From concept sketch to a production-ready drawing pack — the complete product engineering lifecycle under one roof. Design, simulation, manufacturing engineering and AI optimisation run as one continuous thread, so a topology result never gets lost on its way to the shop floor and a DFM constraint never arrives after the tooling is cut.
Concept to detailed design with FEA/CFD-validated performance.
We take a requirement — a load case, an envelope, a cost target — and turn it into a manufacturable product. Concept studies are narrowed against real constraints, detailed in parametric CAD, then proven in simulation before a single component is cut. Structural, thermal, fatigue and flow behaviour are characterised in ANSYS, tolerance stack-ups are run on every critical interface, and the design is released as a GD&T drawing package your supply chain can quote from without a single clarification call.
Production-ready packages, tooling, and vendor development.
A good design that cannot be built on your floor is a failed design. This service line covers everything between a released drawing and a repeatable production part: tooling and fixture engineering, Special Purpose Machines built around your cycle time, hydraulic and pneumatic circuit design, assembly-line configuration, vendor development and RFQ support, and inspection planning that ties every critical characteristic on the drawing to a measurable check on the shop floor.
Generative design, predictive analysis, and digital twins.
The intelligence layer sits inside the engineering workflow rather than beside it. Topology optimisation explores load paths no engineer would draw by hand, typically recovering 15–40% mass at equal stiffness. Machine-learning models trained on FEA output and field data flag fatigue and thermal risk before a prototype exists. Manufacturability scoring against real vendor capability catches cost drivers while the geometry is still cheap to change, and physics-based digital twins keep monitoring the part once it is in service.
Define load cases and manufacturing constraints — AI explores the full design space to discover optimal material distribution. Typical outcomes: 15–40% weight reduction with equivalent or superior structural performance.
ML models trained on FEA outputs, material property databases and field performance data predict fatigue life, crack propagation probability and thermal failure risk — before a physical prototype is built.
Automated manufacturability scoring against real vendor capabilities. AI flags features that will drive machining cost, assembly complexity, or supplier rejection before the design is locked — reducing DFM iteration cycles by up to 50%.
Physics-based digital twins linked to production data for real-time performance monitoring. Dashboards identify bottleneck patterns, excess WIP, and quality escape trends across production lines.
Helping manufacturing companies identify operational bottlenecks, reduce inefficiencies and build scalable systems.
Book free assessment →45-minute on-site assessment · written Engineering Health Report.
Evaluate business independence and leadership maturity.
Standard operating procedures, workflows and documentation.
KPI systems, productivity improvement, process optimisation.
Identify hidden operational losses and margin improvement opportunities.
Systems, delegation, leadership development, organisational maturity.
The complete capability profile — service lines, simulation and AI toolchain, sector experience, delivered programmes and the engagement models we work under. Useful for circulating internally before a technical call.
Toolchain, deliverable formats, IP ownership and how a design engagement actually runs.
Ask the engineering desk →Three connected service lines: product engineering and 3D CAD design (SolidWorks, CATIA, NX, Fusion 360) with FEA/CFD validation; manufacturing engineering covering tooling, fixtures, Special Purpose Machines, hydraulics and inspection planning; and AI-driven optimisation including topology optimisation, predictive failure analysis and digital twins. A single team carries a programme from concept sketch to a released, DFM-checked production drawing package.
Design in SolidWorks, CATIA V5, Siemens NX and Fusion 360. Simulation in ANSYS Mechanical, ANSYS Fluent and ANSYS Discovery for structural, fatigue, thermal and flow behaviour. Optimisation in nTopology, SolidWorks Topology and custom Python/scikit-learn pipelines. Drawings are released to ASME Y14.5 GD&T, and we can deliver in the native format your supply chain already uses.
Yes. A typical end-to-end engagement runs: requirement capture and concept studies, detailed design, FEA/CFD validation, design reviews, DFM and tolerance stack-up, GD&T production drawings, vendor development and RFQ support, inspection and qualification planning, then first-article support on the shop floor until the part is signed off.
Frequently. We plug into your PLM/PDM workflow, follow your drawing standards and review gates, and take ownership of a defined work package — a sub-assembly, a simulation campaign, or a full drawing release — so your core team stays on the critical path.
Three models: fixed-scope deliverable (drawing package, simulation report, tooling design), monthly dedicated-engineer retainer for continuous programmes, and milestone-based development for full product programmes. Every proposal states scope, deliverable format, review points, revision allowance and timeline before work begins.
All engagements run under NDA. Design data is held on controlled storage with access restricted to the assigned engineering team, and all IP generated during an engagement is assigned to the client unless the contract says otherwise. Export-controlled and classified work follows the customer's prescribed handling procedure.
An engineer answers by email — usually within one working day.
