Flexible Part Tolerancing Optimization

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Solution Overview

Problem

Existing methods for tolerancing mechanically flexible parts, such as those used in aircraft structural elements, often result in manufacturing costs being either too high due to overly stringent tolerances or too low due to wide tolerances, leading to assembly challenges and inefficiencies, particularly in large-scale assemblies where parts' flexibility causes deformation.

Innovation Solution

A method that optimizes manufacturing tolerances by simulating the mechanical flexibility of parts using distortion vectors and influence coefficients, allowing for the calculation of optimal tolerances during the digital model stage, which maximizes the chances of successful assembly while minimizing manufacturing costs, and accounts for assembly range and positioning variability through statistical methods like Monte Carlo simulations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If tight manufacturing tolerances are imposed on flexible parts, then assembly precision is improved, but manufacturing cost increases significantly

Engineering Contradiction:
Improveassembly precisionVSAvoidmanufacturing cost
Core Design Contradiction:
Manufacturing precisionVSEase of manufacture

Solution Approach 1:

The patent transforms the tolerancing problem from a static geometric constraint into a dynamic parameter optimization problem. By introducing influence coefficients that quantify the effect of manufacturing deviations on assembly quality, the system can dynamically adjust tolerances for different parts based on their actual impact on assembly performance, rather than uniformly applying tight tolerances to all parts.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent performs preliminary simulation and optimization during the design stage using digital models before actual manufacturing occurs. By calculating influence coefficients and optimizing tolerances in advance through virtual assembly simulations, the system identifies which parts require tight tolerances and which can tolerate wider variations, preventing the need for uniformly tight tolerances that increase manufacturing costs.

Inventive Principle:
Principle #10Preliminary action

2Ease of manufacture

If wide manufacturing tolerances are used to reduce cost, then manufacturing cost decreases, but assembly success rate and functional compliance deteriorate

Engineering Contradiction:
Improvemanufacturing costVSAvoidassembly success rate
Core Design Contradiction:
Ease of manufactureVSReliability

Solution Approach 1:

The patent changes the approach from fixed geometric tolerances to dynamic tolerance optimization based on influence coefficients. These coefficients quantify how manufacturing deviations in each part affect assembly quality, allowing the system to identify critical parts that require tighter tolerances to ensure assembly success while allowing non-critical parts to have wider tolerances for cost reduction.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent establishes a feedback loop where influence coefficients are calculated based on simulated assembly results, and these coefficients then guide the optimization of tolerances for subsequent manufacturing. The system continuously refines tolerance allocations based on how actual or simulated manufacturing variations affect assembly performance, ensuring functional compliance while minimizing costs.

Inventive Principle:
Principle #23Feedback

3Manufacturing precision

If uniform tight tolerances are applied to all parts, then assembly quality is ensured, but overall manufacturing cost increases due to unnecessary precision on non-critical parts

Engineering Contradiction:
Improveassembly qualityVSAvoidoverall manufacturing cost
Core Design Contradiction:
Manufacturing precisionVSEase of manufacture

Solution Approach 1:

The patent applies the principle of local quality by differentiating tolerance requirements for different parts based on their specific influence on assembly quality. Through influence coefficient analysis, the system identifies which local parts or features have significant impact on assembly performance and assigns tighter tolerances only to those critical locations, while allowing non-critical parts to have wider tolerances.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The patent transforms uniform tolerances into differentiated tolerances by introducing influence coefficients as varying parameters. Each part's tolerance is optimized based on its calculated influence coefficient, creating a non-uniform tolerance distribution that matches the actual importance of each part to assembly quality, thereby reducing unnecessary manufacturing costs.

Inventive Principle:
Principle #35Parameter changes

4Reliability

If post-facto measurement and adjustment methods are used, then assembly feasibility is improved for parts with defects, but the approach cannot prevent excessive manufacturing costs incurred during production

Engineering Contradiction:
Improveassembly feasibilityVSAvoidmanufacturing cost
Core Design Contradiction:
ReliabilityVSEase of manufacture

Solution Approach 1:

The patent performs preliminary optimization during the design stage using digital models and simulated manufacturing variations. By calculating influence coefficients and optimizing tolerances before actual manufacturing occurs, the system prevents excessive manufacturing costs from being incurred in the first place, rather than attempting to compensate for poor tolerancing choices after production has begun.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent uses digital models as virtual copies of physical parts to perform tolerancing optimization simulations. By working with digital replicas that incorporate simulated manufacturing variations and flexibility characteristics, the system can evaluate and optimize tolerances without affecting actual production costs, then apply the optimized tolerance values to guide real manufacturing processes.

Inventive Principle:
Principle #26Copying

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach reduces manufacturing costs by allowing wider tolerances for some parts and tighter tolerances for others, ensuring higher assembly success rates while maintaining compliance with functional requirements, and is applicable at the design stage before physical parts are created, thus aligning with just-in-time production needs.

Implementation Method 1

simulating the mechanical flexibility of parts using distortion vectors... accounts for assembly range and positioning variability through statistical methods

Methodology Applied
Scientific EffectElastic deformation: Elasticity

Implementation Method 2

The identification of a reduced linear model makes it possible to carry out the optimization in a way that consumes little computational resources while taking into account a large number of variation configurations

Methodology Applied
Scientific EffectFinite element analysis:

Data Source

PatentEP2764415B1Method for optimizing the tolerancing of a set of flexible parts subjected to forces
Publication Date: 2019.12.18 AIRBUS (SAS)
  • EP2764415B1 patent drawingFigure 1~4
  • EP2764415B1 patent drawingFigure 5~6
  • EP2764415B1 patent drawingFigure 7

AI summary

The invention relates to a method for optimizing the tolerancing of a set of flexible parts, said parts being particularly subjected to forces. The method that is the subject of the invention enables the definition, at the design phase, of an optimum tolerancing for flexible parts according to the assembly process plan thereof and according to the desired functional requirements. Said method considers that structural digital models (201, 202) are parts to be assembled. Said digital models (201, 202) are composed of the following information: - a plurality of points referred to as assembly points (220); - a plurality of points referred to as structural points (230); - mathematical relations, known as mechanical stiffness, such as a non-null relative displacement of a structural point (230) or an assembly point (220) in relation to the other structural or assembly points in a single digital model, modify a tensor in each of these points. From a mechanical point of view, these mathematical relations express the existence of an elastic recovery property between the points (220, 230) that make up the digital model (201, 202). The issue of optimization is simplified by: the definition of influence factors; the simulation of parts deviating from the nominal by a distortion vector.