Novel calculation methods for geometrically accurate thread depth

In advanced manufacturing systems, particularly High-Mix Low-Volume (HMLV) environments, achieving first-pass conformity in threaded components remains challenging due to strict ISO tolerance requirements, non-standardized tool geometries, and reliance on gauge-based iterative corrections. These limitations not only reduce machining accuracy but also increase setup time, energy consumption, and material waste. This study introduces three fundamentally new calculation methods that enable precise geometrical determination of thread depth for CNC turning and milling of both external and internal metric threads. The methods integrate ISO-defined pitch-diameter tolerances, detailed tool geometry, and measured nose radius into a unified analytical framework, thereby enabling automatic and dimensionally accurate G-code generation. Method 1 addresses external thread turning using full-profile inserts. Method 2 provides a generalized model for external thread milling with free-form radii. Method 3 extends the approach to internal threads by incorporating pre-machined reference diameters. Industrial case studies demonstrates that the proposed methods can enhance precision manufacturing, eliminate trial-and-error adjustments. The results contribute to advanced and green manufacturing practices by improving automation readiness, shortening machine setup cycles, and enabling reliable production of atypical thread sizes and tolerance classes.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-05-18
DOI
https://doi.org/10.1038/s41598-026-53095-1
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Novel calculation methods for geometrically accurate thread depth

Mátyás Andó
Scientific Reports
Manufacturing Process and Optimization
article

Novel calculation methods for geometrically accurate thread depth

Mátyás Andó
article en

Abstract

In advanced manufacturing systems, particularly High-Mix Low-Volume (HMLV) environments, achieving first-pass conformity in threaded components remains challenging due to strict ISO tolerance requirements, non-standardized tool geometries, and reliance on gauge-based iterative corrections. These limitations not only reduce machining accuracy but also increase setup time, energy consumption, and material waste. This study introduces three fundamentally new calculation methods that enable precise geometrical determination of thread depth for CNC turning and milling of both external and internal metric threads. The methods integrate ISO-defined pitch-diameter tolerances, detailed tool geometry, and measured nose radius into a unified analytical framework, thereby enabling automatic and dimensionally accurate G-code generation. Method 1 addresses external thread turning using full-profile inserts. Method 2 provides a generalized model for external thread milling with free-form radii. Method 3 extends the approach to internal threads by incorporating pre-machined reference diameters. Industrial case studies demonstrates that the proposed methods can enhance precision manufacturing, eliminate trial-and-error adjustments. The results contribute to advanced and green manufacturing practices by improving automation readiness, shortening machine setup cycles, and enabling reliable production of atypical thread sizes and tolerance classes.

Scientific Reports
Eötvös Loránd University (HU)
Eötvös Loránd Tudományegyetem
Affordable and clean energy
Openalex Percentile: Top 5%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.