Digital Thread · Platform Implementation · Data Governance
We implement and optimise PLM platforms that connect every stage of the product lifecycle with accurate, controlled, and traceable data — from requirements and design through manufacturing, service, and end-of-life.
What We Do
Unmanaged product data — scattered across shared drives, legacy PDM systems, and disconnected tools — is one of the most significant sources of engineering rework, compliance risk, and slow product development. Our PLM team implements industry-leading platforms, migrates legacy data, establishes governance frameworks, and integrates CAD and simulation tools into the PLM environment.
Key Problems We Solve
6 Service Types
Select a capability to explore the methodology, deliverables, and tools in detail.
ANALYSIS TYPE / 01
platform deployment · workflow configuration · system integration
Deploying and configuring PLM platforms tailored to your organisation's workflows — establishing the authoritative product data backbone that connects engineering, manufacturing, procurement, and quality from concept to end-of-life.
Key Aspects
Assessing business processes, data volumes, integration landscape, and regulatory requirements to define the PLM platform selection criteria and deployment architecture.
Configuring PLM workflows, lifecycle states, roles, and attribute schemas to match your engineering process — avoiding over-customisation that creates upgrade risk.
Designing and implementing integrations between the PLM platform and downstream systems including ERP, MES, CAD tools, and simulation environments.
Delivering structured training and change management programmes to ensure engineering teams adopt the platform and data quality is maintained from day one.
ANALYSIS TYPE / 02
requirements traceability · simulation linkage · lifecycle continuity
Establishing the continuous digital thread that links product requirements, design intent, simulation results, manufacturing process data, and service history — enabling full traceability from stakeholder need to delivered product and field performance.
Key Aspects
Mapping the information flows and data relationships across the product lifecycle to define which data objects must be linked and how traceability will be maintained.
Connecting system requirements to CAD geometry, simulation models, and test results — enabling impact analysis when requirements change and evidence collection for design reviews.
Integrating CAE results, analysis reports, and simulation metadata into the PLM backbone so simulation evidence is traceable to the design revision it validated.
Extending the digital thread from design into manufacturing and service — capturing as-built configurations, field incidents, and service actions against the original design baseline.
ANALYSIS TYPE / 03
legacy data cleansing · metadata enrichment · BOM restructuring
Migrating engineering data from legacy PDM systems, file vaults, and shared drives into the target PLM platform — including data cleansing, classification, metadata enrichment, and BOM restructuring to ensure the migrated data is accurate, usable, and consistently organised.
Key Aspects
Inventorying the source data estate — identifying duplication, obsolete revisions, missing metadata, and classification gaps before migration begins.
Applying transformation rules to normalise part numbers, material codes, lifecycle states, and attribute values to the target PLM schema.
Reconstructing engineering BOM structures from flat file lists, legacy drawings, and PDM assembly trees — validating completeness and correctness before load.
Running parallel validation between source and target systems, executing a controlled cutover, and decommissioning legacy systems after a defined stabilisation period.
ANALYSIS TYPE / 04
data ownership · change control · access management
Defining data ownership, lifecycle states, change management workflows, access control policies, and audit trail requirements — establishing the governance structures that ensure product data remains accurate, controlled, and compliant throughout the product lifecycle.
Key Aspects
Assigning clear data ownership roles for every product data object type — defining who creates, approves, and maintains each class of data across the product lifecycle.
Designing lifecycle state machines and engineering change workflows that enforce review, approval, and release gates before data is promoted to controlled status.
Implementing role-based access control, export controls, and IP protection policies — ensuring the right people have access to the right data at the right lifecycle state.
Configuring audit logging and compliance reporting to meet regulatory requirements (ISO, AS9100, IATF 16949) and internal governance standards.
ANALYSIS TYPE / 05
connector implementation · metadata capture · vault management
Implementing and tuning CAD-to-PLM connectors for CATIA, NX, CREO, SolidWorks, and Ansys — ensuring designers save directly to the managed vault, metadata is captured automatically, and design iterations are tracked without manual data entry overhead.
Key Aspects
Installing, configuring, and testing CAD-PLM connectors — defining attribute mappings, save rules, and checkout/checkin workflows that match the design team's working practices.
Automating capture of part number, revision, material, and mass properties from CAD into PLM attributes — eliminating manual transcription and reducing errors.
Managing product structures that contain components from multiple CAD systems — handling format translation, JT visualisation, and associativity across CAD boundaries.
Extending the PLM integration to Ansys Workbench and other CAE tools — linking simulation models to their parent CAD geometry and storing results in the managed environment.
ANALYSIS TYPE / 06
eBOM · mBOM · variant management · effectivity
Structuring and managing engineering BOM, manufacturing BOM, and service BOM across product variants, options, and effectivity ranges — providing the BOM backbone for production planning, service operations, and regulatory submissions.
Key Aspects
Defining the engineering BOM structure — part-subassembly hierarchy, component classification, and usage relationships — as the master source of design intent.
Translating the engineering BOM into the manufacturing BOM — adding process steps, work centres, and phantom assemblies to drive production planning.
Managing product variants through rules-based configuration management — defining option codes, effectivity dates, and variant conditions to control which components apply to each product configuration.
Providing BOM comparison and redline tools to visualise differences between revisions — supporting change impact analysis and production planning updates.
Connect with our PLM team to discuss platform implementation, data migration, or digital thread architecture for your organisation.
