Predictive Maintenance Incident Log

This dataset provides a comprehensive log of predictive maintenance incidents in advanced manufacturing environments, detailing machine failures, sensor anomalies, maintenance actions, downtime, and associated costs. It enables operations managers and AI engineers to analyze equipment reliability, optimize preventive strategies, and model risk for improved uptime and cost efficiency.

  • opened 7 times
  • last updated 11 Dec 2025
  • by GoMask
The brief that made it

Failure trend analysis and risk modeling

Sample rows

preview · 8 of 140 rows · all 19 columns
incident_idstringmaintenance_typestringcost_estimatefloatmachine_typestringmachine_idstringlocationstringincident_datetimedatetimeincident_typestringfailure_codestringsensor_idstringsensor_typestringsensor_valuefloatdowntime_minutesintegerreported_bystringresolved_datetimedatetimeresolution_statusstringfailure_descriptionstringmaintenance_actionstringroot_causestring
INCID001blank4500.5CNC Lathe Model XMC-1001APlant A - East Bay2024-05-02T08:15:27machine_failureF103blankblankblank120sys_auto_012024-05-02T10:20:15resolvedSpindle motor overheated causing rapid shutdown.blankInadequate cooling due to blocked air filter.
INCID002blank300Robotic Arm RX-45MC-1002BPlant B - North Wing2024-05-03T09:23:11sensor_anomalyS201SNSR-90812TempSensor102.415tech_joseph2024-05-03T09:38:40resolvedTemperature sensor reported spike above threshold.blankLoose wiring led to false readings.
INCID003preventive800Packaging Line V2MC-1003CPlant A - West Bay2024-05-04T14:05:43maintenance_eventblankblankblankblank45sys_auto_022024-05-04T14:50:59closedScheduled preventive maintenance performed.Lubricated conveyor belt and replaced worn rollers.Routine maintenance per schedule.
INCID004blank2300CNC Lathe Model XMC-1001APlant A - East Bay2024-05-05T07:49:10machine_failureF110blankblankblank75tech_amanda2024-05-05T09:04:11resolvedAxis drive fault detected during startup.blankDrive module firmware corrupted after power outage.
INCID005blank410.75Assembly Robot Z330MC-1004DPlant C - South Gate2024-05-05T11:32:22sensor_anomalyS214SNSR-77643PressureSensor210.720tech_joseph2024-05-05T11:53:10resolvedPressure sensor exceeded max limit during cycle.blankHydraulic seal worn, causing pressure spike.
INCID006blank5100Robotic Arm RX-45MC-1002BPlant B - North Wing2024-05-06T16:10:03machine_failureF120blankblankblank180tech_amanda2024-05-06T19:19:55closedController failed to initialize motion sequence.blankMain relay board shorted due to condensation.
INCID007predictive1700.2Laser Cutter Pro-7MC-1005EPlant D - Central Lane2024-05-07T13:05:47maintenance_eventblankblankblankblank60sys_auto_012024-05-07T14:06:33resolvedPredictive maintenance triggered on laser diode.Replaced laser diode and recalibrated beam alignment.Laser diode nearing end-of-life per sensor data.
INCID008blank2900Injection Molder S100MC-1006FPlant E - South Dock2024-05-08T15:20:59machine_failureF135blankblankblank95tech_susan2024-05-08T16:56:35resolvedNozzle heater failed, causing incomplete molding.blankHeater element burned out, required replacement.

What the 140 rows show

from the 140-row sample

Preventive (maintenance type) stands out: mean cost_estimate is 461.1, against 1,078 for the rest.

  • 515.0median cost_estimate
  • 2resolution statuses
  • 3incident types
  • 18locations
  • 15.8median sensor_value
  • 33median downtime_minutes
Mean cost_estimate by maintenance_type48 rows
01,0002,000461.1preventive18 rows1,202corrective16 rows935.5predictive14 rows
cost_estimate140 rows, in bands of 2,000
060120118128100108,00014kcost_estimate →

Median 515.0, from 17.0 to 12,751.

machine_type140 rows · top 10 of 20 values
  1. Automated Welder ZX-5513
  2. Robotic Arm RX-70012
  3. Hydraulic Press HP-35012
  4. CNC Lathe Model X219
  5. Hydraulic Press Model C9
  6. Robotic Arm Model X8
  7. CNC Lathe Series 48
  8. Packaging Line Model Q8
  9. Laser Cutter Model L8
  10. Packaging Line V27
19 columns by typefrom the column list below
  • string 14
  • integer 1
  • float 2
  • datetime 2

Columns

19 columns in three groups
blueprint · 19 columns
columntypedescriptionexample
Text 14 columns
incident_idstringUnique identifier for each maintenance incidentuniqueINCID001
machine_idstringUnique identifier for the machine involved in the incidentMC-1001A
machine_typestringType or model of the machineCNC Lathe Model X
locationstringPhysical location or plant where the machine is installedPlant A - East Bay
incident_typestringType of incident (e.g., machine_failure, sensor_anomaly, maintenance_event)machine_failure · sensor_anomaly · maintenance_eventmachine_failure
failure_codestringStandardized code representing the failure or anomaly (if applicable)optionalF103
failure_descriptionstringDetailed description of the failure, anomaly, or eventoptionalSpindle motor overheated …
sensor_idstringUnique identifier for the sensor involved (if applicable)optionalSNSR-90812
sensor_typestringType of sensor reporting the anomaly (if applicable)optionalTempSensor
maintenance_typestringType of maintenance performed (e.g., preventive, corrective, predictive)preventive · corrective · predictive · optionalpreventive
maintenance_actionstringDescription of maintenance actions takenoptionalReplaced hydraulic hose.
reported_bystringName or identifier of the person or system that reported the incidentsys_auto_01
resolution_statusstringStatus of the incident (e.g., open, in_progress, resolved, closed)open · in_progress · resolved · closedresolved
root_causestringSummary of root cause analysis (if available)optionalElectrode misalignment.
Numbers 3 columns
sensor_valuefloatSensor reading at the time of incident (if applicable)optional102.4
downtime_minutesintegerTotal downtime in minutes caused by the incident0 or more · optional120
cost_estimatefloatEstimated cost of the incident or maintenance action (in local currency)0 or more · optional4500.5
Dates and times 2 columns
incident_datetimedatetimeDate and time when the incident occurred2024-05-02T08:15:27
resolved_datetimedatetimeDate and time when the incident was resolvedoptional2024-05-02T10:20:15

Use it for

  • median cost es…515.0140 rowsmean cost estimate by…461.1preven…1.2kcorrec…935.5predic…

    A manufacturing dashboard

    Cost_estimate by maintenance_type and a breakdown of machine_type. Excel, Power BI or Tableau.

  • Why do the 18 preventive rows have a mean cost_estimate of 461.1?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable incidents with machine_id, machine_type and location to fill a screen in front of a buyer.

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This dataset140 rows19 columns
Yours1,000 rows19 columnslocation: UK only

blueprint · predictive-maintenance-incident-log

Behind this dataset

Same schema. As many rows as you need.

These 140 rows came out of a blueprint — 19 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each incident record includes timestamp, equipment type, failure type, sensor readings, and maintenance action.
  • Sensor anomalies are flagged with severity levels and require follow-up maintenance within 48 hours.
  • Maintenance actions are classified as scheduled, unscheduled, or emergency.
  • Incident resolution must include root cause analysis and downtime duration.
  • Downtime exceeding 6 hours triggers additional operational review.
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
predictive-maintenance-incident-log

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