Stiffness optimization of a novel reconfigurable parallel kinematic manipulator
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Bibliographic record
Abstract
SUMMARY This paper proposes a novel design of a reconfigurable parallel kinematic manipulator used for a machine tool. After investigating the displacement and inverse kinematics of the proposed manipulator, it is found that the parasitic motions along x -, y -, and θ z -axes can be eliminated. The system stiffness of the parallel manipulator is conducted. In order to locate the highest system stiffness, single and multiobjective optimizations are performed in terms of rotation angles in x - and y -axes and translation displacement in z -axis. Finally, a case study of tool path planning is presented to demonstrate the application of stiffness mapping. Through this integrated design synthesis process, the system stiffness optimization is conducted with Genetic Algorithms. By optimizing the design variables including end-effector size, base platform size, the distance between base platform and middle moving platform, and the length of the active links, the system stiffness of the proposed parallel kinematic manipulator has been greatly improved.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it