Predictive Maintenance

predictive maintenance

Connect condition insights to maintenance decisions.

Combine available condition signals with maintenance history to investigate emerging asset risk. Configure models and workflows for the agreed asset class, then validate useful alerts, warning lead time and operating value.

Request Assessment

Asset risk oversight

Assess emerging risk using the available asset data and validated models.

Maintenance performance

Keep uptime and cost outcomes measurable.

predictive maintenance

Predictive Maintenance

Solutions that scale.

Connect selected condition signals with operational context and the maintenance workflow your team already uses.

Asset-specific models

Evaluate condition and failure models for the selected assets and available data.

Anomaly Correlation

Bring available signals across selected assets into context for investigation.

CMMS Integration

Where supported integrations are configured, relevant alerts and asset context can feed your existing maintenance workflow. Your team reviews and approves the response.

Lifecycle decisions

Use available condition and maintenance evidence to support repair and replacement decisions.

Indicative implementation stages. Timing and evaluation period depend on readiness, integration scope and validation needs.

Stage 1

Asset Priority & Sensor Audit

We identify your highest-criticality assets, review existing sensor coverage, failure history, and maintenance records. We define uptime and cost-reduction KPIs with your operations leadership.

Stage 2

Model Configuration & Integration

Configure and evaluate models for the selected asset classes. Assess supported CMMS or ERP interfaces and agree the review and response workflow.

Stage 3

Live Monitoring Activation

Activate selected sources, review baseline quality and route relevant condition reports through the agreed operating channels.

Stage 4

Outcomes & ROI Performance Review

Review observed alerts, workflow performance and maintenance effort against baseline. Evaluate avoided loss only where evidence and an agreed method support it.

Asset continuity

Condition insights connected to approved maintenance workflows

predictive maintenance

Move from isolated signals to informed maintenance.

Monitor selected conditions, evaluate emerging risk and support investigation with operational context.

Talk to an expert

Condition Monitoring

Monitor selected assets and condition signals within the agreed data and deployment scope.

Failure Forecasting

Evaluate potential failure patterns where suitable telemetry, historical data and validated models are available. Warning horizons vary by asset and failure mode.

Investigation Support

Investigate contributing signals and connected systems with supporting operational context.

predictive maintenance

Support earlier investigation and better-informed maintenance.

Bring asset signals, maintenance history and approved workflows together, then evaluate warning quality and operating value in your environment.

Talk to an expert

Engineering tomorrow’s business

Book a call

Microsoft advertising cookies

With your permission, Microsoft Advertising can use cookies to measure visits and enquiries from our ads. You can accept or reject this tracking and change your choice here later.

These controls apply only to Microsoft Advertising. They do not change the site's existing Google Analytics or Google Tag Manager settings.

Microsoft tracking is currently disabled while this setup is being verified.

Predictive Maintenance: Put asset condition in context.

Identify, measure, and reduce risks before they escalate

Predictive Maintenance

Move from isolated signals to informed maintenance.

Support earlier investigation and better-informed maintenance.

Engineering tomorrow’s business

Microsoft advertising cookies