Key Takeaways
- GEHA (Nieuw-Amsterdam, NL) şimdi yüksek hacimde veri merkezi soğutması için >2,1 m (7 ft) endüstriyel fanlar üretiyor.
- Tüm mühendislik çalışması, Siemens Designcenter Solid Edge ve bir dizi AI-destekli araç kullanan tek mühendis Jan Bos tarafından yürütülüyor.
- Takım büyüklüğü dört kişiden (2017 öncesi) bir kişiye düştü, ancak yeni bir fan tasarımı için döngü süresi ~8 haftadan <3 haftaya indi.
- AI yardımı (üretken tasarım, topoloji-optimizasyon ve otomatik çizim oluşturma) insan gücü kaybını telafi ederken ISO 9001-uyumlu dokümantasyonu koruyor.
From Oil-Field Fans to Data-Center Coolers
GEHA, 1957'den beri endüstriyel hava taşıma ekipmanının niş bir tedarikçisi olup, başlangıçta rafineriler, petrokimya kompleksleri ve ısı transferi müteahhitlerine hizmet vermektedir. Bayrak ürünleri—7,3 m (24 ft) çapa kadar bir fan muhafazası—ağır-sanayi havalandırması için hâlâ temel bir üründür.
Son beş yılda yeni bir müşteri segmenti ortaya çıktı: hiperskala veri merkezi işletmecileri. Tek bir kampüs, 2,1 m–2,5 m (7-8 ft) boyut aralığında yüzlerce fan gerektirebilir ve yüksek hacimli üretim, düşük akustik imza ve sıkı toleranslar talep eder.
“Veri merkezleri için en büyük ve en sessiz fanları üretiyoruz—bu bizim uzmanlığımız,” diyor Jan Bos, GEHA’nın Engineering & R&D Manager'ı.
One Engineer, One CAD Platform, A Toolbox of AI
The staffing shift
| Year | Engineering staff | Primary market | Typical design lead time |
|---|---|---|---|
| 2015 | 4 engineers | Oil & petrochemicals | ~8 weeks |
| 2017 | 2 engineers | Transition phase | ~6 weeks |
| 2024 | 1 engineer (Bos) | Data-center cooling | <3 weeks |
When the oil market contracted in 2017, GEHA reduced its engineering headcount. Rather than outsource, Bos consolidated the design workflow onto Siemens Designcenter Solid Edge (latest 2024 release) and layered it with AI utilities:
| AI Tool | Function | Measurable impact |
|---|---|---|
| Generative Design (Siemens Xcelerator) | Auto-creates geometry that meets weight, strength, and acoustic targets | 15 % mass reduction on fan blades |
| Topology Optimization (Altair OptiStruct) | Refines internal rib structures for stiffness | 10 % increase in natural frequency |
| Automated Drafting (Solid Edge DraftSight AI) | Generates GD&T-ready 2-D drawings from 3-D models | Saves ~2 days per part |
| Chat-GPT-style Knowledge Base | Answers design-rule queries, pulls standards (ISO 9001, IEC 60204) | Reduces research time by ~30 % |
Bos emphasizes that he “doesn’t need to be a programmer” because the AI interfaces are largely no-code: prompts and drag-drop nodes replace scripting.
Workflow snapshot
- Concept input – Bos sketches performance specs (airflow = 12 m³/s, noise < 45 dB(A)).
- Generative run – AI proposes 12 viable blade profiles; Bos selects the one meeting acoustic and weight goals.
- Topology refinement – The optimizer trims unnecessary material, producing a 0.8 kg lighter blade while preserving a safety factor of 1.5.
- Solid Edge assembly – The chosen components are assembled; interference checks run automatically.
- Automated drawing – DraftSight AI produces ISO-compliant 2-D sheets, complete with bill-of-materials (BOM) and CNC toolpaths.
The entire loop, from requirement capture to production-ready drawing, now averages 18 days, a 77 % improvement over the pre-AI baseline.
Why AI Makes a Solo Engineer Viable
- Speed: AI-driven design iterations occur in minutes rather than days.
- Consistency: Built-in rule checking enforces standards (e.g., ISO 2768-1 for geometric tolerances).
- Scalability: Cloud-hosted AI services handle compute-heavy simulations without local hardware upgrades.
Bos notes that the AI suite also provides continuous learning: each completed project feeds back into the knowledge base, sharpening future suggestions.
Bottom Line
GEHA’s pivot from oil-field ventilation to data-center cooling illustrates how a single, well-equipped engineer can sustain high-volume, high-precision fan production. By leveraging Siemens Designcenter Solid Edge together with generative design, topology optimization, and automated drafting AI tools, Jan Bos has turned a 75 % staff reduction into a three-fold acceleration of product development. The result is a lean, future-ready engineering operation capable of delivering the world’s largest, quietest data-center fans—proof that AI-augmented CAD can replace traditional manpower without compromising quality.
