Predictive Maintenance Fleet

• Remaining useful life (RUL) regression

  with rul_days or true_rul_days, and failure within 30 days classification with fails_within_30d (5.7% positive, the realistic imbalance).

• Survival analysis

  238 runs are right-censored at the cut-off and 194 were ended early by a repair or replacement; Weibull, Cox and Kaplan-Meier on runs.csv with load, climate and failure mode as covariates.

• Anomaly detection and alarm tuning

  the alarms are rule-based (ISO zone, temperature, pressure, current, debris); beat them with a model, and measure false alarms against lead time.

• Failure mode diagnosis

  from the sensor signature: vibration for bearings, imbalance and misalignment, temperature for lubrication, pressure for impellers and seals, current for windings, oil debris for gears.

• Maintenance strategy and cost

  run-to-failure against condition-based against age-based replacement; breakdowns cost a median $29,513 against $9,692 for a condition-based repair.

• Dashboards and teaching

  MTBF, MTTR, availability, backlog, PM compliance, cost by site and criticality in Power BI, Tableau or SQL; a reliability engineering course or a CMMS demo.

• runs.failure_modeThe true failure mode of the life, which sets the signals that move.8 values: bearing wear, shaft misalignment, seal leak…
• runs.true_life_daysHow long the life lasts to failure if nothing intervenes; a run caught or replaced early ends before it.70.9 to 2,921.1, mean 433.3
• runs.true_failure_atWhen the machine would fail, including for runs that were caught or renewed first.2024-01-10 08:59:05 to 2033-06-10 20:20:16
• runs.warning_signsWhether the failure gives signs a sensor can see, or comes suddenly.true on 82.3% of rows
• runs.pf_onsetThe share of the life at which the signals start to rise (the P on the P-F curve); near 1 for sudden failures.0.55 to 0.98, mean 0.69
• readings.life_usedThe share of the run's true life used at the reading.0 to 1, mean 0.46, 0.79% empty
• readings.rul_daysDays left until the run ends, however it ends.0 to 720.3, mean 158.2, 34.9% empty
• readings.true_rul_daysDays left until the true failure: the remaining-useful-life target.0 to 2,920.3, mean 313.8, 0.79% empty
• readings.fails_within_30dWhether the machine truly fails within 30 days: the classification target.true on 5.7% of rows, 3.9% empty

• Signals stay flat for most of a life, then rise along a P-F curve: median vibration on vibration-type failures goes 1.57 -> 1.63 -> 2.46 -> 8.46 mm/s from new to the last 3% of life.
• 91% of warned and 5% of sudden failures gave a sustained alarm first, median 41 days ahead. 21% of failures were sudden: some faults give no warning a sensor can see.
• Harder-worked machines live shorter (bearings with the cube of load): Spearman -0.57 between load factor and true life; hot sites wear machines out sooner (median true life 268 against 351 days).
• Near the end of a life, bearing temperature is 61 C against 42 C for bearing and lubrication failures against other modes; discharge pressure falls to 77% of nominal against 96% for impeller and seal failures.
• Breakdowns keep a machine down a median 51 h against 6 h for planned work; lost production is $20,543,709 of the $21,992,407 maintenance cost.
• Runs: 326 failures, 105 caught by monitoring, 89 age-based replacements, 238 still running at the cut-off. Sensor dropouts: about 0.8% of readings.

• every key resolves; one reading per asset per day for all 731 days; runs of an asset never overlap and each starts after the last repair ended; a run still going at the cut-off has no end in the files;
• the run in force is rebuilt for every reading from the run table, and every label (run age, life used, remaining life, true remaining life, fails within 30 days) recomputes from it;
• no sensor value while the asset is down; pressure only on pumps and compressors, oil debris only on gearboxes and compressors; ISO 10816-3 zone, alarm and alarm reason recompute from the readings;
• one work order per run ended in the window, its type from how the run ended, its times from the run, its costs re-adding; inspection findings recompute from the measured vibration and follow each asset's PM interval;
• the physics above: P-F curve, mode-specific signals, load and climate against life, criticality against catches, sudden failures, false alarm rate.

• readingsOne reading per asset per day for two years: vibration RMS and crest factor, bearing temperature, motor current, discharge pressure, oil debris, load, ambient, ISO 10816-3 zone, alarm and its reason; plus labels (run age, life used, remaining life to the run's end and to the true failure, fails within 30 days)175,440 rows · 24 cols
• inspectionsRoute-based vibration checks at each asset's PM interval, with the measured value and the finding2,042 rows · 7 cols
• runsEvery life of every asset, from install or repair to the next failure or renewal: failure mode, true life, whether it gave warning signs, how it ended, downtime, and whether it was still running at the cut-off758 rows · 19 cols
• work_ordersOne per run that ended in the window: breakdown, condition-based or preventive, priority, raised/started/completed, component replaced, found condition, labour hours, parts, labour and lost-production cost520 rows · 19 cols
• assetsPumps, motors, fans, gearboxes and compressors: type, criticality A/B/C, rated power and current, nominal pressure, install year, load factor, duty hours, online monitoring or route-based, PM interval240 rows · 15 cols
• sitesFour plants in different climates: ambient temperature and its seasonal swing, spares lead time, cost of an hour of downtime4 rows · 7 cols

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