# Generative AI design for heavy construction equipment

Long design cycles and heavy physical prototyping slowed new excavator and loader models, while components needed to get lighter and stronger. A generative design platform that explores thousands of manufacturable component designs overnight and exports the best straight to CAD.

- **Sector**: Heavy equipment
- **Region**: India
- **Disciplines**: Generative design · Simulation · Cloud HPC
- **Practices**: [AI & machine learning](https://www.winapps.co.in/services/ai-ml/), [Product engineering](https://www.winapps.co.in/services/product-engineering/)
- **Client**: Under NDA. References available on a call.

## The challenge

An Indian manufacturer of excavators, backhoe loaders and motor graders needed to launch models faster while cutting component weight for fuel efficiency and transport cost. Design relied on experienced CAD engineers iterating by hand, and physical prototyping took a large share of every programme's time and budget.

## Our approach

We built a generative design pipeline that combines topology and lattice optimisation with multi-objective search over mass, stiffness, fatigue life and cost. Real manufacturing limits for sand casting, welded fabrication and CNC machining, plus Indian material libraries and IS, ISO and SAE standards, are built into the constraints.

Thousands of candidates run in parallel on cloud HPC overnight, with FEA and fatigue checks in the loop to discard infeasible designs early. Engineers explore the trade-offs in a web dashboard and export chosen concepts directly to their CAD tools.

## Architecture

- **Inputs**: Load cases, Manufacturing constraints (casting, welding, machining), IS / ISO / SAE standards
- **Generation**: Topology and lattice optimisation, Multi-objective search (mass, stiffness, fatigue, cost)
- **Validation**: Non-linear FEA and fatigue checks, Design rule checking
- **Engineers**: Pareto-front explorer, CAD export, Automated design reports

Illustrative architecture, simplified to protect client confidentiality.

## Results

Outcome details for this engagement are shared under NDA. We're happy to walk through results and put you in touch with a reference on a call.

## Stack

- ANSYS
- Siemens NX
- Solid Edge
- Cloud HPC

Next case study: [AI-powered CRM for a fashion e-commerce brand](https://www.winapps.co.in/work/ecommerce-crm-personalisation/) ([Markdown](https://www.winapps.co.in/work/ecommerce-crm-personalisation.md))

## Facing something similar?

A senior engineer, not a salesperson, replies within one business day. NDA available before any detailed discussion.

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