AI-Enabled Automation of 3D Pipe Design for Vehicle Chassis

Designing 3D pipe layouts for vehicle chassis has traditionally been a slow, expert-heavy process manual modelling, repeated reviews, and long iteration cycles.

AI-enabled automation, built on encoded engineering rules, is reshaping this workflow enabling faster design exploration while maintaining engineering integrity. A clear example of how generative AI, when grounded in real-world engineering constraints, can scale design quality rather than just accelerate speed.

At Shwaira, this is the kind of engineering-led AI thinking that guides how complex workflows are reimagined.

Business Challenge Client Faced

A leading U.S. agriculture and automotive enterprise struggled with slow, manual 3D pipe CAD workflows and repeated expert reviews, extending design cycles by ~40% and driving significant cost overruns.

Their engineering teams were heavily dependent on specialized experts for validation, creating bottlenecks that limited throughput and delayed product releases. Frequent rework, lack of automation, and inconsistent design validation further increased development risk and operational expense.

As product complexity grew, the organization faced mounting pressure to improve design speed, accuracy, and scalability without expanding headcount.

Solution Engineered by Shwaira

Shwaira automated pipe design by encoding engineering constraints into a rule-based AI engine and using generative AI to produce multiple CAD-ready pipe layouts, each automatically validated against manufacturer and structural rules.

The solution seamlessly integrated with existing CAD systems and engineering workflows, enabling teams to generate optimized designs in minutes instead of weeks. Automated rule enforcement ensured every design met compliance standards from the start, dramatically reducing the need for manual reviews and late-stage corrections.

This intelligent automation transformed the design process from a linear, manual workflow into a fast, scalable, and repeatable digital pipeline.

Business Impact

Experienced

• Reduced manual CAD effort by ~60% and cut design iteration time by 2×, allowing engineers to focus on innovation rather than repetitive tasks.
• Achieved ~97% rule-compliant pipe designs through automated validation, significantly improving quality and reducing costly redesigns.
• Enabled scalable pipe generation, delivering double-digit cost savings while supporting rapid product expansion across multiple programs and platforms.

Together, these improvements accelerated time-to-market, increased engineering productivity, and positioned the organization for long-term competitive advantage.