Monitoring Machine Health Using IoT: Sensors, Data and Alerts

Prioritise assets and failure modes

Rank equipment by operational consequence, repair lead time and known failure history. Identify what evidence may change before each relevant failure: vibration, temperature, current or process performance. Start with a manageable pilot asset. Do not assume one wireless sensor can detect every mechanical and electrical problem.

Choose measurements and context

Specify sensor location, range, frequency coverage and measurement interval for the intended fault. Record speed, load and operating mode alongside condition readings. A change caused by higher production load should not automatically be labelled deterioration. Include sensor health and communication quality so missing data is not mistaken for a healthy machine.

Establish a reviewed baseline

Collect data across normal operating conditions and have maintenance staff confirm the machine’s condition. Label startup, shutdown and known interventions. Use manufacturer limits and engineering review where applicable rather than learning every historical condition as normal. Retain baseline versions when components are replaced or operating conditions change.

Connect alerts to decisions

For each alert, specify the review owner, supporting evidence and next inspection. Record whether the issue was confirmed and what work was performed. Evaluate useful warning time, false alarms and missed events during the pilot. Report observed condition changes honestly; predicting a failure date requires additional validated evidence.

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