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Condition-Based Monitoring.

Data-driven predictive maintenance for modern manufacturing. Reduce unplanned downtime, improve equipment reliability, and increase production efficiency.

Reduce downtime Improve reliability Increase efficiency
Instrumented plant equipment with a live health dashboard
Instrumented plant equipment with a live health dashboard

01 / Overview

Maintenance driven by real condition.

Condition-Based Monitoring (CBM) is an intelligent maintenance strategy that continuously monitors the health of industrial equipment using real-time operational data. Instead of servicing machines on fixed schedules or reacting after failures occur, CBM lets maintenance teams make informed decisions based on the actual condition of each asset.

ServvEdge's AI-powered CBM platform combines Industrial IoT, advanced analytics, machine learning, and intuitive dashboards to detect abnormal operating conditions early—so organisations can plan maintenance before failures impact production.

ServvEdge health dashboard in the maintenance control room
ServvEdge health dashboard in the maintenance control room

02 / Business challenges

The cost of reacting late.

Manufacturers consistently face the same pressures. CBM addresses each by monitoring equipment health continuously and providing early warnings before failures occur.

  • Unplanned downtimeSudden stoppages that ripple across the line.
  • High maintenance costOver-servicing and emergency repairs.
  • Unexpected failuresBreakdowns with no early warning.
  • Production lossesMissed output and delivery targets.
  • Reduced availabilityAssets offline when you need them most.
  • Quality & safety riskDefects and hazards from degrading equipment.

03 / Equipment supported

Built for the assets you rely on.

From rotating machinery to process lines, ServvEdge monitors the equipment that keeps production moving.

  • Electric motors
  • Pumps
  • Compressors
  • Fans
  • Gearboxes
  • Conveyors
  • Blowers
  • Stamping presses
  • Textile machinery
  • Feed processing equipment
  • CNC machines
  • Mixers
Motor and pump skid fitted with vibration sensors
Motor & pump skid fitted with vibration sensors

04 / Maintenance strategy

From reactive to predictive.

CBM sits at the mature end of the maintenance spectrum—optimising work against real asset condition rather than the clock.

StrategyTriggerLimitation
ReactiveFailure occursHighest downtime
PreventiveTime scheduleUnnecessary maintenance
Condition-based ServvEdgeAsset conditionOptimised maintenance
Predictive ServvEdgeAI forecastHighest maturity

05 / How it works

From machine to decision.

A continuous signal path turns raw equipment behaviour into prioritised, actionable insight.

  1. 01MachineCritical production asset
  2. 02SensorsVibration, temperature, current & more
  3. 03Edge gateway / PLCAcquire and pre-process data
  4. 04Secure connectivityEncrypted outbound transfer
  5. 05Cloud platformCentral data foundation
  6. 06AI analyticsAnomaly detection & ML models
  7. 07Health scoreCondition index & remaining useful life
  8. 08AlertsIntelligent, prioritised notifications
  9. 09DashboardAct with clear evidence

06 / Sensor types

The signals that reveal machine health.

  • Vibration
  • Temperature
  • Current
  • Pressure
  • Flow
  • Acoustic
  • RPM
  • Oil condition
Vibration sensor mounted on a motor drive-end bearing
Vibration sensor mounted on a motor drive-end bearing

07 / Application capabilities

Analytics that see ahead.

  • Trend analysisTrack condition over time.
  • Statistical monitoringBaseline normal behaviour.
  • Dynamic thresholdsAdapt to operating mode.
  • Anomaly detectionFlag meaningful change early.
  • Machine learningLearn each asset's signature.
  • Remaining useful lifeForecast time to intervention.
  • Health indexOne clear condition score.
  • Intelligent alertsPrioritised, low-noise warnings.

08 / Business impact

Outcomes you can measure.

Typical results reported by manufacturers adopting condition-based monitoring.

20–50%Reduction in unplanned downtime
10–30%Lower maintenance cost
ImprovedOverall equipment effectiveness (OEE)
ExtendedAsset life
BetterSpare inventory planning
HigherProduction availability & safety

09 / Industries

Proven across manufacturing.

  • Automotive
  • Textile
  • Food & beverage
  • Animal feed
  • Cement
  • Steel
  • Chemical
  • Pharmaceuticals
  • Packaging
  • General manufacturing

10 / Implementation roadmap

A practical path to rollout.

  1. 01
    Asset assessment

    Identify critical assets and failure modes that matter.

  2. 02
    Sensor selection

    Match the right sensing to each asset and signal.

  3. 03
    Installation

    Mount sensors and connect edge gateways safely.

  4. 04
    Data collection

    Establish baselines from live operating data.

  5. 05
    AI configuration

    Tune models, thresholds, and health scoring.

  6. 06
    Dashboard deployment

    Give teams a shared, real-time condition view.

  7. 07
    Pilot validation

    Prove value on a focused asset set.

  8. 08
    Plant rollout

    Scale across lines, sites, and use cases.

11 / Why ServvEdge

Intelligent maintenance, delivered.

  • AI-powered analyticsModels built for industrial signals.
  • Industrial IoT expertiseFrom sensor to dashboard, end to end.
  • Scalable deploymentStart focused, expand with evidence.
  • Cloud & on-premiseDeploy to fit your IT policy.
  • ERP & CMMS integrationInsight lands in the systems you use.
  • Measurable ROICustom dashboards focused on outcomes.

Empowering manufacturers

Begin with the assets that matter most.

Tell us where reliability, visibility, or performance is limiting your operation and we'll help define a focused first step with condition-based monitoring.