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.

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.

Stream of Variation Modeling and Analysis for Compliant Composite Part Assembly—Part I: Single-Station Processes

2016 ◽  
Vol 138 (12) ◽  
Author(s):  
Tingyu Zhang ◽  
Jianjun Shi
Keyword(s):  
New York ◽  
Composite Structures ◽  
Weight Ratio ◽  
High Strength ◽  
Laminated Plates ◽  
Composite Part ◽  
Modeling And Analysis ◽  
Single Station ◽  
Assembly Deviation ◽  
The Impact

Composite structures are widely used due to their superior properties, such as low density, high strength, and high stiffness-to-weight ratio (Mallick, 1993, Fiber-Reinforced Composites: Materials, Manufacturing, and Design, Marcel Dekker, New York). However, the lack of methodologies for variation modeling and analysis of composite part assembly has imposed a significant constraint on developing dimensional control for composite assembly processes. This paper develops a modeling method to predict assembly deviation for compliant composite parts in a single-station assembly process. The approach is discussed in two steps: considering the part manufacturing error (PME) only and considering both the PME and the fixture position error (FPE). Finite element method (FEM) and homogenous coordinate transformation are used to reveal the impact of the PME and the FPE. The validity of the method is verified with two case studies on assembly deviation prediction of two composite laminated plates considering the PME only and both the PME and the FPE, respectively. The proposed method provides the basis for assembly deviation prediction in the multistation composite assembly.

Diagnosability Analysis of Multi-Station Manufacturing Processes

2001 ◽  
Vol 124 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Yu Ding ◽  
Jianjun Shi ◽  
Dariusz Ceglarek
Keyword(s):  
Manufacturing Process ◽  
State Space Model ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Space Model ◽  
Distribution Strategy ◽  
Variation Propagation ◽  
Distribution Scheme ◽  
Stream Of Variation ◽  
Comprehensive Study

Variation propagation in a multi-station manufacturing process (MMP) is described by the theory of “Stream of Variation.” Given that the measurements are obtained via certain sensor distribution scheme, the problem of whether the stream of variation of an MMP is diagnosable is of great interest to both academia and industry. We present a comprehensive study of the diagnosability of MMPs in this paper. It is based on the state space model and is parallel to the concept of observability in control theory. Analogous to the observability matrix and index, the diagnosability matrix and index are first defined and then derived for MMP systems. The result of diagnosability study is applied to the evaluation of sensor distribution strategy. It can also be used as the basis to develop an optimal sensor distribution algorithm. An example of a three-station assembly process with multi-fixture layouts is presented to illustrate the methodology.

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.

Diagnosability Analysis of Multi-Station Manufacturing Processes

Manufacturing ◽  
2002 ◽  
Author(s):  
Yu Ding ◽  
Jianjun Shi ◽  
Dariusz Ceglarek
Keyword(s):  
Manufacturing Process ◽  
State Space Model ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Space Model ◽  
Distribution Strategy ◽  
Variation Propagation ◽  
Distribution Scheme ◽  
Stream Of Variation ◽  
Comprehensive Study

Variation propagation in a multi-station manufacturing process (MMP) is described by the theory of “Stream of Variation.” Given that the measurements are obtained via certain sensor distribution scheme, the problem of whether the stream of variation of an MMP is diagnosable is of great interest to both academia and industry. We present a comprehensive study of the diagnosability of MMPs in this paper. It is based on the state space model and is parallel to the concept of observability in control theory. Analogous to the observability matrix and index, the diagnosability matrix and index are first defined and then derived for MMP systems. The result of diagnosability study is applied to the evaluation of sensor distribution strategy. It can also be used as the basis to develop an optimal sensor distribution algorithm. An example of a three-station assembly process with multi-fixture layouts is presented to illustrate the methodology.

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.

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.

Stream-of-Variation Modeling—Part I: A Generic Three-Dimensional Variation Model for Rigid-Body Assembly in Single Station Assembly Processes

2007 ◽  
Vol 129 (4) ◽  
pp. 821-831 ◽  
Author(s):  
Wenzhen Huang ◽  
Jijun Lin ◽  
Michelle Bezdecny ◽  
Zhenyu Kong ◽  
Dariusz Ceglarek
Keyword(s):  
Rigid Body ◽  
Manufacturing Systems ◽  
Three Dimensional ◽  
Single Station ◽  
Generic Modeling ◽  
Stream Of Variation ◽  
Product And Process ◽  
Industrial Software ◽  
Multistation Assembly ◽  
Relationship Of

A stream-of-variation analysis (SOVA) model for three-dimensional (3D) rigid-body assemblies in a single station is developed. Both product and process information, such as part and fixture locating errors, are integrated in the model. The model represents a linear relationship of the variations between key product characteristics and key control characteristics. The generic modeling procedure and framework are provided, which involve: (1) an assembly graph (AG) to represent the kinematical constraints among parts and fixtures, (2) an unified method to transform all constraints (mating interface and fixture locators etc.) into a 3-2-1 locating scheme, and (3) a 3D rigid model for variation flow in a single-station process. The generality of the model is achieved by formulating all these constraints with an unified generalized fixture model. Thus, the model is able to accommodate various types of assemblies and provides a building block for complex multistation assembly model, in which the interstation interactions are taken into account. The model has been verified by using Monte Carlo simulation and a standardized industrial software. It provides the basis for variation control through tolerance design analysis, synthesis, and diagnosis in manufacturing systems.

Stream of Variation Modeling and Analysis of Serial-Parallel Multistage Manufacturing Systems

2004 ◽  
Vol 126 (3) ◽  
pp. 611-618 ◽  
Author(s):  
Qiang Huang ◽  
Jianjun Shi
Keyword(s):  
Manufacturing Systems ◽  
Model Complexity ◽  
Modeling And Analysis ◽  
Multistage Manufacturing ◽  
Reduction Techniques ◽  
Process Route ◽  
Variation Propagation ◽  
Space Modeling ◽  
Multiple Routes ◽  
Stream Of Variation

In a Serial-Parallel Multistage Manufacturing System (SP-MMS), identical work-stations are utilized at each stage to meet the productivity and line balance requirements. In such a system, parts could go through different process routes and some routes may merge at certain stage(s). Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a system. This paper extends the state space modeling approach from single process route to the SP-MMS with multiple routes. Several model dimension reduction techniques are proposed to reduce model complexity. Properties of these techniques are studied from the perspectives of system representation and diagnosability. Furthermore, these techniques are applied to analyze system measurement strategies.

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.

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