Combination modeling of auto body assembly dimension propagation considering multi-source information for variation reduction

2019 ◽  
Vol 39 (4) ◽  
pp. 514-522
Author(s):  
Yinhua Liu ◽  
Shiming Zhang ◽  
Guoping Chu
Keyword(s):  
Modeling Method ◽  
Propagation Model ◽  
Source Information ◽  
Content Type ◽  
Variation Reduction ◽  
Combination Model ◽  
Model Based ◽  
Variation Propagation ◽  
Variable Weight ◽  
Assembly Deviation

PurposeThis paper aims to present a combination modeling method using multi-source information in the process to improve the accuracy of the dimension propagation relationship for assembly variation reduction.Design/methodology/approachBased on a variable weight combination prediction method, the combination model that takes the mechanism model and data-driven model based on inspection data into consideration is established. Furthermore, the combination model is applied to qualification rate prediction for process alarming based on the Monte Carlo simulation and also used in engineering tolerance confirmation in mass production stage.FindingsThe combination model of variable weights considers both the static theoretical mechanic variation propagation model and the dynamic variation relationships from the regression model based on data collections, and provides more accurate assembly deviation predictions for process alarming.Originality/valueA combination modeling method could be used to provide more accurate variation predictions and new engineering tolerance design procedures for the assembly process.

A modification of DMVs based state space model of variation propagation for multistage machining processes

2017 ◽  
Vol 37 (4) ◽  
pp. 381-390 ◽  
Author(s):  
Fuyong Yang ◽  
Sun Jin ◽  
Zhimin Li
Keyword(s):  
Current Model ◽  
Propagation Model ◽  
Machining Processes ◽  
Motion Vectors ◽  
Content Type ◽  
Model Based ◽  
Differential Motion ◽  
Variation Propagation ◽  
Current Variation ◽  
Differential Motion Vectors

Purpose Complicated workpiece, such as an engine block, has special rough locating datum features (i.e. six independent datum features) due to its complex structure. This locating datum error cannot be handled by current variation propagation model based on differential motion vectors. To extend variation prediction fields, this paper aims to solve the unaddressed variation sources to modify current model for multistage machining processes. Design/methodology/approach To overcome the limitation of current variation propagation model based on differential motion vectors caused by the unaddressed variation sources, this paper will extend the current model by handling the unaddressed datum-induced variation and its corresponding fixture variation. Findings The measurement results of the rear face with respect to the rough datum W and the pan face with respect to the hole Q by coordinate measuring machine (CMM) are −0.006 mm and 0.031 mm. The variation results for rear face and pan face predicted by the modified model are −0.009 mm and 0.025 mm, respectively. The discrepancy of model prediction and measurement is very small. Originality/value This paper modifies the variation propagation model based on differential motion vectors by solving the unaddressed variation sources, which can extend the variation prediction fields for some complicated workpiece and is useful in the future work for many fields, such as process monitoring, fault diagnosis, quality-assured setup planning and process-oriented tolerancing.

Propagation analysis of variation for fuselage structures in multi-station aircraft assembly

2018 ◽  
Vol 38 (1) ◽  
pp. 67-76 ◽  
Author(s):  
Liang Cheng ◽  
Qing Wang ◽  
Jiangxiong Li ◽  
Yinglin Ke
Keyword(s):  
Propagation Model ◽  
Analysis Approach ◽  
Good Prediction ◽  
Assembly Process ◽  
Content Type ◽  
Modeling And Analysis ◽  
Aircraft Assembly ◽  
Propagation Analysis ◽  
Variation Propagation ◽  
Large Aircraft

Purpose This paper aims to present a modeling and analysis approach for multi-station aircraft assembly to predict assembly variation. The variation accumulated in the assembly process will influence the dimensional accuracy and fatigue life of airframes. However, in digital large aircraft assembly, variation propagation analysis and modeling are still unresolved issues. Design/methodology/approach Based on an elastic structure model and variation model of multistage assembly in one station, the propagation of key characteristics, assembly reference and measurement errors are introduced. Moreover, the reposition and posture coordination are considered as major aspects. The reposition of assembly objects in a different assembly station is described using transformation and blocking of coefficient matrix in finite element equation. The posture coordination of the objects is described using homogeneous matrix multiplication. Then, the variation propagation model and analysis of large aircraft assembly are established using a discrete system diagram. Findings This modeling and analysis approach for multi-station aircraft assembly reveals the basic rule of variation propagation between adjacent assembly stations and can be used to predict assembly variation or potential dimension problems at a preliminary assembly phase. Practical implications The modeling and analysis approaches have been used in a transport aircraft project, and the calculated results were shown to be a good prediction of variation in the actual assembly. Originality/value Although certain simplifications and assumptions have been imposed, the proposed method provides a better understanding of the multi-station assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.

Multi-Operational Machining Processes Modeling for Sequential Root Cause Identification and Measurement Reduction

2004 ◽  
Author(s):  
Hui Wang ◽  
Qiang Huang ◽  
Reuven Katz
Keyword(s):  
Machine Tool ◽  
Propagation Model ◽  
Machining Processes ◽  
Error Sources ◽  
Variation Reduction ◽  
Measurement Reduction ◽  
Propagation Modeling ◽  
Root Cause ◽  
Variation Propagation ◽  
Root Cause Identification

Variation propagation modeling has been proved to be an effective way for variation reduction and design synthesis in multi-operational manufacturing processes (MMP). However, previously developed approaches for machining processes did not directly model the process physics regarding how fixture, and datum, and machine tool errors generate the same pattern on part features. Consequently, it is difficult to distinguish error sources at each operation. This paper formulates the variation propagation model using the proposed equivalent fixture error (EFE) concept. With this concept, datum error and machine tool error are transformed to equivalent fixture locator errors at each operation. As a result, error sources can be grouped and root cause identification can be conducted in a sequential manner. The case studies demonstrate the model validity through a real cutting experiment and model advantage in measurement reduction for root cause identification.

Improved GM(1, 1) model based on concave sequences and its applications

2017 ◽  
Vol 7 (3) ◽  
pp. 343-352
Author(s):  
Xinhai Kong ◽  
Peng Zhang ◽  
Xin Ma
Keyword(s):  
Design Methodology ◽  
Modeling Method ◽  
Content Type ◽  
Sequence Modeling ◽  
Model Based ◽  
Convex Sequence ◽  
Gas Consumption ◽  
Symmetry Transformations ◽  
Natural Gas Consumption ◽  
Practical Implications

Purpose The purpose of this paper is to improve the GM(1, 1) model based on concave sequences. Design/methodology/approach First, the restored sequence of the GM(1, 1) model is proved to be convex, and the residual characters of the GM(1, 1) model for concave sequences are analyzed. Second, two symmetry transformations are introduced to transform an original concave sequence into a convex sequence, and then the GM(1, 1) model is established based on the convex sequence. Findings Compared with the traditional modeling method, the new method has high accuracy and is applicable for all concave sequence modeling. Practical implications Two cases are used to illustrate the superiority of this modeling method. Case A is to predict China’s per capita natural gas consumption, and case B is to predict the annual output of an oilfield. Originality/value The application scope of GM (1, 1) model is greatly extended.

Assembly variation analysis of the non-rigid assembly with a deformation gradient model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ibrahim Ajani ◽  
Cong Lu
Keyword(s):  
Deformation Gradient ◽  
Transformation Matrix ◽  
Propagation Model ◽  
Assembly Process ◽  
Content Type ◽  
Target Value ◽  
Gradient Model ◽  
Variation Propagation ◽  
Target Values ◽  
Gradient Models

Purpose This paper aims to develop a mathematical method to analyze the assembly variation of the non-rigid assembly, considering the manufacturing variations and the deformation variations of the non-rigid parts during the assembly process. Design/methodology/approach First, this paper proposes a deformation gradient model, which represents the deformation variations during the assembly process by considering the forces and the self-weight of the non-rigid parts. Second, the developed deformation gradient models from the assembly process are integrated into the homogenous transformation matrix to model the deformation variations and manufacturing variations of the deformed non-rigid part. Finally, a mathematical model to analyze the assembly variation propagation is developed to predict the dimensional and geometrical variations due to the manufacturing variations and the deformation variations during the assembly process. Findings Through the case study with a crosshead non-rigid assembly, the results indicate that during the assembly process, the individual deformation values of the non-rigid parts are small. However, the cumulative deformation variations of all the non-rigid parts and the manufacturing variations present a target value (w) of −0.2837 mm as compared to a target value of −0.3995 mm when the assembly is assumed to be rigid. The difference in the target values indicates that the influence of the non-rigid part deformation variations during the assembly process on the mechanical assembly accuracy cannot be ignored. Originality/value In this paper, a deformation gradient model is proposed to obtain the deformation variations of non-rigid parts during the assembly process. The small deformation variation, which is often modeled using a finite-element method in the existing works, is modeled using the proposed deformation gradient model and integrated into the nominal dimensions. Using the deformation gradient models, the non-rigid part deformation variations can be computed and the accumulated deformation variation can be easily obtained. The assembly variation propagation model is developed to predict the accuracy of the non-rigid assembly by integrating the deformation gradient models into the homogeneous transformation matrix.

Dimensional variation propagation modeling and analysis for single-station assembly based on multiple constraints graph

2016 ◽  
Vol 36 (3) ◽  
pp. 308-317 ◽  
Author(s):  
Jian-feng Yu ◽  
Wen-Bin Tang ◽  
Yuan Li ◽  
Jie Zhang
Keyword(s):  
Geometric Constraints ◽  
Multiple Constraints ◽  
Content Type ◽  
Modeling And Analysis ◽  
Variation Reduction ◽  
Propagation Modeling ◽  
Variation Propagation ◽  
Single Station ◽  
Accumulation Mechanism ◽  
Dimensional Variation

Purpose Modeling and analysis of dimensional variation propagation is a crucial support technology for variation reduction, product/process design evaluation and recognition of variation source. However, owing to the multi-deviation (i.e. part deviations and fixture deviations) and multi-interaction (i.e. part-to-part interaction, part-to-fixture interaction and station-to-station interaction) in assembly processes, it is difficult for designers to describe or understand the variation propagation (or accumulation) mechanism clearly. The purpose of this paper is to propose a variation propagation modeling and analysis (VPMA) method based on multiple constraints aiming at a single station. Design/methodology/approach Initially, part-to-part constraints (PPCs) and part-to-fixture constraints (PFCs) are applied for the multi-interaction of assembly, and multiple constraints graph (MCG) model is proposed for expressing PPCs, PFCs, parts, as well as the variation propagation relation among them. Then, locating points (LPs) are adopted for representing the deviations in constraints, and formulas for calculating the deviations of LPs are derived. On that basis, a linearized relation between LPs’ deviations and part’s locating deviations is derived. Finally, a wing box is presented to validate the proposed method, and the results indicate the methodology’s feasibility. Findings MCG is an effective tool for dimensional VPMA, which is shown as an example of this paper. Originality/value Functions of geometric constraints in dimensional variation propagation are revealed, and MCG is proposed to formulize dimensional variation propagation.

Analysis and optimization of assembly precision-cost model based on 3D tolerance expression

2018 ◽  
Vol 38 (4) ◽  
pp. 497-510 ◽  
Author(s):  
Wei Sun ◽  
Xiaokai Mu ◽  
Qingchao Sun ◽  
Zhiyong Sun ◽  
Xiaobang Wang
Keyword(s):  
Upper Bound ◽  
Cost Model ◽  
Low Cost ◽  
Great Influence ◽  
Small Displacement ◽  
Content Type ◽  
Model Based ◽  
Manufacturing Tolerances ◽  
Assembly Deviation ◽  
Assembly Precision

PurposeThis paper aims to comprehensively achieve the requirements of high assembly precision and low cost, a precision-cost model of assembly based on three-dimensional (3D) tolerance is established in this paper.Design/methodology/approachThe assembly precision is related to the tolerance of parts and the deformation of matching surfaces under load. In this paper, the small displacement torsor (SDT) theory is first utilized to analyze the manufacturing tolerances of parts and the assembly deformation deviation of matching surface. In the meanwhile, the extracting method of SDT parameters is proposed and the assembly precision calculation model based on the 3D tolerance is established. Second, an integrated optimization model based on the machining cost, assembly cost (mapping the deviation domain to the SDT domain) and quality loss cost is built. Finally, the practicability of the precision-cost model is verified by optimizing the horizontal machining center.FindingsThe assembly deviation has a great influence on cost fluctuation. By setting the optimization objective to maximize the assembly precision, the optimal total cost is CNY 72.77, decreasing by 16.83 per cent from the initial value, which meets economical requirements. Meanwhile, the upper bound of each processing tolerance is close to the maximum value of 0.01 mm, indicating that the load deformation can be offset by appropriately increasing the upper bound of the tolerance, but it is necessary to strictly restrict the manufacturing tolerances of lower parts in a reasonable range.Originality/valueIn this paper, a 3D deviation precision-cost model of assembly is established, which can describe the assembly precision more accurately and achieve a lower cost compared with the assembly precision model based on rigid parts.

Dynamic prediction and compensation of aerocraft assembly variation based on state space model

2015 ◽  
Vol 35 (2) ◽  
pp. 183-189 ◽  
Author(s):  
Yujun Cao ◽  
Xin Li ◽  
Zhixiong Zhang ◽  
Jianzhong Shang
Keyword(s):  
State Space ◽  
State Space Model ◽  
Propagation Model ◽  
Small Displacement ◽  
Assembly Process ◽  
Dynamic Prediction ◽  
Content Type ◽  
Assembly Accuracy ◽  
Variation Propagation ◽  
State Space Theory

Purpose – This paper aims to clarify the predicting and compensating method of aeroplane assembly. It proposes modeling the process of assembly. The paper aims to solve the precision assembly of aeroplane, which includes predicting the assembly variation and compensating the assembly errors. Design/methodology/approach – The paper opted for an exploratory study using the state space theory and small displacement torsor theory. The assembly variation propagation model is established. The experiment data are obtained by a real small aeroplane assembly process. Findings – The paper provides the predicting and compensating method for aeroplane assembly accuracy. Originality/value – This paper fulfils an identified need to study how the assembly variation propagates in the assembly process.

Estimation of form deviation and the associated uncertainty in coordinate metrology

2015 ◽  
Vol 32 (5) ◽  
pp. 456-471 ◽  
Author(s):  
Abdelilah Jalid ◽  
Said Hariri ◽  
Jean Paul Senelaer
Keyword(s):  
Optimization Method ◽  
Propagation Model ◽  
Form Error ◽  
Content Type ◽  
Measurement Result ◽  
Model Based ◽  
Circularity Error ◽  
Measuring Machine ◽  
The Law ◽  
Propagation Of Uncertainties

Purpose – The uncertainty evaluation for coordinate measuring machine metrology is problematic due to the diversity of the parameters that can influence the measurement result. From discrete coordinate data taken on curve (or surface) the software of these machines proceeds to an identification of the measured feature, the parameters of the substitute feature serve in the phase of calculation to estimate the form error of form, and the decisions made based on the result measurement may be outliers when the uncertainty associated to the measurement result is not taken into account. The paper aims to discuss these issues. Design/methodology/approach – The authors relied on the orthogonal distance regression (ODR) algorithm to estimate the parameters of the substitute geometrical elements and their uncertainties. The solution of the problem is resolved by an iterative calculation according to the Levenberg Marquard optimization method. The authors have also presented in this paper the propagation model of uncertainties to the circularity error. This model is based on the law of propagation of the uncertainties defined in the GUM. Findings – This work proposes a model based on ODR to estimates parameters of the substitute geometrical elements and their uncertainties. This contribution allows us to estimate the uncertaintof the form error by applying the law of propagation of uncertainties. An example of calculating the circularity error and the associated uncertainty is explained. This method can be applied to others geometry type: line, plan, sphere, cylinder and cone. Practical implications – This work interested manufacturing firms by allowing them: to meet the normative, which requires that each measurement must be accompanied by its uncertainty-in conformity assessment, the decision-making must take account of this uncertainty to avoid the aberrant decisions. Informing the operators on the capability of their measurement process Originality/value – This work proposes a model based on ODR to estimates parameters of the substitute geometrical elements and its uncertainties. without the hypothesis of small displacements torsor, this method integrates the uncertainty on the coordinates of points and can be applied in any reference placemark. This contribution allows us also to estimate the uncertainty of the form error by applying the law of propagation of uncertainties.

Stream of Variation Modeling and Analysis for Compliant Composite Part Assembly— Part II: Multistation Processes

2016 ◽  
Vol 138 (12) ◽  
Author(s):  
Tingyu Zhang ◽  
Jianjun Shi
Keyword(s):  
State Space Model ◽  
Laminated Plates ◽  
Propagation Model ◽  
Composite Part ◽  
Modeling And Analysis ◽  
Variation Reduction ◽  
Variation Propagation ◽  
Single Station ◽  
Stream Of Variation ◽  
Multistation Assembly

Part I of this paper (Zhang and Shi, 2015, “Stream of Variation Modeling and Analysis for Compliant Composite Part Assembly—Part I: Single-Station Processes,” ASME J. Manuf. Sci. Eng.,) has studied the variation modeling and analysis of compliant composite part assembly in a single-station process. In practice, multiple assembly stations are involved in assembling the final product. This paper aims to develop a variation propagation model for stream of variation analysis in a multistation assembly process for composite parts. This model takes into account major variation factors, including part manufacturing error (PME), fixture position error (FPE), and relocation-induced error (RIE). With the help of a finite element method (FEM), a state space model (SSM) is established to represent the relationships between the sources of variation and the final assembly variation. The developed methodology is illustrated by using a case study of three composite laminated plates assembled in a two-station assembly system. The validity of the developed SSM is verified by Monte Carlo simulation (MCS), which is implemented on the basis of FEM. The SSM provides a potential application for diagnosis of variation sources and variation reduction.

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