Tolerance Analysis and Diagnosis Model of Compliant Block Assembly Considering Welding Deformation

2015 ◽  
Author(s):  
Junghyun Lee ◽  
Wooyoung Choi ◽  
Minseok Kang ◽  
Hyun Chung
Keyword(s):  
Tolerance Analysis ◽  
Normal Equation ◽  
Welding Distortion ◽  
Assembly Process ◽  
Accuracy Control ◽  
Mechanical Assembly ◽  
Multi Stage ◽  
Proposed Model ◽  
Diagnosis Model ◽  
Welding Processes

This paper proposes a simplified tolerance analysis and diagnosis model including the effects of welding distortion, for accuracy control in ship block assembly processes. The variation simulation model for tolerance analysis utilizes the concepts of the sources of variation and the compliant mechanical assembly model to include the welding distortions. The proposed model utilizes welding distortion patterns and a transformation matrix to efficiently model the deformation during the joining process. The diagnosis model assumes the multi-stage assemblies and that the variations of previous stages are propagated to the current stage. It calculates the sensitivity; a linear mapping from input parts to output assembly variations, and includes the effects of welding distortion as an additional vector that deviates the assembly variation further. The diagnosis model predicts the quantitative effect of each source of variations to the final assembly’s geometrical variation, based on normal equation and assembly stage’s state space equation model. The proposed model is applied to a realistic block assembly process for validation purpose. The model can effectively simulate the propagation of welding distortion as well as quantitatively identify variation patterns and welding processes throughout the multi-stage assembly process.

scholarly journals Reliability-based tolerance redesign of mechanical assemblies using Jacobian-Torsor model

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110132
Author(s):  
Bingxiang Wang ◽  
Xianzhen Huang ◽  
Miaoxin Chang
Keyword(s):  
Optimization Model ◽  
Economic Effect ◽  
Tolerance Analysis ◽  
Lambert W Function ◽  
Mechanical Assembly ◽  
Assembly Tolerance ◽  
Tolerance Optimization ◽  
Geometric Tolerances ◽  
Mechanical Assemblies ◽  
Proposed Model

The purpose of this paper is to present a new method to redesign dimensional and geometric tolerances of mechanical assemblies at a lower cost and with higher reliability. A parametric Jacobian-Torsor model is proposed to conduct tolerance analysis of mechanical assembly. A reliability-based tolerance optimization model is established. Differing from previous studies of fixed process parameters, this research determines the optimal process variances of tolerances, which provide basis for the subsequent assembly tolerance redesign. By using the Lambert W function and the Lagrange multiplier method, the analytical solution of the parametric tolerance optimization model is obtained. A numerical example is presented to demonstrate the effectiveness of the model, while the results indicate that the total cost is reduced by 10.93% and assembly reliability improves by 2.12%. This study presents an efficient reliability-based tolerance optimization model. The proposed model of tolerance redesign can be used for mechanical assembly with a better economic effect and higher reliability.

Variation Simulation of Compliant Metal Plate Assemblies Considering Welding Distortion

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Wooyoung Choi ◽  
Hyun Chung
Keyword(s):  
Welding Process ◽  
Offshore Structures ◽  
Welding Distortion ◽  
Influence Coefficient ◽  
Mechanical Assembly ◽  
Offshore Structure ◽  
Shipbuilding Industry ◽  
Proposed Model ◽  
Variation Simulation ◽  
Joining Process

The shipbuilding industry employs numerous cutting and joining processes to build the ship and offshore structure. Welding, as the primary joining process, inherently causes distortion and accounts for most of the major geometrical variation in the intermediate products (IPs), thus adversarially affecting the downstream assembly processes. Because of the welding process, the variation analysis of compliant assemblies in shipbuilding is clearly different from that of the automobile and aerospace industries, where the distortion during the joining process is negligible. This paper proposes a variation simulation model including the effects of joining process distortion for ships and offshore structures. The proposed model extends the concepts of the sources of variation and the method of influence coefficient (MIC) for a compliant mechanical assembly to include the welding distortions. The proposed model utilizes welding distortion patterns and a transformation matrix to efficiently model the deformation due to the joining process. Also the welding distortions are represented as stochastic values due to its randomness. The model is verified by case study simulation and by a comparison with welding experimental results.

A novel multi-stage ensemble model with multiple K-means-based selective undersampling: An application in credit scoring

2021 ◽  
Vol 40 (5) ◽  
pp. 9471-9484
Author(s):  
Yilun Jin ◽  
Yanan Liu ◽  
Wenyu Zhang ◽  
Shuai Zhang ◽  
Yu Lou
Keyword(s):  
Machine Learning ◽  
Predictive Accuracy ◽  
Credit Scoring ◽  
Imbalanced Data ◽  
Ensemble Model ◽  
Selective Sampling ◽  
Machine Learning Methods ◽  
Multi Stage ◽  
Proposed Model ◽  
New Feature

With the advancement of machine learning, credit scoring can be performed better. As one of the widely recognized machine learning methods, ensemble learning has demonstrated significant improvements in the predictive accuracy over individual machine learning models for credit scoring. This study proposes a novel multi-stage ensemble model with multiple K-means-based selective undersampling for credit scoring. First, a new multiple K-means-based undersampling method is proposed to deal with the imbalanced data. Then, a new selective sampling mechanism is proposed to select the better-performing base classifiers adaptively. Finally, a new feature-enhanced stacking method is proposed to construct an effective ensemble model by composing the shortlisted base classifiers. In the experiments, four datasets with four evaluation indicators are used to evaluate the performance of the proposed model, and the experimental results prove the superiority of the proposed model over other benchmark models.

A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition for corporate bankruptcy prediction

2020 ◽  
pp. 1-17
Author(s):  
Dongqi Yang ◽  
Wenyu Zhang ◽  
Xin Wu ◽  
Jose H. Ablanedo-Rosas ◽  
Lingxiao Yang ◽  
...  
Keyword(s):  
Fuzzy Clustering ◽  
Rapid Development ◽  
Optimization Method ◽  
Selection Method ◽  
Bankruptcy Prediction ◽  
Ensemble Model ◽  
Composition Method ◽  
Classifier Selection ◽  
Multi Stage ◽  
Proposed Model

With the rapid development of commercial credit mechanisms, credit funds have become fundamental in promoting the development of manufacturing corporations. However, large-scale, imbalanced credit application information poses a challenge to accurate bankruptcy predictions. A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition is proposed herein by combining the fuzzy clustering-based classifier selection method, the random subspace (RS)-based classifier composition method, and the genetic algorithm (GA)-based classifier compositional optimization method to achieve accuracy in predicting bankruptcy among corporates. To overcome the inherent inflexibility of traditional hard clustering methods, a new fuzzy clustering-based classifier selection method is proposed based on the mini-batch k-means algorithm to obtain the best performing base classifiers for generating classifier compositions. The RS-based classifier composition method was applied to enhance the robustness of candidate classifier compositions by randomly selecting several subspaces in the original feature space. The GA-based classifier compositional optimization method was applied to optimize the parameters of the promising classifier composition through the iterative mechanism of the GA. Finally, six datasets collected from the real world were tested with four evaluation indicators to assess the performance of the proposed model. The experimental results showed that the proposed model outperformed the benchmark models with higher predictive accuracy and efficiency.

scholarly journals Research of reliability and efficiency of technological processes of mechanical assembly production on the basis of the common semi-Markov model

2018 ◽  
Vol 224 ◽  
pp. 01138
Author(s):  
Yuri Rapatskiy ◽  
Mikhail Zamorenov ◽  
Vadim Kopp ◽  
Yuri Obzherin ◽  
Vladimir Gusev ◽  
...  
Keyword(s):  
Distribution Functions ◽  
Mechanical Assembly ◽  
Renewal Equations ◽  
Technological Processes ◽  
Threaded Connections ◽  
Proposed Model ◽  
The Common ◽  
Semi Markov Processes ◽  
Simulation Parameters ◽  
Assembly Production

In the article a common semi-Markov mathematical model is considered that allows one to investigate the productivity and reliability of various technological processes of mechanical assembly production. The proposed model allows to study, inter alia, technological processes of manufacturing parts with screw and assemblies of threaded connections. Mathematical apparatus of the research is the theory of semi-Markov processes with a common phase space, which operates with a common kind of random variables distribution functions. If the considering process in the system is a subsystem located on a higher level of hierarchy, the hierarchical model for compatibility with each other levels as output simulation parameters required distribution functions. In the proposed model, based on the decision of the Markov renewal equations depend not only on the torque characteristics, but also the distribution function of time per unit of output service according to different kinds of undervalued failures.

scholarly journals Implementation of dimensional management methodology and optimisation algorithms for pre-drilled hinge line interfaces of critical aero assemblies – A case study

2020 ◽  
pp. 095440542097810
Author(s):  
Konstantinos C Bacharoudis ◽  
David Bainbridge ◽  
Alison Turner ◽  
Atanas A Popov ◽  
Svetan M Ratchev
Keyword(s):  
Degrees Of Freedom ◽  
Engineering Problem ◽  
Hole Diameter ◽  
Design Stage ◽  
Assembly Process ◽  
Mechanical Assembly ◽  
Hinge Line ◽  
Management Procedure ◽  
Dimensional Management ◽  
Optimisation Algorithms

A dimensional management procedure is developed and implemented in this work to deal with the identification of the optimum hole diameter that needs to be pre-drilled in order to successfully join two subassemblies in a common hinge line interface when most of the degrees of freedom of each subassembly have already been constrained. Therefore, an appropriate measure is suggested that considers the assembly process and permits the application of optimisation algorithms for the identification of the optimum hole diameter. The complexity of the mechanical subassemblies requires advanced 3D tolerance analysis techniques to be implemented and the matrix method was adopted. The methodology was demonstrated for an industrial, aerospace engineering problem, that is, the assembly of the joined wing configuration of the RACER compound rotorcraft of AIRBUS Helicopter and the necessary tooling needed to build the assembly. The results indicated that hinge line interfaces can be pre-opened at a sufficiently large size and thus, accelerate the assembly process whilst the suggested methodology can be used as a decision-making tool at the design stage of this type of mechanical assembly.

Effect of Mechanical Alignment System on Assembly Accuracy

2000 ◽  
Author(s):  
Neville K. S. Lee ◽  
Grace H. Yu ◽  
Y. Zou ◽  
J. Y. Chen ◽  
Ajay Joneja
Keyword(s):  
Alignment Accuracy ◽  
Mechanical Alignment ◽  
Mechanical Assembly ◽  
Surface Waviness ◽  
Form Errors ◽  
Multi Stage ◽  
Assembly Accuracy ◽  
Alignment System ◽  
Simulation Based ◽  
Selection Of

Abstract Mechanical means of positioning are frequently used in mechanical assembly processes. However, very little attention has been paid to the selection of mechanical alignment systems (MAS) for assembly processes. Our analysis shows that if the MAS are not properly selected, the form errors as well surface waviness and roughness of the workpieces to be assembled can badly limit the level of accuracy achievable. A simulation-based methodology is described to study the alignment accuracy for multi-stage processes. Such cases are common, where fabrication operations are done on parts before they are assembled. The study shows that if the workpieces are aligned in the same orientation, using similar or identical MAS for the fabrication processes and assembly processes, then the effect of the form errors as well as surface waviness and roughness of the workpieces can be greatly suppressed.

A Novel Enhanced Russell Graph Efficiency Measure in Network DEA

2021 ◽  
pp. 1-31
Author(s):  
Robabeh Eslami ◽  
Mohammad Khoveyni
Keyword(s):  
Efficiency Score ◽  
Network System ◽  
Network Structures ◽  
Efficiency Measure ◽  
Network Dea ◽  
Economic Implications ◽  
Multi Stage ◽  
Proposed Model ◽  
Decision Making Units ◽  
High Computational Complexity

Hitherto, the presented models for measuring the efficiency score of multi-stage decision-making units (DMUs) either are nonlinear or require to specify the weights for combining their divisional efficiencies. The nonlinearity leads to high computational complexity for these models, especially when used for problems with enormous dimensions, and also assigning various weights to the divisional efficiencies causes to obtain different efficiency scores for the multi-stage network system. To tackle these problems, this study contributes to network DEA by introducing a novel enhanced Russell graph (ERG) efficiency measure for evaluating the general two-stage series network structures. Then, the proposed model is extended into the general multi-stage series network structures. This study also describes the managerial and economic implications of measuring the efficiency score of the multi-stage DMUs and provides two numerical and empirical examples for illustrating the use of our proposed model.

Introduce the Quantitative Identification Method of Rolling Bearing in the Application of Fault Detection

2015 ◽  
Vol 742 ◽  
pp. 147-149
Author(s):  
Li Huo
Keyword(s):  
Rolling Bearing ◽  
Rotating Machinery ◽  
Normal Operation ◽  
Support Vector ◽  
Decision Boundary ◽  
Proposed Model ◽  
Quantitative Identification ◽  
Diagnosis Model ◽  
Bearing Damage ◽  
Vector Description

Rolling bearing is an important part of rotating machinery. Its failure will directly affect the normal operation of the whole machinery. This study proposed an intelligent diagnosis model based on Fuzzy support vector description for the quantitative identification of bearing fault. The proposed model constructs the spherically shaped decision boundary by training the features of normal bearing data, and then calculates the fuzzy monitoring coefficient to identify the bearing damage.

Sign in / Sign up

Export Citation Format

Share Document