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Kaggle

Industrial Equipment Maintenance Data

Industrial IoT
Jan 13, 2026
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Abstract

"Real-time sensor data for industrial equipment with maintenance history. Designed for developing predictive maintenance models, failure mode analysis, and maintenance planning systems."

Description

Dataset Overview

Comprehensive industrial maintenance dataset combining continuous sensor monitoring with historical maintenance records. Covers various equipment types in manufacturing environments with real-world failure modes and repair costs.

Equipment Coverage

  • Motor-driven machinery (pumps, compressors, fans)
  • Rotating equipment (bearings, gearboxes)
  • Heat exchangers
  • Hydraulic systems
  • Electrical switchgear

Sensor Data

  • Mechanical Sensors: Vibration (acceleration, velocity), temperature
  • Electrical Sensors: Current draw (A), power consumption (kW), voltage (V)
  • Operational Data: Run hours, speed (RPM), load percentage
  • Maintenance Records: Work orders, repair costs, downtime hours

Data Characteristics

  • Records: 10,000+ equipment observations
  • Time Period: 2+ years operational history
  • Failure Modes: 20+ documented failure types
  • Label Balance: 70% normal, 30% failure-prone equipment

Research Applications

Predictive maintenance model development, remaining useful life estimation, failure classification, maintenance cost optimization, and condition-based maintenance planning.

Data Preview

Equipment_IDTimestampVibration_mm_sTemperature_CCurrent_ARun_HoursFailure_Status
PUMP_0012024-01-15 10:303.268.512.415840Normal
MOTOR_0022024-01-15 10:308.992.318.724560Failure_Risk
PUMP_0012024-01-15 11:003.569.112.615870Normal

Showing first few rows for preview

Cite This Dataset

Kaggle (2026). Industrial Equipment Maintenance Data. [Dataset]. Kaggle. https://www.kaggle.com/datasets/mayurgadekar5555/industrial-equipment-maintenance-data

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Original source: Kaggle (2026). Visit official page for more details.

Indexed by IoTDataset.com on Jan 13, 2026

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