Smart Factory Sensor Output Data

This dataset contains detailed time-stamped sensor readings from advanced manufacturing lines, including machine, line, and factory identifiers, sensor types and values, operational statuses, and anomaly flags. It enables granular analysis for predictive maintenance, process optimization, and real-time anomaly detection, supporting data-driven manufacturing operations.

  • last updated 5 Sept 2025
  • by GoMask
The brief that made it

Predictive maintenance and failure prevention

Sample rows

preview · 8 of 200 rows · all 15 columns
reading_idstringstatusstringsensor_valuefloatanomaly_flagbooleanline_idstringtimestampdatetimefactory_idstringmachine_idstringsensor_idstringsensor_typestringsensor_unitstringmaintenance_requiredbooleanoperator_idstringlocation_zonestringremarksstring
A1-00001normal22.5falseLN-A012024-05-21T08:15:00ZFCT-NORTH-001MC-1001S-1001-TEMPtemperatureCelsiusfalseOP-2001Zone-ARoutine temperature check, all values within range.
B2-00002normal2.1falseLN-B012024-05-21T12:45:00ZFCT-SOUTH-002MC-1020S-1020-VIBvibrationmm/sfalseOP-2002Zone-BVibration levels stable during midday production.
C3-00003error99.8trueLN-C012024-05-21T23:59:00ZFCT-EAST-003MC-1050S-1050-HUMhumidity%RHtrueblankZone-EHumidity spike detected, possible condensation risk.
D4-00004normal8.3falseLN-D092024-05-22T06:00:00ZFCT-WEST-004MC-1075S-1075-PRSRpressurebarfalseOP-2003Zone-FPressure reading within safe operating limits.
A1-00005warning58.2trueLN-A012024-05-22T15:30:00ZFCT-NORTH-001MC-1015S-1015-TEMPtemperatureCelsiustrueOP-2004Zone-GTemperature exceeded safe threshold, review required.
B2-00006normal14.3falseLN-B012024-05-22T17:45:00ZFCT-SOUTH-002MC-1025S-1025-CURRcurrentAmpfalseOP-2005Zone-HCurrent draw stable during afternoon shift.
C3-00007error995trueLN-C052024-05-23T02:30:00ZFCT-EAST-003MC-1060S-1060-VOLTvoltageVolttrueblankZone-IVoltage surge detected, machine auto shutdown.
D4-00008normal1468falseLN-D092024-05-23T09:10:00ZFCT-WEST-004MC-1082S-1082-SPDspeedrpmfalseOP-2006Zone-JMachine speed consistent with scheduled production rate.

What the 200 rows show

from the 200-row sample

Error status stands out: 34 of its 34 rows have anomaly_flag = true, against 24 of 166 for the rest.

  • 29%anomaly_flag = true
  • 11.7median sensor_value
  • 4factories
  • 8sensor types
  • 11sensor units
  • 13location zones
Anomaly flag rate by statusanomaly_flag = true
0%50%100%0%normal0 of 98100%warning24 of 24100%error34 of 340%offline0 of 44
sensor_value200 rows, in bands of 1,000
090180517413008-1,0002,0005,000sensor_value →

Median 11.7, from -5.0 to 5,000.

line_id200 rows · top 10 of 39 values
  1. LN-A0125
  2. LN-D0925
  3. LN-C0524
  4. LN-B0123
  5. LN-C0120
  6. LN-E058
  7. LN-F047
  8. LN-C026
  9. LN-D025
  10. LN-A095
15 columns by typefrom the column list below
  • string 11
  • float 1
  • datetime 1
  • boolean 2

Columns

15 columns in four groups
blueprint · 15 columns
columntypedescriptionexample
Text 11 columns
reading_idstringUnique identifier for each sensor reading recorduniqueA1-00001
factory_idstringUnique identifier for the factory where the sensor is located4 factoriesFCT-NORTH-001
line_idstringUnique identifier for the production line within the factoryLN-A01
machine_idstringUnique identifier for the machine generating the sensor readingMC-1001
sensor_idstringUnique identifier for the sensor deviceS-1001-TEMP
sensor_typestringType of sensor (e.g., temperature, vibration, pressure, humidity)8 valuestemperature
sensor_unitstringMeasurement unit for the sensor value (e.g., Celsius, mm/s, bar, %RH)11 unitsCelsius
statusstringOperational status of the sensor at the time of readingnormal · warning · error · offlinenormal
operator_idstringIdentifier for the operator responsible for the machine at the time of readingoptionalOP-2001
location_zonestringPhysical zone or area within the factory where the machine is locatedoptionalZone-A
remarksstringAdditional notes or comments related to the sensor readingoptionalRoutine temperature check…
Numbers 1 column
sensor_valuefloatMeasured value from the sensor at the given timestamp22.5
Dates and times 1 column
timestampdatetimeDate and time when the sensor reading was captured2024-05-21T08:15:00Z
True or false 2 columns
anomaly_flagbooleanIndicates if the reading is flagged as an anomalyfalse
maintenance_requiredbooleanIndicates if the machine requires maintenance based on the readingoptionalfalse

Use it for

  • anomaly flag29%58 of 200 rowsmean sensor value by …160.4norm…354.6warn…929.8error229.4offl…

    A manufacturing dashboard

    The anomaly_flag rate, sensor_value by status and a breakdown of line_id. Excel, Power BI or Tableau.

  • Why do 58 of 200 rows have anomaly_flag = true?

    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 readings with timestamp, factory_id and line_id to fill a screen in front of a buyer.

Not quite right?

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This dataset200 rows15 columns
Yours1,000 rows15 columnslocation_zone: UK only

blueprint · smart-factory-sensor-output-data

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 15 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
  • Time-stamped readings per sensor.
  • Sensors mapped to production machines.
  • Includes error codes for failure events.
  • Temperature, vibration, and humidity measured.
  • Devices may be offline intermittently.
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
smart-factory-sensor-output-data

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