Robust Design of Aero-Engine Assembly Using Taguchi Method Based on Jacobian-Torsor Model

2019 ◽  
Author(s):  
Siyi Ding ◽  
Xiaohu Zheng ◽  
Jinsong Bao ◽  
Jie Zhang
Keyword(s):  
Robust Design ◽  
Optimization Method ◽  
Design Stage ◽  
Original Design ◽  
Traditional Methods ◽  
Geometrical Errors ◽  
Statistical Variation ◽  
Variation Propagation ◽  
Aero Engine ◽  
The Rich

Abstract Aero-engine assembly is the core tache in the whole process of aero-engine manufacturing. Assembly variations are unavoidable due to parts’ geometrical errors. Statistical variation analysis is an effective method for robust design that can quantitatively predict product quality in the original design stage. However, traditional methods focus on the modeling of plane dimension chain and extremum analysis, which is difficult to comprehensively consider the rich geometrical errors and their relationship to each other; meanwhile, the precision prediction is too conservative to reduce the parts’ rework frequency and adjusting difficulty; in addition, traditional methods overemphasize the promotion of parts’ machining precision, and ignore the means of overall stack optimization. To overcome these problems, firstly, Jacobian-Torsor (J-T) model is used to build the variation propagation, which is well suited to a complex assembly that contains large numbers of joints and geometric tolerances; secondly, combining with Monte Carlo simulation and J-T statistical contribution solution, the percentage contribution of each part could be solved; Finally, Taguchi multi-objective optimization method is adopted for robust design of the whole system. A case study on an entire aero-engine assembly is presented to illustrate the proposed method and the results show that this new method can effectively evaluate the assembly performance and determine the optimal assembly plan, which has strong practical guiding significance.

An improved Jacobian-Torsor model for statistical variation solution in aero-engine rotors assembly

2020 ◽  
pp. 095440542095876
Author(s):  
Siyi Ding ◽  
Xiaohu Zheng ◽  
Jinsong Bao ◽  
Jie Zhang
Keyword(s):  
Three Dimensional ◽  
Statistical Variation ◽  
Variation Propagation ◽  
Aero Engine ◽  
Core Components ◽  
Key Issues ◽  
Assembly Technology ◽  
Parts Manufacturing ◽  
Rotor Assembly ◽  
Engine Rotors

Rotor assembly is one of the core components of aero-engine, which basically consists of multistage revolving components. With the influence of parts’ manufacturing errors and practical assembly technology, assembly variations are unavoidable which will cause insecurity and unreliable of the whole engine. Statistical variation solution is a feasible means to analyze assembly precision. When using the three-dimensional variation analysis in rotor assembly, two key issues cannot be well solved, which involve the variation expression (the over-positioning problem of multiple datums) and the variation propagation (revolving characteristic of the rotors). To overcome the deficiency, extended Jacobian matrix and updated torsor equation were derived and unified, which eventually resulted in the improved Jacobian-Torsor model. This model can both provide rotation regulating mechanism by introducing the revolution joint, and characterize the interaction between essential mating features. Multistage rotational optimization of four-stage aero-engine rotors assembly has been performed to demonstrate this solution in statistical way. Results showed that the proposed model was applicable and conducive to precision prediction and analysis in design preliminary stage.

Application of Shape Optimization Method on Steel Wheel Rim

2014 ◽  
Vol 564 ◽  
pp. 13-18
Author(s):  
Mohd Nizam Ahmad ◽  
Awanis Ihsanul Kamil ◽  
Wan Mansor Wan Muhamad
Keyword(s):  
Shape Optimization ◽  
Weight Reduction ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Design Stage ◽  
Original Design ◽  
Great Opportunity ◽  
Steel Wheel ◽  
Automotive Components ◽  
Wheel Rim

Nowadays, weight reduction is great opportunity for automotive components design due to meet the structural strength without reducing the components safety. A classical try-and-error approach to design the automotive components in industries is inadequate which mean new methods are needed to enhance the design process. An improvement of the component can be achieved by adopting suitable optimization techniques at the early design stage. In this paper, the problem of automotive component design; steel wheel rim design in a view of weight reduction was tackled by means of shape optimization method. Design methodology was proposed to the original design of selected wheel rim and was continued optimized them by various reduction targets. The optimized design together with the datum has been analyzed and the results were compared and discussed. Shape optimization with 15% of reduction target at steel wheel rim was the best optimal design and it was met the design criteria and safety factor. By applying shape optimization, weight of steel wheel also has been reduced by using proper reduction target. The methodology has been proven to be successful in finding innovative and efficient layouts for automotive components design.

scholarly journals SIMULTANEOUS DEFINITION OF KEY CHARACTERISTICS IN ORDER TO FACILITATE ROBUST DESIGN IN EARLY PRODUCT DEVELOPMENT STAGES

2021 ◽  
Vol 1 ◽  
pp. 2691-2700
Author(s):  
Stefan Goetz ◽  
Dennis Horber ◽  
Benjamin Schleich ◽  
Sandro Wartzack
Keyword(s):  
Product Development ◽  
Robust Design ◽  
Language Processing ◽  
Design Stage ◽  
Concept Design ◽  
Clear Definition ◽  
Implicit Information ◽  
Key Characteristics ◽  
Associated Functions ◽  
Definition Of

AbstractThe success of complex product development projects strongly depends on the clear definition of target factors that allow a reliable statement about the fulfilment of the product requirements. In the context of tolerancing and robust design, Key Characteristics (KCs) have been established for this purpose and form the basis for all downstream activities. In order to integrate the activities related to the KC definition into product development as early as possible, the often vaguely formulated requirements must be translated into quantifiable KCs. However, this is primarily a manual process, so the results strongly depend on the experience of the design engineer.In order to overcome this problem, a novel computer-aided approach is presented, which automatically derives associated functions and KCs already during the definition of product requirements. The approach uses natural language processing and formalized design knowledge to extract and provide implicit information from the requirements. This leads to a clear definition of the requirements and KCs and thus creates a founded basis for robustness evaluation at the beginning of the concept design stage. The approach is exemplarily applied to a window lifter.

UNCERTAINTY BASED ROBUST OPTIMIZATION IN AERODYNAMICS

2009 ◽  
Vol 23 (03) ◽  
pp. 477-480 ◽  
Author(s):  
ZHILI TANG
Keyword(s):  
Nash Equilibrium ◽  
Robust Design ◽  
Single Point ◽  
Optimization Method ◽  
Equilibrium Solutions ◽  
Design Problems ◽  
Nash Equilibrium Solutions ◽  
Definition Of ◽  
Taguchi Robust Design ◽  
Statistical Definition

The Taguchi robust design concept is combined with the multi-objective deterministic optimization method to overcome single point design problems in Aerodynamics. Starting from a statistical definition of stability, the method finds, Nash equilibrium solutions for performance and its stability simultaneously.

A time-varying reliability-based robust design method considering overall efficiency of axial piston pump

2021 ◽  
pp. 1748006X2110661
Author(s):  
Zunling Du ◽  
Yimin Zhang
Keyword(s):  
Energy Conversion ◽  
Robust Design ◽  
Design Method ◽  
Design Stage ◽  
Structure Parameters ◽  
Time Varying ◽  
Design Variables ◽  
Reliability Method ◽  
Overall Efficiency ◽  
Axial Piston

Axial piston pumps (APPs) are the core energy conversion components in a hydraulic transmission system. Energy conversion efficiency is critically important for the performance and energy-saving of the pumps. In this paper, a time-varying reliability design method for the overall efficiency of APPs was established. The theoretical and practical instantaneous torque and flow rate of the whole APP were derived through comprehensive analysis of a single piston-slipper group. Moreover, as a case study, the developed model for the instantaneous overall efficiency was verified with a PPV103-10 pump from HYDAC. The time-variation of reliability for the pump was revealed by a fourth-order moment technique considering the randomness of working conditions and structure parameters, and the proposed reliability method was validated by Monte Carlo simulation. The effects of the mean values and variance sensitivity of random variables on the overall efficiency reliability were analyzed. Furthermore, the optimized time point and design variables were selected. The optimal structure parameters were obtained to meet the reliability requirement and the sensitivity of design variables was significantly reduced through the reliability-based robust design. The proposed method provides a theoretical basis for designers to improve the overall efficiency of APPs in the design stage.

Improvement of Variation Propagation Control in Mechanical Assembly Using Adjustment Assembly Technique

2017 ◽  
Vol 870 ◽  
pp. 459-464 ◽  
Author(s):  
Chuan Zhi Sun ◽  
Lei Wang ◽  
Jiu Bin Tan ◽  
Bo Zhao ◽  
Guo Liang Jin ◽  
...  
Keyword(s):  
Assembly Model ◽  
Mechanical Assembly ◽  
Assembly Quality ◽  
Cumulative Error ◽  
Assembly Method ◽  
Variation Propagation ◽  
Rotationally Symmetric ◽  
Aero Engine ◽  
Assembly Technique ◽  
Engine Components

This paper aims to provide an assembly method to improve mechanical assembly quality. In order to improve the variation propagation control in rotationally symmetric cylindrical components assembly, the eccentric and tilt errors of a single rotor stage were taken into account using a connective assembly model and the eccentric deviation in a mechanical assembly was minimized by properly selecting component orientations. Compared to the minimum cumulative error, the maximum cumulative error was reduced by 71 percent, and the average cumulative error was reduced by 57 percent in the assembly of three components. This article provides an assembly method through variation propagation control in rotationally symmetric cylindrical components assembly. The method could be extended to rotationally symmetric cylindrical components assembly, for example in the assembly of aero-engine components.

scholarly journals FEM Based Preliminary Design Optimization in Case of Large Power Transformers

2019 ◽  
Author(s):  
Tamás Orosz ◽  
David Pánek ◽  
Pavel Karban
Keyword(s):  
Design Optimization ◽  
Design Process ◽  
Optimization Problems ◽  
Optimization Method ◽  
Power Transformers ◽  
Design Stage ◽  
Preliminary Design ◽  
Large Power ◽  
Custom Made ◽  
Transformer Design

Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

Production Yield Estimation by the Metamodel Method With a Boundary-Focused Experiment Design

1997 ◽  
Author(s):  
Chinghsin Tu ◽  
Russell R. Barton
Keyword(s):  
Monte Carlo ◽  
Robust Design ◽  
Simulation Models ◽  
Experiment Design ◽  
Production Yield ◽  
Design Stage ◽  
Yield Estimation ◽  
Simulation Code ◽  
New Approach ◽  
A Priority

Abstract The need for yield estimation strategies in the design stage is a priority recognized by industry. Yield estimates can be employed to assess the manufacturability of a design, and allow for modification to produce a robust design. Therefore, low yield of products can be avoided and costs for manufacturing can be reduced. This paper presents an accurate and time-efficient yield estimation approach for use with simulation models. We use a metamodel-based method, which is time-efficient compared to crude Monte Carlo yield estimation using the original simulation code. The approach employs a boundary-focused experiment design, which overcomes the inaccuracy of yield estimates that can occur when using a metamodel method. The results of two examples demonstrate the effectiveness of this new approach.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

An Analysis Model to Predict Rotation Accuracy of High-Precision Spindles Considering Part Errors and Deformation

2017 ◽  
Author(s):  
Yanhui Sun ◽  
Jun Hong ◽  
Junkang Guo ◽  
Yanfei Zhang ◽  
Shaoke Wan ◽  
...  
Keyword(s):  
High Precision ◽  
Design Stage ◽  
Small Displacement ◽  
Analysis Model ◽  
Transformation Matrices ◽  
Beam Elements ◽  
Fea Model ◽  
Small Displacement Torsor ◽  
Variation Propagation ◽  
Error Accumulation

High-precision spindles have significant influence on the machining precision and finishing quality largely due to their motion errors. However, the analysis of rotation accuracy is quite not easy in design stage because of the neglecting of geometric errors and deformations of parts in the traditional dimension chains. Hence, a theoretical analysis model is built in present study to do the prediction. The 3D error accumulation path is recognized by Datum Flow Chain (DFC) and the key tolerances are modeled by Small Displacement Torsor (SDT). Thereafter, the variation propagation is conducted by Homogeneous Transformation Matrices (HTM) and the geometric misalignment in the spindle is calculated. Then, an FEA model is built with Timoshenko beam elements and the deformation is calculated after the geometric misalignment is applied to the model. As spindle rotates, the trajectory of the spindle nose is obtained. Finally, the Monte Carlo (MC) method is used to get the distribution and the range of motion errors. To verify the feasibility and reliability of the analysis model, the radial and axial motion errors of a double supported high-precision spindle are analyzed.

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