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Engineering Change Order Impact Analysis on DFMEA Risk Baselines

A commercial hemodialysis machine manufacturer managing a field fleet of 25,000 clinic dialysis consoles, implementing an engineering change to replace an obsolete blood flow sensor.

Runs onTatvam

ECO risk impact analysis turnaround time cut: 3 weeksECO risk impact analysis turnaround time cut
design verification testing costs reduced: 45%design verification testing costs reduced

How the work runs

The pressure that made this worth automating, the steps the system runs, and what came out the other side.

Pressure & Trigger Points

Replacing the flow sensor required evaluating potential new failure modes, firmware algorithm changes, and fluid dynamics impacts.
Engineers lacked an automated way to determine which sections of the 3,000 row DFMEA were touched by the component revision.
An overlooked sensor sampling frequency mismatch caused intermittent air bubble false alarms in clinical trials after ECO release.

The run · 5 operational steps

Click any step to inspect telemetry signals, model reasoning, and governance gates.

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Engineering Change Order Impact Scanning

Tatvam analyzes proposed ECO component revisions, scanning the complete system risk model to highlight all affected failure modes.

Input Signal:

Real-time operational telemetry & queue

Reasoning Pattern:

MCP grounded vector inference

Governance Gate:

Policy constrained with audit write-back

Verified Business Outcomes

ECO risk impact analysis turnaround time cut from 3 weeks to 2 hours.
Design verification testing costs reduced by 45% by targeting only affected risk control pathways.
Zero post release clinical false alarms or unintended design side effects.

Capabilities this relies on

document intelligence
risk scoring
generative design
evidence audit trail
policy compliance
human approval

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