Flexible fixture design with applications to assembly of sheet metal automotive body parts
Bibliographic record
Abstract
Purpose To design a reconfigureable flexible fixture for the assembly of a set of sheet metal automotive body parts. Reconfigureable fixturing permits different parts to be grasped for assembly by a fixture without the need to conduct costly redesign and fabrication of hardware fixtures, which is an industry standard in widespread use in industry. While somewhat more complex than fixtures in current use, reconfigureable fixtures provide one solution to the problem of costly redesign of fixtures due to changes in dimensions, or geometry of parts to be assembled. Design/methodology/approach We propose a novel reconfigureable fixture for robotic assembly of a number of different parts. Motivated by the marine organism, O. vulgaris, commonly referred to as an octopus, which grasps different objects or prey using suction cups, the proposed fixture has three fingers, each equipped with a suction cup, to facilitate the grasping process and increase grasp flexibility. Using this design approach, the fixture is sufficiently general in design to grasp several different parts. To position the suction cups located on the flexible fixture, two linkage‐based mechanisms are employed. Pneumatic cylinders and electric motors are used as actuators. A prototype flexible fixture has been built and experimental results with this prototype confirm the effectiveness of the proposed flexible fixture. Software has been developed to calculate the relative positions and angles in the mechanism as required for reconfiguration. Findings The proposed reconfigureable fixture, used as an end‐of‐arm tool, permits each of a set of four sheet metal parts to be successfully grasped permitting assembly of these four components, in a robotic assembly work cell. Research limitations/implications The proposed flexible fixture is a simple proof‐of‐concept device that is suitable for a laboratory setting. We do not consider part localization of parts when grasped by the reconfigureable fixture. Practical implications Assembly operations, in industrial manufacturing operations, are typically heavily reliant on hardware fixtures devices to orient and clamp parts together during assembly operations. While of great importance in such operations, hardware fixtures are very costly to design and build. Further, fixtures are designed for use with parts of specific dimensions and geometry, hence cannot be used to grasp or orient parts with even very small differences in dimensions or geometry. Typically, if parts with different dimensions or geometry are to be assembled, new hardware fixtures must be designed and manufactured to grasp and orient these parts. This lack of flexibility leads to substantial manufacturing costs associated with fixturing. Reconfigureable fixtures permit parts with different geometries to be grasped and oriented for assembly. Originality/value Reconfigureable fixtures for use in the automotive manufacturing sector is an important development due to the highly competitive nature of this industry. Rapid introduction of new models of vehicles is greatly facilitated through the use of reconfigureable fixtures which can be reprogrammed to grasp parts of different geometries required for new vehicle models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".