Real-World Reliability Results

How ReliaNova helps companies eliminate failures, strengthen designs, and improve uptime—from early concept to global deployment.

At ReliaNova, every engagement is engineering-first and outcome-driven. Our case studies highlight how we apply Design for Reliability (DfR), Physics-of-Failure (PoF), modeling & simulation, testing strategy, supplier reliability, PHM, AI-driven diagnostics, and reliability culture development to solve real-world challenges.

Each example shows measurable improvements: lower AFR, stronger designs, reduced downtime, earlier detection of failures, and better supplier control.

✅ Pillar 1 — Design for Reliability (DfR) & Physics of Failure (PoF)

During vibration qualification, a perpendicular daughter board exhibited intermittent opens and solder-joint cracking at the mezzanine connector—despite linear FEA showing safe margins.

What We Found

A 2:1 internal resonance occurred between the main board’s second bending mode and the daughter board’s first mode.
Connector compliance created nonlinear energy transfer, amplifying alternating shear/peel stresses at outer solder joints.
Localized fatigue damage was driven by geometric nonlinearities, invisible to isolated or linear models.

What We Did

Conducted nonlinear assembly-level dynamic FEA capturing connector stiffness and geometric coupling.
Validated results using accelerometers and DIC high-speed motion tracking.
Adjusted daughter-board stiffness and selected a connector with higher Z-compliance.
Added light damping between boards to reduce energy transfer.

Impact

The cracking failure mode disappeared, vibration margin increased >40%, and costly redesign risk was avoided.

A differential-pressure sensing module in an EV showed inconsistent mid-frequency readings from one microphone in a four-element array. The issue was intermittent and could not be replicated in isolated subsystem testing.

What We Found

A tiny enclosure gap near the affected microphone opened only during a specific acoustic–structural resonance mode.
Resonance-modulated gap opening caused air leakage and destructive acoustic cancellation at that mic location.
Linear inspection methods could not detect this frequency-dependent behavior; only PoF + structural-acoustic analysis exposed it.

What We Did

Modeled the enclosure’s structural-acoustic behavior to identify the problematic resonance band.
Introduced a viscoelastic support pad to increase local stiffness and damping.
Shifted the enclosure’s resonance out of the operating band.
Verified the fix in system-level testing.

Impact

The instability was fully eliminated in the next EV build, avoiding a redesign cycle and improving the robustness of future variants.

✅ Pillar 2 — Modeling & Simulation

A portable device was suspected of being vulnerable to connector fretting under vibration, but the project had not yet produced hardware to experimentally confirm the risk.

What We Found

FMMEA and vibration FEA showed high sensitivity to local PCB mounting stiffness.
Fretting risk increased sharply with small variations in mechanical support.
A DoE confirmed that connector retention and solder-joint geometry were key contributors.

What We Did

Performed FEA-driven fretting risk mapping.
Conducted a structured DoE to isolate dominant design sensitivities.
Recommended enhancements to connector retention features and solder-joint support.
Defined mounting-stiffness thresholds for mechanical layout teams.

Impact

Predicted AFR dropped by over 50%, reducing design uncertainty and accelerating prototype readiness.

✅ Pillar 3 — Testing & Qualification

EMI clips consistently detached during DV testing after the assembly process shifted to a dual-reflow requirement for a new PCB revision.

What We Found

Surface contamination reduced solder wettability, confirmed by EDX/FTIR.
Ni/Au–BeCu interface showed delamination under second reflow thermal load.
Uneven solder-paste height and poor stencil cleanliness contributed to weak attachment.

What We Did

Tuned the reflow thermal profile to match updated assembly needs.
Improved stencil cleaning practices and standardized solder-paste thickness.
Increased pick-and-place Z-force to drive solder flow through clip center holes.
Re-tested using updated DV builds.

Impact

All subsequent builds passed qualification, restoring yield stability and preventing production delays.

✅ Pillar 4 — Field Reliability, Data Analytics & PHM (AI-Driven)

A conveyor system experienced recurring motor failures with minimal warning, resulting in costly unplanned downtime.

What We Found

IR thermal patterns correlated with PoF mechanisms such as bearing wear and insulation degradation.
ML-assisted PHM algorithms provided early anomaly detection not visible from basic threshold triggers.
PD (Prognostics Distance) trends showed detectable signatures weeks ahead of actual failure.

What We Did

Integrated IR imaging data into a PHM pipeline.
Developed ML-based anomaly detection and PD estimation.
Built dashboards for maintenance teams to track motor health and schedule interventions.
Fed field insights back into DfR to improve future motor selection and integration.

Impact

The system shifted from reactive to predictive maintenance, significantly reducing emergency failures and enabling scheduled interventions.

✅ Pillar 5 — Supplier Reliability & Global Supply Chain Assurance

Board-to-board connectors repeatedly failed extraction-force and bend-test criteria, raising concerns about material consistency and upstream supplier variation.

What We Found

Dimensional stack-up and material-property variations originated at a Tier-3 supplier.
Nearly 20% of units were below extraction-force requirements, with a subset significantly below spec.
Weakness was masked at the Tier-1 assembly stage due to insufficient incoming reliability controls.

What We Did

Performed reliability-focused supplier capability assessments.
Executed dimensional and material audits across Tier-1 and Tier-3 manufacturing processes.
Implemented corrective actions including revised tolerances, material adjustments, and stronger IQC screening.
Rolled out a reliability scorecard to track supplier maturity.

Impact

Connector reliability stabilized across multiple lots, preventing latent field failures and strengthening supply-chain dependability.

✅ Pillar 6 — Reliability Strategy, Maturity & Team Development

A large-scale automation system suffered downtime caused not by hardware failures but by inconsistent service procedures, unclear troubleshooting steps, and inefficient material flow.

What We Found

Field logs showed variability in technician interpretation of service steps.
Material flow and tool placement led to wasted motion and handling-related errors.
Human-factor-related AFR spikes aligned with unclear documentation and training gaps.

What We Did

Rewrote service procedures using visual documentation and Poka-Yoke steps.
Redesigned material flow and workstation layout for safer, more efficient access.
Conducted training sessions on PoF-based failure signatures and structured RCA.
Integrated reliability metrics into day-to-day operations.

Impact

Unplanned downtime dropped ~35%, technician confidence improved, and reliability culture strengthened across engineering and operations.

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