Extract polymer processing machinery specs, surface coating parameters, and global distributor networks. Delivered as clean JSON, CSV, or Parquet to S3 or PostgreSQL on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Machinery Specifications objects from oerlikon.com. All fields typed and schema-versioned.
"machine_id": "OB-POY-WINGS-01", "model_name": "WINGS POY 1800", "division": "Oerlikon Barmag", "product_line": "Spinning Systems", "application_area": "Polyester Yarn Production", "throughput_capacity": "Up to 3200 kg/h", "energy_consumption": "Optimised standard", "brochure_pdf_url": "https://www.oerlikon.com/assets/wings-poy.pdf"
| # | machine_id | model_name | division | product_line | application_area | throughput_capacity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Surface Coatings objects from oerlikon.com. All fields typed and schema-versioned.
"coating_id": "BAL-INIT-01", "brand_name": "BALINIT A", "coating_type": "TiN", "base_material": "Titanium Nitride", "hardness_hv": 2300, "max_operating_temp_c": 600, "friction_coefficient": 0.4, "color": "Gold"
| # | coating_id | brand_name | coating_type | base_material | hardness_hv | max_operating_temp_c |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Spare Parts objects from oerlikon.com. All fields typed and schema-versioned.
"part_number": "SP-8842-X1", "part_name": "Godet Roller Assembly", "compatible_machines": "['WINGS POY 1800', 'WINGS FDY']", "category": "Drive Components", "weight_kg": 45.2, "availability_status": "In Stock", "lead_time_days": 14, "drawing_reference": "DWG-773-A"
| # | part_number | part_name | compatible_machines | category | material_type | weight_kg |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Locations & Distributors objects from oerlikon.com. All fields typed and schema-versioned.
"location_id": "LOC-DE-REM", "facility_type": "Manufacturing & R&D", "division_focus": "Oerlikon Barmag", "company_name": "Oerlikon Textile GmbH & Co. KG", "city": "Remscheid", "country": "Germany", "postal_code": "42897", "services_offered": "['Sales', 'Service', 'Manufacturing']"
| # | location_id | facility_type | division_focus | company_name | address_line1 | city |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Material Data Sheets objects from oerlikon.com. All fields typed and schema-versioned.
"document_id": "MSDS-METCO-41C", "material_name": "Metco 41C Stainless Steel Powder", "division": "Oerlikon Metco", "language": "English", "revision_date": "2024-02-15", "hazard_classification": "Non-hazardous", "pdf_download_url": "https://www.oerlikon.com/assets/msds-41c.pdf", "file_size_kb": 1240
| # | document_id | material_name | division | language | revision_date | chemical_composition |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Oerlikon distributes its technical data across complex division portals, nested HTML tables, and embedded PDFs. We normalise this into queryable database records.
Extract technical parameters for Barmag and Neumag spinning lines, texturing machines, and polycondensation systems into typed fields.
Compile hardness, friction coefficients, and operating temperatures for Balzers and Metco coating portfolios.
Parse tabular data directly from Material Safety Data Sheets (MSDS) and technical brochures using vision-language models and layout analysis.
Resolve parent-child relationships between main machinery units and their compatible spare parts catalogues.
Extract specifications across German, English, and Chinese portals, mapping region-specific terminology to a single unified schema.
Scrape the complete distributor and facility network, including geocoordinates, service capabilities, and division alignments.
Monitor layout changes in technical tables. Our fallback chains ensure a CSS update on oerlikon.com does not break your data feed.
Aggregate corporate press releases, investor relations updates, and exhibition announcements with exact publication timestamps.
Run extractions on demand for one-off catalogue dumps or schedule weekly diffs to track new product introductions.
Brief in. Clean data out.
Specify target divisions (e.g. Barmag, Metco) and required data fields. We map the extraction schema together.
We deploy Scrapy crawlers with PDF parsing modules and Playwright for JavaScript-heavy product configurators.
Verify unit normalisation, check PDF extraction accuracy, and ensure complete geographic coverage before deployment.
Clean records pushed via JSON, CSV, or Parquet directly to your AWS S3 bucket or PostgreSQL database.
Industrial manufacturing sites prioritise brochure downloads over API access. Here is how we bridge the gap between unstructured web assets and structured data.
Critical engineering specifications on oerlikon.com are frequently gated inside PDF brochures rather than HTML. Our pipeline intercepts PDF links, downloads the assets, and runs layout-aware parsing to extract embedded tables into structured JSON arrays.
Oerlikon operates multiple sub-brands (Barmag, Neumag, Balzers, Metco) with distinct site architectures. We maintain separate crawl logic for each division while normalising the output into a single, unified database schema.
Parts finders and coating selection tools rely on client-side rendering. We deploy Playwright to execute JavaScript, interact with dropdowns, and intercept the underlying XHR responses containing the raw catalogue data.
Specifications are often published with mixed units depending on the target region (e.g. Celsius vs Fahrenheit, mm vs inches). We apply regex-based normalisation to strip text strings and convert all metrics to agreed SI units.
To prevent IP bans and respect origin server load, we route requests through residential proxies and enforce strict concurrency limits, ensuring complete extraction without triggering security firewalls.
Machine manufacturers track throughput capacities and energy consumption metrics across Oerlikon's spinning lines to benchmark their own R&D.
Textile producers aggregate spare parts catalogues to optimise inventory planning and identify compatible aftermarket components.
Research institutions compile surface coating hardness and thermal properties to train predictive material selection models.
Analysts monitor facility expansions and distributor network changes to gauge Oerlikon's regional market penetration.
Engineering teams extract replacement intervals and operating tolerances to feed digital twin models of their production lines.
Used machinery dealers map original specifications to older equipment models to standardise secondary market listings.
"Oerlikon hosts decades of industrial material science and machinery specifications, but engineering teams need it as structured database rows, not scattered PDFs."
Extracting industrial equipment data requires more than simple HTTP GET requests. We parse nested HTML tables, extract tabular data from embedded PDF spec sheets, and map complex parent-child relationships between machinery lines and spare parts components. DataFlirt handles the extraction so you can focus on the engineering analysis.
Everything supported by our oerlikon.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Custom Python modules utilizing optical character recognition and layout analysis to strip tabular data from engineering PDFs.
Scrapy manages crawl orchestration and deduplication while Playwright handles client-side rendering for interactive product configurators.
Containerised execution on Kubernetes with Apache Airflow managing dependency chains, scheduling, and automated retry logic.
Data delivered to where your team already works — no new tooling required.
About oerlikon.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline includes document parsing modules that download PDFs, identify embedded tables, and extract the specifications into structured JSON arrays.
We extract all publicly available catalogue data from myOerlikon. However, we do not bypass authentication walls to scrape customer-specific pricing or proprietary machine manuals.
We apply regex-based cleaning during the extraction phase to separate numeric values from unit strings. We can configure the pipeline to normalise all values to your preferred metric standard.
Yes. We maintain a hash index of previously scraped records. Subsequent runs compare current values against this index and output only the modified fields.
We cover all major divisions including Oerlikon Barmag, Oerlikon Neumag, Oerlikon Nonwoven, Oerlikon Balzers, Oerlikon Metco, and Oerlikon AM.
For static catalogues, we recommend weekly or monthly runs. For press releases and news, we can configure daily or hourly checks.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop copying specifications from PDFs. We build and maintain the pipeline to deliver clean Oerlikon machinery and materials data directly to your database.
