Assetize

All learning series · Suite application · Part 1

Maximo Monitor

Turn measured operating conditions into an actionable monitoring view.

Before you start

MAS learning path. Match the component documentation to your installed release and maintenance build before configuring it.

  • Monitor available with a test data source.
  • A synthetic sensor feed and a documented mapping from device/entity identity to a training asset.

IBM sources + Assetize exercise · Not lab-verified

01 · Basics — Understand the building blocks

Monitor organizes operational measurements so teams can examine asset behavior. Its APIs expose raw and aggregated metric data by entity type.

A measurement needs identity, timestamp, units and context. A dashboard showing a number is only useful when the number refers to the intended equipment and time period.

Topics in this series

  • Entities and measurements
  • Data ingestion and units
  • Calculations and dashboards
  • Alerts and operational context
  • Maintenance handoff and replay

02 · Configuration — Work through the setup

Use a training environment and match the actions to the IBM guide for your installed build.

  1. Define one pump entity and the meanings of temperature, vibration and operating state in your training data.
  2. Use the installed Monitor data-ingestion procedure to supply a small timestamped sample.
  3. Inspect the entity's raw measurements and compare them with the input file.
  4. Configure a view or calculation for an agreed time window; distinguish individual readings from aggregate values.
  5. Apply a documented alert function available in your build and test normal, sustained-high and missing-data samples separately.

03 · Practical example

Fictional teaching example

A pump is warm during startup. In the practice design, the operator investigates only if a high-temperature condition persists while the pump is running. The threshold and duration are teaching assumptions, not equipment limits.

04 · Practice and verify

Create ten normal readings, ten persistent high readings and a deliberate time gap. Record which observations reach the dashboard and alert process.

Expected result

Identity, units and times match the input. Persistent high data is distinguishable from a gap and from a transient startup event.

Common mistakes

  • Sending every raw reading directly into a new work order.
  • Interpreting absence of telemetry as healthy operation.

05 · Advanced concepts

Design deduplication, alert ownership and a deliberate handoff to maintenance. Test stale data, replayed readings and a restored connection before scaling the feed.

IBM references

Product explanations link to IBM sources. Scenarios and exercises are original Assetize guidance, not claims of executed lab procedures. Reviewed 2026-10-01.

Maximo ecosystem overview · Manage learning paths · Practice data in Workbench