Search results

This study aims to present a model and analysis of automotive body outer cover panels (OCPs) assembly systems to predict assembly variation. In the automotive industry, the OCPs assembly process directly influences the quality of the automobile body appearance. However, suitable models to describe variation propagation of OCPs assembly systems remain unknown.

An adaptive state space model for OCPs assembly systems is introduced to accurately express variation propagation, including variation accumulation and transition, where two compliant deviations make impacts on key product characteristics (KPCs) of OCP, and the impacts are accumulated from welding process to threaded connection process. Another new source of variation from threaded connection is included in this model. To quantify the influence of variation from threaded connection on variation propagation, the threaded connection sensitivity matrix is introduced to build up a linear relationship between deviation from threaded connection and output deviation in KPCs. This matrix is solved by homogeneous coordinate transformation. The final deviation of KPCs will be transferred to ensure gaps and flushes between two OCPs, and the transition matrix is considered as a unit matrix to build up the transition relationship between different states.

A practical case on the left side body structure is described, where simulation result of variation propagation reveals the basic rule of variation propagation and the significant effect of variation from threaded connection on variation propagation of OCPs assembly system.

The model can be used to predict assembly variation or potential dimension problems at a preliminary assembly phase. The calculated results of assembly variation guide designers or technicians on tolerance allocation, fixture layout design and process planning.

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.

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.

MCG is an effective tool for dimensional VPMA, which is shown as an example of this paper.

Functions of geometric constraints in dimensional variation propagation are revealed, and MCG is proposed to formulize dimensional variation propagation.

Assembly variations, which will propagate along the assembly process, are inevitable and difficult to analyze in Aeronautical Thin‐Walled Structures (ATWS) assembly. The purpose of this paper is to present a new method for analyzing the variation propagation of ATWS with automated riveting.

The paper addresses the variation propagation model and method by first, forming a novel Stage‐State model to represent the process of automated riveting. Second, the effect of positioning error on assembly variation is defined as propagation variation (PV), and propagation matrix of key characteristic points (KCP) is discussed. Third, the effect between the variations in each stage is defined as expansion variation (EV). According to the analysis of mismatch error and the reference transformation, the expansion matrix is formed.

The model can solve the variation propagation problem of ATWS with automated riveting efficiently, which is shown as an example of this paper.

The variation obtained by the model and method presented in this paper is in conformity with the variation measured in experiments.

The propagation variation and expansion variation is proposed for the first time, and variations are studied according to novel propagation matrix and expansion matrix.

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.

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.

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.

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.

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.

This 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.

Based 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.

The 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.

A combination modeling method could be used to provide more accurate variation predictions and new engineering tolerance design procedures for the assembly process.

Dimensional variation management is a major challenge in multi‐station sheet metal assembly processes involving complex products such as automotive body and aircraft fuselage assemblies. Very few studies have explored it at a preliminary design phase taking into consideration effects of part deformation on variation propagation, since early design phase involves the development of imprecise design models with scant or incomplete product and process knowledge. The objective of this paper is to present a variation model which can be built into the preliminary design phase taking into consideration all of the existing interactions between flexible parts and tools in multi‐station sheet metal assembly process.

The paper addresses this problem by first, presenting a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; second, determining the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and third, utilizing this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.

This paper presents a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; determines the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and utilizes this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.

A truck cab assembly is presented to demonstrate the advantages of the proposed model over the state‐of‐the‐art approach used in industry for sheet metal assemblies.

Manufacturing errors, which will propagate along the assembly process, are inevitable and difficult to analyze for complex products, such as aircraft. To realize the goal of precise assembly for an aircraft, with revealing the nonlinear transfer mechanism of assembly error, a set of analytical methods with response to the assembly error propagation process are developed. The purpose of this study is to solve the error problems by modeling and constructing the coordination dimension chain to control the consistency of accumulated assembly errors for different assemblies.

First, with the modeling of basic error sources, mutual interaction relationship of matting error and deformation error is analyzed, and influence matrix is formed. Second, by defining coordination datum transformation process, practical establishing error of assembly coordinate system is studied, and the position of assembly features is modified with actual relocation error considering datum changing. Third, considering the progressive assembly process, error propagation for a single assembly station and multi assembly stations is precisely modeled to gain coordination error chain for different assemblies, and the final coordination error is optimized by controlling the direction and value of accumulated error range.

Based on the proposed methodology, coordination error chain, which has a direct influence on the property of stealthy and reliability for modern aircrafts, is successfully constructed for the assembly work of the jointing between leading edge flap component and wing component at different assembly stations.

Precise assembly work at different assembly stations is completed to verify methodology’s feasibility. With analyzing the main comprised error items and some optimized solutions, benefit results for the practical engineering application showing that the maximum value of the practical flush of the profiles between the two components is only 0.681 mm, the minimum value is only 0.021 mm, and the average flush of the entire wing component is 0.358 mm, which are in accordance with theoretical calculation results and can successfully fit the assembly requirement. The potential user can be the engineers for manufacturing the complex products.

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.

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.

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.

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.

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research.

To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change.

Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters.

A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.

Thin-walled structures inevitably always have manufacturing deviations, which affects the assembly quality of mechanical products. The assembly quality directly determines the performances, reliability and service life of the products. To achieve the automatic assembly of large-scale thin-walled structures, the sizing force of the structures with deviations should be calculated, and its assembling ability should be studied before assembly process. The purpose of this study is to establish a precise model to describe the deviations of structures and to study the variation propagation during assembly process.

Curved thin-walled structures are modeled by using the shell element via the absolute nodal coordinate formulation. Two typical deviation modes of the structure are defined. The generalized elastic force of shell elements with anisotropic materials is deduced based on a continuum mechanics approach to account for the geometric non-linearity. The quasi-static method is introduced to describe the assembly process. The effects of the deviation forms, geometrical parameters of the thin-walled structures and material properties on assembly quality are investigated numerically.

The geometric non-linearity of structure and anisotropy of materials strongly affect the variation propagation and the assembly quality. The transformation and accumulation effects of the deviations are apparent in the multiple assembly process. The constraints on the structures during assembly can reduce assembly deviation.

The plate element via the absolute nodal coordinate formulation is first introduced to the variation propagation analysis. Two typical shape deviation modes are defined. The elastic force of structures with anisotropic materials is deduced. The variation propagation during the assembly of structures with various geometrical and material parameters is investigated.