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.

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.

An assembly sensitivity analysis method based on state space model

2017 ◽  
Vol 37 (2) ◽  
pp. 249-259 ◽  
Author(s):  
Xin Li ◽  
Jianzhong Shang ◽  
Hong Zhu
Keyword(s):  
Sensitivity Analysis ◽  
State Space ◽  
Process Parameters ◽  
State Space Model ◽  
System Level ◽  
System Response ◽  
Assembly Process ◽  
Content Type ◽  
Space Model ◽  
Variation Propagation

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.

The Modeling and Prediction of Gravity Deformation in Precision Machine Tool Assembly

2013 ◽  
Author(s):  
Junkang Guo ◽  
Jun Hong ◽  
Xiaopan Wu ◽  
Mengxi Wang ◽  
Yan Feng
Keyword(s):  
Machine Tool ◽  
State Space ◽  
State Space Model ◽  
Variation Theory ◽  
Assembly Process ◽  
Motion Error ◽  
Space Model ◽  
Precision Machine ◽  
Variation Propagation ◽  
Tool Assembly

The variation propagation in mechanical assembly is an important topic in several research fields, such as computer aided tolerancing (CAT) and product quality control. Mathematical models and analysis methods have been developed to solve this practical problem. Tolerance analysis which is based on the rigid hypothesis can be used to simulate the mass manufacturing and assembly. The state space model and stream of variation theory are mainly applied in flexible part assembly. However, in precision machine tool assembly, both tolerance design and process planning critically impact the accuracy performance, mainly because of the fact that the gravity deformation, including the part deformation and the variation in the joint of two connecting parts, cannot be ignored in variation propagation analysis. In this paper, based on the new generation GPS (Geometrical Product Specification and Verification) standards, the verification and modeling of key characteristics variation due to gravity deformation of single part and adjacent parts are discussed. The accurate evaluation of position and orientation variation taking into account form errors and gravity deformation can be solved from this model by FEM. A mathematical model considering rail error, stiffness of bearings is introduced to simulate the motion error in gravity effect. Based on this work to more accurately calculate the variation propagation considering gravity impact, a state space model describing the assembly process of machine tools is proposed. Then, in any assembly process, the final accuracy can be predicted to find out whether the accuracy is out of design requirement. The validity of this method is verified by a simulation of the assembly of a precision horizontal machining center.

An empirical study-based state space model for multilayer overlay errors in the step-scan lithography process

RSC Advances ◽  
2015 ◽  
Vol 5 (126) ◽  
pp. 103901-103906 ◽  
Author(s):  
Fuyun He ◽  
Zhisheng Zhang
Keyword(s):  
Empirical Study ◽  
State Space ◽  
Integrated Circuit ◽  
Manufacturing Process ◽  
Semiconductor Manufacturing ◽  
State Space Model ◽  
Key Factors ◽  
Space Model ◽  
Lithography Process ◽  
Multistage Manufacturing

In semiconductor manufacturing, the multilayer overlay lithography process is a typical multistage manufacturing process; one of the key factors that restrict the reliability and yield of integrated circuit chips is overlay error between the layers.

Research on Alignment Error of Cable-Stayed Bridge Based on Stream of Variation

2012 ◽  
Vol 178-181 ◽  
pp. 2439-2443
Author(s):  
Lin Shen ◽  
Lai Jun Liu
Keyword(s):  
State Space Model ◽  
Evaluation Index ◽  
Variation Theory ◽  
Alignment Error ◽  
Space Model ◽  
Cable Stayed Bridge ◽  
Long Span ◽  
Assembly Method ◽  
Stream Of Variation ◽  
Time Linear

Based on the model of discrete-time linear systems, the paper builds up the state space model of cantilever assembly method by studying the stream of variation theory. To address the problem of evaluation in alignment error, the evolution index of comprehensive stability is presented after comparing the advantage and disadvantage of evaluation index of point stability and evaluation index of slope stability. The method of evolution index of comprehensive stability is demonstrated by evaluating the alignment error of a long-span cable-stayed bridge, and it can accurately evaluate the error of assembly process.

scholarly journals Variation propagation modelling in multistage machining processes using dual quaternions

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2987-2998
Author(s):  
Filmon Yacob ◽  
Daniel Semere
Keyword(s):  
Motion Vector ◽  
Manufacturing Processes ◽  
Machining Processes ◽  
Dual Quaternions ◽  
Multistage Manufacturing ◽  
Differential Motion ◽  
Variation Propagation ◽  
Stream Of Variation ◽  
Matrix Differential ◽  
Propagation Modelling

Abstract Variation propagation models play an important role in part quality prediction, variation source identification, and variation compensation in multistage manufacturing processes. These models often use homogenous transformation matrix, differential motion vector, and/or Jacobian matrix to represent and transform the part, tool and fixture coordinate systems and associated variations. However, the models end up with large matrices as the number features and functional element pairs increase. This work proposes a novel strategy for modelling of variation propagation in multistage machining processes using dual quaternions. The strategy includes representation of the fixture, part, and toolpath by dual quaternions, followed by projection locator points onto the features, which leads to a simplified model of a part-fixture assembly and machining. The proposed approach was validated against stream of variation models and experimental results reported in the literature. This paper aims to provide a new direction of research on variation propagation modelling of multistage manufacturing processes.

scholarly journals Design Evaluation of Multi-station Assembly Processes by Using State Space Approach

2002 ◽  
Vol 124 (3) ◽  
pp. 408-418 ◽  
Author(s):  
Yu Ding ◽  
Dariusz Ceglarek ◽  
Jianjun Shi
Keyword(s):  
State Space ◽  
Process Design ◽  
State Space Model ◽  
System Level ◽  
Space Representation ◽  
System Response ◽  
Design Evaluation ◽  
Assembly Process ◽  
Sensitivity Indices ◽  
Variation Propagation

This paper considers the problem of evaluating and benchmarking process design configuration in a multi-station assembly process. We focus on the unique challenges brought by the multi-station system, namely, (1) a system level model to characterize the variation propagation in the entire process, and (2) the necessity to describe the system response to variation inputs at both global (system level) and local (station level and single fixture level) scales. State space representation is employed to recursively describe the propagation of variation in such a multi-station process, incorporating process design information 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 process design configuration. Implication of these indices with respect to variation control is discussed and a three-step procedure of applying the sensitivity indices for selecting a better design and prioritizing the critical station/fixture is presented. We illustrate the proposed method using the group of sensitivity indices in design evaluation of the assembly process of an SUV (Sport Utility Vehicle) side panel.

Variation Propagation Analysis on Compliant Assemblies Considering Contact Interaction

2006 ◽  
Author(s):  
Kang Xie ◽  
Lee Wells ◽  
Jaime A. Camelio ◽  
Byeng D. Youn
Keyword(s):  
Linear Response ◽  
Reduction Method ◽  
Linear Process ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Dimension Reduction Method ◽  
Propagation Analysis ◽  
Variation Propagation ◽  
Non Linear ◽  
Dimensional Variation

Dimensional variation is inherent to any manufacturing process. In order to minimize its impact on assembly products is important to understand how it propagates through the assembly process. Unfortunately, manufacturing processes are complex and in many cases highly non-linear. Traditional assembly models have represented assembly as a linear process. However, assemblies that include the contact between their components and tools show a highly non-linear response. This paper presents a new assembly methodology considering the contact effect. In addition, an efficient to predict output response is presented. The enhance dimension reduction method (eDR) is used to accurately and efficiently predict the statistical response of the assembly to variation on the input parameters.

Method of Identifying Key Quality Characteristics in Multistage Manufacturing Process Based on PLSR

2012 ◽  
Vol 217-219 ◽  
pp. 2580-2584 ◽  
Author(s):  
Ning Wang ◽  
Ji Chao Xu ◽  
Jian Feng Yang
Keyword(s):  
State Space ◽  
Manufacturing Process ◽  
State Space Model ◽  
Quality Characteristics ◽  
The State ◽  
Quality Analysis ◽  
Least Squares Regression ◽  
Space Model ◽  
Multistage Manufacturing ◽  
And Control

To improve the existing methods of identifying the key quality characteristics in multistage manufacturing process, the partial least squares regression (PLSR) method is combined with the state space model that a new method of identifying the key quality characteristics in multistage manufacturing process based on PLSR is proposed. According to the feature of multistage manufacturing process, the state space model is introduced to build the key quality characteristics identifying model for multistage manufacturing process, using the PLSR method to solve the problem of the quality characteristics such as multicollinearity, do model analyzing and identify the key quality characteristics. At last, the cigarette production process is presented as an example to introduce the application of this method. The result shows that this method can not only identify the key quality characteristics in multistage manufacturing process, but also establish the model of output quality effecting of all levels on the final product quality and its quality characteristics relationship, which reflect the structure of the multistage manufacturing process and causal relationship between quality characteristics at all process levels, provide the basis for quality analysis and control in multistage manufacturing process.

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