Evidence map›Paper›PMID 41753820›Full record

ArticleMicromachines2026

Process Optimization for Ultra-Precision Machining of HUD Freeform Surface Mold Cores Based on Slow Tool Servo.

Tianji Xing, Naiming Qi, Huanming Gao, Longkun Xu, Xuesen Zhao, Tao Sun

Abstract read
In one paragraph

Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tianji XingCenter for Precision Engineering, Harbin Institute of Technology, Harbin 150001, China.
Naiming QiDepartment of Aerospace Engineering, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0003-0401-5616
Huanming GaoTianjin Navigation Instrument Research Institute, Tianjin 300131, China.
Longkun XuCenter for Precision Engineering, Harbin Institute of Technology, Harbin 150001, China.
Xuesen ZhaoCenter for Precision Engineering, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0001-5460-0683
Tao SunCenter for Precision Engineering, Harbin Institute of Technology, Harbin 150001, China.

Funding

National Natural Science Foundation Joint Fund for Regional Innovation and Development U24A20124Sichuan Science and Technology Program 2024YFCY0028
6 · The paper itself

Abstract

With the rapid development of Head-Up Display (HUD) technology for vehicles, optical freeform mirrors, as its core optical components, are crucial for achieving system compactness and high imaging quality. However, their complex surface shapes and large-aperture characteristics pose significant challenges to ultra-precision manufacturing. This study presents a systematic optimization framework for the ultra-precision machining of HUD optical freeform mold cores, integrating surface design, tool path planning, vibration analysis, and process parameter optimization. Firstly, based on the XY polynomial freeform surface model, an off-axis three-mirror HUD system was designed, and the surface parameters and machining dimensions of the mold core were determined. For the Single-Point Diamond Turning (SPDT) Slow Tool Servo (STS) process, a hybrid trajectory planning method combining equidistant projection and cubic spline interpolation was proposed to ensure the smoothness and accuracy of the tool path. Through theoretical analysis and experimental verification, the selection criteria for tool parameters such as tool nose radius and effective cutting angle were clarified, and the mechanistic impact of

Indexed as

head-up displayoptical freeform surfacesingle-point diamond turningslow tool servoultra-precision manufacturing

Identifiers

PMID41753820
PMCPMC12943503

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.