    kpi(startDateTime: $startDateTime, endDateTime: $endDateTime, kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime) {
      name
      from
      to
      error
      value
      units
    }
  }
}

                    input:

                    {
  "startDateTime": "2024-09-01T06:00:00Z",
  "endDateTime": "2024-09-01T14:00:00Z",
  "kpi": ["ActualProductionTime"],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false
}

                    {
  "data": {
    "queryEquipment": [
      {
        "id": "Machine A",
        "kpi": [
          {
            "name": "ActualProductionTime",
            "from": "2024-09-01T06:00:00Z",
            "to": "2024-09-01T14:00:00Z",
            "error": null,
            "value": 27000,
            "units": "seconds"
          }
        ]
      },
      {
        "id": "Machine B",
        "kpi": [
          {
            "name": "ActualProductionTime",
            "from": "2024-09-01T06:00:00Z",
            "to": "2024-09-01T14:00:00Z",
            "error": null,
            "value": 27000,
            "units": "seconds"
          }
        ]
      }
    ]
  }
}

                    Query JobResponse

                    Extending the job response type allows:

                    • startDateTime to be inferred from jobResponse.startDateTime
                    • endDateTime to be inferred from jobResponse.endDateTime
                    • equipmentIds to be inferred from jobResponse.equipmentActual.EquipmentVersion.id

                      query:

                      query QueryJobResponse($kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean, $filter: KPIFilter) {
  queryJobResponse {
    id
    startDateTime
    endDateTime
    equipmentActual {
      id
      equipmentVersion {
        id
      }
    }
    kpi(kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime, filter: $filter) {
      name
      from
      to
      error
      value
      units
    }
  }
}

                      input:

                      {
  "kpi": [
    "ActualProductionTime"
  ],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false
}

                      {
  "data": {
    "queryJobResponse": [
      {
        "id": "Order A1.JobResponse 1",
        "startDateTime": "2024-09-01T08:00:00Z",
        "endDateTime": "2024-09-01T14:00:00Z",
        "equipmentActual": [
          {
            "id": "Machine A.2024-09-01T08:00:00Z",
            "equipmentVersion": {
              "id": "Machine A"
            }
          }
        ],
        "kpi": [
          {
            "name": "ActualProductionTime",
            "from": "2024-09-01T08:00:00Z",
            "to": "2024-09-01T14:00:00Z",
            "error": null,
            "value": 27000,
            "units": "seconds"
          }
        ]
      }
    ]
  }
}

                      Query Job Order, Work Request, and Work Schedule

                      Extending the Job order, Work Request, and Work Schedule entities makes it possible to recursively query all of the attached job responses:

                      flowchart TD
    WorkSchedule --> WorkRequests
    WorkRequests --> JobOrders
    JobOrders --> JobResponses

                      Imagine that from the data from example 2 has this hierarchy:

                      flowchart TD
    WorkScheduleA --> WorkRequestA
    WorkScheduleA --> WorkRequestB
    WorkRequestA --> OrderA1
    WorkRequestA --> OrderA2
    WorkRequestB --> OrderB1
    WorkRequestB --> OrderC1

                      Querying KPI on workSchedule A combines all results for order A1, A2, B1 and C1:

                        query:

                        query QueryWorkSchedule($kpi: [KPI!], $ignorePlannedDownTime: Boolean, $ignorePlannedShutdownTime: Boolean, $filter: KPIFilter) {
  queryWorkSchedule {
    id
    kpi(kpi: $kpi, ignorePlannedDownTime: $ignorePlannedDownTime, ignorePlannedShutdownTime: $ignorePlannedShutdownTime, filter: $filter) {
      name
      from
      to
      error
      value
      units
    }
  }
}

                        input:

                        {
  "kpi": [
    "ActualProductionTime"
  ],
  "ignorePlannedDownTime": false,
  "ignorePlannedShutdownTime": false
}

                        {
  "data": {
    "queryWorkSchedule": [
      {
        "id": "WorkScheduleA",
        "kpi": [
          {
            "name": "ActualProductionTime",
            "from": "2024-09-01T08:00:00Z",
            "to": "2024-09-02T06:00:00Z",
            "error": null,
            "value": 108000,
            "units": "seconds"
          }
        ]
      }
    ]
  }
}

                        Additional Filters

                        Some KPI Queries provide additional filters that are not mentioned in the preceding examples:

                        • ignorePlannedDownTime (default: false) - Ignores planned down time events. For example if a state change happens while in the planned downtime calendar state, by default it is ignored. If ignorePlannedDowntime = true, the underlying state change is still returned.
                        • ignorePlannedShutdownTime (default: false). Similar to ignorePlannedDowntime except with planned shutdown calendar events.
                        • onlyIncludeActiveJobResponses (default: false) - if set to true will adjust the time interval of the KPI query to only be whilst a job response is active. For example if a user queries a KPI between 00:00 - 23:59 but there are only active job responses from 08:00-19:00, the query time range would be adjusted to 08:00-19:00.