Architecture, knowledge graph design, engine specification, and cross-engine integration across six specialized PLM engines — requirements traceability, BOM configuration, engineering change management, simulation orchestration, regulatory compliance, and field feedback intelligence — competing directly with Siemens Teamcenter, PTC Windchill, and Dassault 3DEXPERIENCE. Built in Rust.
Meridian manages the foundational layer of the digital thread: the requirements that define what the product must do. The engine implements bi-directional traceability from stakeholder needs through system requirements, subsystem requirements, design specifications, verification procedures, and validation evidence. Every requirement is a node in the knowledge graph, linked to the design artifacts that satisfy it (Lattice BOM components, CAD models), the simulations that verify it (Nexus), the test procedures that validate it, and the change orders that modify it (Cascade). Coverage analysis computes V&V completeness in real time — "requirement REQ-4207 is satisfied by design artifact DA-8402, verified by simulation SIM-1204 (pass, 2024-11-15), but validation test VAL-4207 has not been executed." DO-178C structural coverage analysis for avionics, ISO 26262 ASIL decomposition for automotive, and IEC 62304 software safety classification for medical devices are implemented as domain-specific requirement classification schemas.
Lattice manages the most critical and most poorly managed data structure in all of manufacturing: the Bill of Materials. The engine maintains four simultaneous BOM views in a single graph — eBOM (engineering, as-designed), mBOM (manufacturing, as-planned with process materials and routing), sBOM (service, as-maintained with field-replaceable units and supersession chains), and aBOM (as-built, serialized per-unit configuration captured at each manufacturing station). Cross-view reconciliation runs continuously, detecting discrepancies between engineering design intent and manufacturing reality in real time. The variant configuration engine resolves a 150% super-BOM into customer-specific configured BOMs using constraint-satisfaction algorithms that process millions of valid configurations in milliseconds — replacing the manual configuration spreadsheets that cause 40% of order-entry errors in engineer-to-order manufacturers. CAD-to-BOM synchronization extracts BOM structures natively from CATIA, NX, Creo, SolidWorks, Inventor, Fusion 360, and STEP/JT neutral formats.
Cascade manages the mechanism by which the product definition evolves: engineering changes. The core architectural innovation is graph-based impact analysis using modified BFS traversal on the Axiom product knowledge graph, replacing the recursive SQL queries against relational tables that traditional PLM systems use (an approach that degrades exponentially with product complexity). When an engineer proposes changing a material from aluminum 6061-T6 to titanium Ti-6Al-4V for a bracket assembly, Cascade's impact graph traverses every relationship from that component outward: parent assemblies affected, simulation models that must be re-verified (Nexus), manufacturing routings that must be updated, supplier AVL changes required, cost implications across all BOM views (Lattice), and regulatory submissions that must be amended (Sentinel). The BFS traversal runs on Rust zero-allocation hot paths with hash-indexed adjacency lists, achieving sub-10-second full-scope impact analysis across products with 50,000+ components. Parallel approval orchestration uses DAG-based dependency resolution to route ECRs through concurrent review gates.
Nexus orchestrates simulation workflows across FEA (Ansys, Abaqus, Nastran), CFD (Fluent, OpenFOAM, Star-CCM+), multi-body dynamics (Adams, RecurDyn), and electromagnetic simulation (CST, HFSS) — managing simulation data as first-class citizens in the knowledge graph rather than file attachments in a PDM vault. Every simulation model, mesh, boundary condition set, solver configuration, and result dataset is a node linked to the design artifact it validates, the requirement it verifies (Meridian), and the engineering change that triggered it (Cascade). The simulation data management architecture solves the critical problem that incumbent PLM vendors handle poorly: when a design changes, which simulations need to be re-run? Nexus answers this automatically through the knowledge graph — a material change in Cascade triggers re-verification of every simulation whose results depend on material properties. Generative design integration enables constraint-driven topology optimization with TPMS lattice generation for additive manufacturing.
Sentinel transforms regulatory compliance from a post-hoc documentation exercise into an architectural feature of the PLM system itself. The write-path interceptor architecture ensures that every data mutation across all Axiom engines passes through Sentinel's compliance layer before persistence — capturing who made the change, when, why, what the previous state was, what the new state is, and preserving cryptographic proof that the record has not been altered since capture. FDA 21 CFR Part 11 compliance is achieved through ALCOA+ audit trails (Attributable, Legible, Contemporaneous, Original, Accurate + Complete, Consistent, Enduring, Available) with Part 11-compliant electronic signatures requiring biometric or two-factor authentication, signature meaning declaration (authored, reviewed, approved), and immutable binding between the signature and the specific data version signed. ITAR/EAR export control enforces per-request access evaluation against USML category classifications with Technical Assistance Agreement lifecycle management.
Echo closes the digital thread by connecting field performance data — warranty claims, service reports, IoT sensor telemetry, customer complaints, and recall events — back to the design decisions that caused them. When a field failure is reported, Echo traces the failure through the as-built BOM (Lattice aBOM) to identify the specific component, revision, and supplier lot, then traverses the knowledge graph to find the design decision, simulation result, and requirement that governed the failed parameter. The CAPA-to-ECR pipeline automates the corrective action workflow: a validated root cause with design-related attribution auto-generates a draft Engineering Change Request in Cascade, pre-populated with failure evidence, affected population estimate (from the aBOM serial registry), and proposed corrective action. Weibull reliability prediction models estimate time-to-failure distributions for components and assemblies, enabling proactive design changes before field failure rates exceed warranty cost thresholds. This closed-loop architecture is what traditional PLM systems cannot achieve because they store field data in separate quality management systems disconnected from the product knowledge graph.