The UK Battery Industrialisation Centre (UKBIC) in Coventry is at the forefront of scaling battery cell manufacturing for the UK's electrification ambitions. Their technology team was talented — but lacked necessary tools and structure, repeatable methodology for Design Failure Mode and Effects Analysis (DFMEA).

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Through initial scoping workshops, seven distinct barriers to design risk maturity were identified — each captured directly from the team's own words: 

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 ​ DFMEA perceived as too complex and time-consuming — engineers avoid it or treat it as a tick-box exercise because sessions are unstructured and overwhelming.

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  Scope creep and no defined completion criteria — without clear boundaries, sessions expand endlessly with no measurable endpoint.

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  Blurred lines between DFMEA and PFMEA — design risk sessions routinely drift into process failure modes, wasting time and creating confusion.

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  Inconsistent scoring of Severity, Occurrence and Detection — different engineers rate identical failure modes differently, undermining confidence in risk priorities.

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  No agreed SC/CC classification methodology — design, quality and manufacturing teams cannot agree on Special and Critical Characteristic definitions, stalling decisions.

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  Workshops that produce discussion but no outputs — without facilitation discipline, sessions become unproductive conversations with no tangible deliverables.

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  Critical knowledge locked in individuals — experienced engineers hold failure mode expertise that is never documented, structured or made transferable

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With automotive OEMs demanding IATF 16949 compliance and the EU Battery Regulation introducing new traceability requirements, the business needed to move fast — but move right.

What We Were Tasked To Do

UKBIC defined success across three dimensions:

1. Resolving historic challenges 
2. Building current capability
3. Enabling future potential

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Success Criteria:

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  "Generic DFMEA that is easy to understand, with links to DVP"

  "Relevant controls identified, not just SCs & CCs"

  "UKBIC team have knowledge, competency & tool to progress DFMEA"

 "SC & CC justification to wider business, and lead DFMEA with customers"

 "Becomes easy to navigate and part of day-to-day activities"

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Future Potential Targets:

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  "UKBIC team can lead workshops with customers to manage their tech & product development risk"

  "Anticipate potential faults in customer products" — proactive risk identification as a service offering

  "Tool to manage + boost yield, can be presented to customers" — DFMEA as a commercial differentiator

  "Roll out to the PFMEA" — design risk methodology extending into process risk management

  "Live valued-added document process which facilitates training & robust design"

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Our Approach:

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  Deep Stakeholder Engagement: We conducted extensive workshops and interviews with stakeholders across the different functions of the technology team —from senior management and program leads to process engineers, production managers. This allowed us to understand the distinct pain points and requirements of each function.

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 Technical & Design Deep Dives: The team analysed everything from of the existing 21700 design, reviewing design documentation to understand potential design risks.

How We Delivered

We believe that true transformation comes from integrating people, processes, and technology, all underpinned by good data. We embedded within UKBIC's technology team for a 12-week intensive programme, combining VDA/AIAG 2019 methodology with hands-on delivery in Relyence FMEA software.

Phase 1 - Foundation: APQP/PPAP & NPI Framework

We established the end-to-end process framework before touching a single failure mode. Built the NPI process linking Requirements → Product Development → Process Development → Build Management. Mapped DFMEA into APQP's 5-phase structure and aligned all 18 PPAP steps — connecting DFMEA (Step 4) to Process Flow Diagrams, PFMEA and Control Plans.

PPAP Overview

NPI Process Overview

Phase 2 - Scoping & Structural Analysis

This analysis began with a comprehensive structural decomposition of the battery cell’s engineering Bill of Materials (eBOM) across all sub-assemblies. To accurately capture the complexities of the anode and cathode, phantom items were integrated to represent their specific formulation and coating stages. Furthermore, we utilized rigorous interface definitions to establish a clear boundary between design-related and process-related failure modes, ensuring each risk is addressed within the correct scope.

AIAG / VDA 2019 DFMEA Process Steps

Phase 3 — Boundary Diagrams & P-Diagrams

To ensure a comprehensive analysis, every sub-assembly was visually mapped to identify potential failure pathways and system interactions. We developed detailed Boundary Diagrams for each component to track energy transfers, interface flows, and the impact of external influences. This was supplemented by Parameter Diagrams (P-Diagrams) to categorize signal and control factors against environmental noise and error states. Finally, interface matrices were utilized to document the complex relationships existing both within individual sub-assemblies and across the entire battery system.

Phase 4 — Failure Analysis & Risk Scoring

We conducted a series of cross-functional workshops to ensure the risk analysis was both structured and repeatable. The assessment followed the end-to-end 7-step VDA/AIAG 2019 methodology, which established a consistent 'auto-flow'—linking effects to modes and causes across the entire system hierarchy. To categorize risk, we applied a formula-based approach for identifying Critical and Significant Characteristics: any mode with a Severity score of 9 or 10 was classified as a Critical Characteristic (CC), while those with a Severity above 6 and an Occurrence above 4 were designated as Significant Characteristics (SC). Finally, we integrated a product-level Failure Effects column to provide the necessary context to sharpen our definitions of specific failure modes and their root causes

Phase 5 — DVP&R Integration & Optimisation​

To ensure full design-to-test traceability, we established a direct connection between identified risk items and the project’s validation plans. Each DFMEA entry was linked to specific DVP&R (Design Verification Plan and Report) worksheets using evidence pointers to streamline verification. We further strengthened this framework by mapping prevention controls directly to engineering specifications and drawings, while detection controls were aligned with specific testing protocols. To evaluate these risks from multiple perspectives, we utilized Action Priority (AP), Risk Priority Number (RPN), and Severity/Hazard (SH) scoring, providing a comprehensive set of lenses for risk management.

Phase 6 — Knowledge Transfer & Capability Building

The primary objective of the project was to establish long-term self-sufficiency within the internal team. To support this, we developed generic DFMEA blueprints designed for seamless reuse across future battery cell programs. The engineering team underwent rigorous training on the Relyence platform and VDA/AIAG methodologies, including the practical application of Boundary and P-diagrams. This was supported by a comprehensive suite of training materials covering APQP, PPAP, and NPI fundamentals. To ensure these skills were fully internalized, we conducted over 200 hours of facilitated workshops; these were not theoretical classroom sessions, but live DFMEA exercises performed on actual battery cell products where real engineering decisions were made in real-time.