Predictive Assembly Gap Planning With 3D Deformation Filtering
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Solution Overview
Problem
Conventional predictive assembly methods fail to accurately predict gaps between mating surfaces when components experience deformation during assembly, leading to excessive gaps that require disassembly and remanufacturing.
Innovation Solution
A system and method that utilize data filtering to remove pre-assembly deformation from 3D measurement data, allowing for accurate prediction of gap dimensions by accounting for waviness and recommending proactive actions based on gap thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional predictive assembly methods are used to predict gaps between mating surfaces, then the prediction process is simple, but the prediction accuracy deteriorates when components experience deformation during assembly
Solution Approach 1:
The system performs preliminary filtering of 3D measurement data to remove deformation effects before gap prediction. By preprocessing the component geometry data to eliminate pre-assembly deformation, the system achieves accurate gap predictions without requiring complex real-time measurement equipment during assembly.
Solution Approach 2:
The patent replaces complex mechanical measurement and adjustment systems with a computational approach. Instead of using sophisticated physical equipment to measure and compensate for gaps, the system uses software-based filtering algorithms to predict gaps accurately from pre-assembly 3D scan data.
2Productivity
If gap predictions are not accurate, then manufacturing efficiency is maintained, but material waste increases due to disassembly and remanufacturing
Solution Approach 1:
The system performs gap prediction and identifies potential issues before assembly occurs. By detecting problematic gaps in advance through filtered 3D model analysis, the system allows for preemptive modifications such as adjusting component geometry or selecting alternative components, preventing waste from disassembly and remanufacturing.
Solution Approach 2:
The system provides feedback on predicted gap dimensions compared to acceptable thresholds, enabling corrective actions to be taken before assembly. This feedback loop allows manufacturers to adjust their process or select different components based on the prediction results, avoiding material waste.
3Measurement precision
If pre-assembly deformation is not filtered from 3D measurement data, then the measurement process is straightforward, but the gap dimension prediction becomes inaccurate
Solution Approach 1:
The system applies deformation filtering as a preliminary processing step to the 3D measurement data before gap prediction. This preprocessing removes the effects of pre-assembly deformation from the component models, ensuring that subsequent gap measurements are based on the components' true as-manufactured geometry rather than their deformed state during handling or measurement.
Data Source
AI summary
A system for predictive assembly includes a model generator, a model analyzer, and an assembly planner. The model generator generates a first model of a first component and a second model of a second component before the first component and the second component are coupled together. The model analyzer analyzes the first model and the second model to determine a dimension of a gap between a first mating surface of the first component and a second mating surface of the second component after the first component and the second component are coupled together. The assembly planner recommends an action based on a comparison of the gap to a gap threshold.