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CUTWISE BLOG

Practical cutting knowledge, grounded in real plans.

Explore reproducible examples, process guides and API notes built around explicit stock, demand, kerf and trim assumptions—not generic optimization claims.

Updated: · Toreniva Cutwise technical review

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Latest technical articles

Reproducible case

A complete 6000 mm aluminum profile cutting plan

This reproducible demonstration uses 6000 mm stock, 3 mm kerf and 8 mm trim per end. Its verified baseline result uses four stock bars with 94.4% material utilization. It is an example task, not a customer savings claim.

Process guide

How kerf and end trim change a cutting plan

Kerf is the material removed by the blade. End trim reserves unusable material at the ends of a stock bar. Both must be included before a pattern can be called executable.

Foundation guide

What is one-dimensional cutting stock optimization?

1D cutting stock optimization assigns required part lengths to available stock bars while minimizing material cost, stock count or waste. Width and shape are fixed; length is the dimension being optimized.

API guide

Call the Cutwise API with cURL, Python or JavaScript

The API uses the same solver-v1 request and result model as the browser calculator. Keep API keys on the server, set an explicit timeout and do not automatically retry an uncertain solve response.

Industry solution

Cutting optimization for steel tube, bar and profile stock

Turn a mixed demand list into repeatable cutting patterns while respecting available stock lengths, quantities, kerf and end trim. The result stays a planning aid that operators can verify before production.

Maintained with substantive updates

We maintain these guides as product behavior, process explanations and reproducible examples evolve. An updated date marks a substantive change to the article; it is not a promise of a fixed publishing schedule.

September 12, 2026: the kerf guide now explains the exact cut-count convention and a hand-checkable capacity boundary, with a complete Chinese edition. The aluminum example adds the material balance and explains what its optimal result proves.

Built to be checked, not merely read

  • Reproducible inputs and explicit process assumptions.
  • Verified solver outcomes and downloadable artifacts where useful.
  • Clear boundaries between proven optimal, feasible and unmodelled constraints.
  • Direct links to the browser optimizer and production API documentation.