Checklist

Sensor Selection & Deployment Checklist for PM Pilots

Interactive checklist to choose sensor types, placement, sampling rates, labeling conventions, storage, and pilot metrics for reliable predictive maintenance pilots. Captures structured answers you can save with a pilot, export, or attach to a Deck.

Interactive Tool

Sensor Selection & Deployment Checklist for PM Pilots

Use this interactive checklist to capture the concrete technical decisions and acceptance criteria that determine whether a predictive maintenance pilot will produce usable data. Completed submissions provide data engineers, reliability engineers, and pilot owners with the details needed for ingestion, labeling, evaluation, and scaling. Save one submission per pilot asset or sensor cluster.

Keep answers specific: list failure modes, exact mounting points, sampling units, and examples of labeled records. Where possible attach photos or spec-sheet links.

List specific failure modes the pilot needs to detect (for example: bearing wear, shaft misalignment, insulation failure, pump cavitation). Be as precise as possible.
Why is this asset a pilot candidate?
Select one or more sensor types to deploy for this pilot.
Numeric sampling rate (e.g., 256, 25000). If event-driven, enter 0 and set units to 'Event-triggered'.
Describe the precise mounting point (e.g., bearing housing, motor end, axial axis), orientation, mounting method (adhesive, stud, bracket), and any vibration-isolation concerns. Attach a photo link below if available.
Note temporary power plans for pilot if permanent power is not available. Specify expected uptime for battery-powered sensors.
Define sensor IDs, asset tags, file naming conventions, and any mapping to CMMS or asset registry (for example: Plant-Cell-Machine-AssetID-SENSOR01). Include an example record.
Synchronized timestamps are critical when correlating data across sensors. Prefer NTP/PTP or GPS when possible.
Specify where raw and processed data will be stored and who will have access. Include retention and export policies.
Retention should be long enough to capture pre-failure windows and seasonal variation.
Which quality checks will be implemented in ingestion or verified manually?
Select the metrics that will determine whether the pilot succeeds and can be scaled.
Estimate how many failure events you expect to observe in the pilot window. This helps with sample-size and labeling planning.
Describe how failures will be labeled (CMMS work orders, operator tags, manual inspection), who owns labels, and how time windows around events are defined. Include expected latency between event and label availability.
Paste URLs to photos, diagrams, or spec sheets. Store large files in the project repository and reference links here.
Document any known risks, required permits, scaffolding, or outstanding approvals.
Confirm that approvals, power, access, and data pathways are in place.
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