Robust Tolerance Design Research Articles

Effect of adhesive de-bond and crack in adherent plate on single lap joint with bi-adhesive

PurposeThis paper aims to study the benefits of use of bi-adhesive (combination of two different adhesives) over conventional single adhesive in bonded lap joints. Characterise damage severity due to cohesive and adherent failure as feedback for operating load levels that assist in developing damage tolerance design of the adhesively bonded joints.Design/methodology/approachSingle lap joint where the adherent plate is made up of aluminium alloy joined together with bi-adhesives is analysed. The nature of adhesives ranges from brittle, elastic-plastic, moderately ductile to largely ductile. Numerical analysis is performed considering the material and geometric non-linear behaviour of the joint. The optimum bond ratio of bi-adhesives and the effect of the location of adhesive on the stress distribution are studied. The cohesive zone modelling (CZM) is adopted to account for the cohesive failure of the joint. The adherent plate failure is also addressed by modelling and studying the behaviour of the crack at different locations in the plate using modified virtual crack closure integral (MVCCI).FindingsThe results obtained from the stress analysis show some important characteristic behaviour of the bi-adhesive joint. Although bi-adhesive is expected to result in improved joint strength, the purpose gets defeated if a brittle adhesive is used at the corners and ductile adhesive at the middle. The joint strength based on CZM, evaluated for a single adhesive, is in good comparison with the experimental results from the literature. Also, the location of the crack in the adherent plate plays a significant role in the failure of the joint.Originality/valueEstimating joint strength for the bi-adhesive model using CZM and evaluating damage severity in the presence of de-bond and crack in the bi-adhesive lap joint model assists in developing robust damage tolerance design models of such joints.

Integrated parameter and tolerance design for multiple response optimization

Robust parameter design and tolerance design are effective approaches for continuous product quality improvement. However, the traditional two-stage design approach of parameter design followed by tolerance design is time-consuming. The tolerance levels determined in the tolerance design stage typically affect quality loss; therefore, the parameter levels obtained in the parameter design may be suboptimal. In this paper, we propose an integrated parameter and tolerance design model, and then a criteria importance through intercriteria correlation-based grey relational analysis technique is adopted to obtain the optimal parameter and tolerance levels. A case study is conducted to validate the proposed method. Comparison results show that the parameter levels and tolerance levels of controllable factors obtained using the proposed method are more reliable and enable a better tradeoff among quality loss, tolerance cost and predicted loss.

Robust tolerance design for rotor dynamics based on possibilistic concepts

Robust tolerance design for rotor dynamics based on possibilistic concepts

A Chernov bound for robust tolerance design and application

Within an industrial manufacturing process, tolerancing is a key player. The dimensions uncertainties management starts during the design phase, with an assessment on variability of parts not yet produced. For one assembly step, knowledge can be gained from the tolerance range required for the parts involved. In order to assess output uncertainty of this assembly in a reliable way, this paper presents an approach based on the deviation of the sum of uniform distributions. As traditional approaches based on Hoeffding inequalities do not give accurate results when the deviation considered is small, an improved upper bound is proposed. Then, the impact of the stack chain geometry on the bound definition is discussed. Finally, an application of the proposed approach in tolerance design of an aircraft sub-assembly is detailed. The main interest of the technique compared to existing methodologies is the management of the confidence level and the emphasis of the explicit role of the balance within the stack chain.

Sampling-based Tolerance-Cost Optimization of Systems with Interrelated Key Characteristics

Abstract Robustness is a key factor contributing to a high functionality of technical systems under uncertainty. In this context, existing methodologies, such as Axiomatic Design and Quality Function Deployment, can help to identify coupled functional requirements which significantly affect the robustness of a system. However, it is often not possible to decouple all in the final product design. As a consequence, multiple interrelated tolerance chains have to be considered in the subsequent tolerance design leading to multi-constrained or multi-objective optimization problems. Despite their significant influence on the optimization process and its results, interrelated tolerance chains have not been studied in detail yet, especially in the context of sampling-based tolerance-cost optimization. Moreover, a holistic framework for the tolerance-cost optimization of systems with multiple key characteristics is missing so far. In order to close that gap, this paper presents a framework to consider multiple key characteristics in both least-cost and best-quality tolerance-cost optimization using sampling techniques for tolerance analysis. Therefore, interrelated tolerance chains and their effects on the optimization process in terms of the definition and handling of multiple constraints and objectives are discussed in detail. The proposed research aims to bring all important aspects together in one common framework. Thus, it is supposed to help researchers and practitioners to properly define and solve the tolerance optimization problem. In order to show its benefits and applicability, it is applied to an illustrative case study. The novelty of this paper is to present a comprehensive method to support the tolerance engineer in creating a robust and optimal tolerance design of products with multiple interrelated key characteristics.

Study on the Robust Tolerance Design with Multiple Resource Suppliers on Cloud Manufacturing Platform

The robust tolerance design in the scenario with multiple resource suppliers is faced with greater uncertainty in the new manufacturing era. This paper studies the robust tolerance design on cloud manufacturing platform, in which a two-level game is put forward to reveal the relationship and behavior between the products and resource suppliers. According to the scenario with multiple resource suppliers, the multivariate process capability index has been introduced to solve the problem of robust tolerance design faced up with cloud manufacturing environment. A case study is used to illustrate the proposed model.

A new robust tolerance design method for electromechanical device based on variable contribution rate coefficients

ABSTRACTThe consistency of batch electromechanical device is influenced seriously by the uncertainty in manufacturing process. Robust tolerance design (RTD) can reduce the impact of uncertainty on the batch products consistency. However, in the traditional RTD method, the contribution rate coefficients of design parameters remain constant during the tolerance optimisation process, which badly affects the accuracy of optimisation. In the paper, a new RTD method of automatic optimisation is proposed based on the variation of contribution rate coefficients. During the tolerance optimisation process, the contribution rate coefficients will be recalculated for each iteration, the step size of tolerance decrease for each parameter can be automatically adjusted according to the difference between the current consistency index and the optimisation target. Compared with the traditional Taguchi RTD method, the optimisation accuracy can be obviously improved by the new method proposed in the paper.

A Novel Approach to Simultaneous Robust Design of Product Parameters and Tolerances Using Quality Loss and Multivariate ANOVA Concepts

AbstractDesign and development of high quality products are of utmost importance to any production plant. Product design consists of parameter design and tolerance design, which affect the product performances and the manufacturing costs, respectively. Most products involve more than one quality feature. Design and development of such products raise multi‐response surface problems in which it is necessary to determine the optimal values of parameters and the tolerances for all responses simultaneously. In this research, an approach for simultaneous robust parameter and tolerance design is proposed to deal with multi‐response problems. The proposed method employs quality loss concept and one‐way multivariate analysis of variance. Two simulation studies are performed to validate the applicability of the proposed method. Research findings show that the proposed method performs better in quality improvement as well as in cost reduction than the existing methods. The variances of the responses are also lower than those of the other methods, that is, the proposed method results in a more robust approach to product design. Copyright © 2016 John Wiley & Sons, Ltd.

A robust-tolerance design model for destructive quality characteristics: a case study in cement industry

Although remarkable considerations has been devoted to tolerance design (TD) and robust design (RD) by researchers recently and many methodologies have been proposed for the TD and RD optimisation, less attention has been focused on the integration of tolerance design and robust design. In this research, we aim to develop a sequential robust-tolerance design method through best factor settings when several related quality characteristics should be evaluated using destructive tests. Due to the nature of the tests, we could not measure key product quality characteristics directly and this issue added a constraint to the optimisation problem. The developed model under the defined scenario above was evaluated in the cement industry. Results show that the proposed model simulates the operational conditions satisfactorily.

Quality Analysis and Consistency Design of Electromagnetic Device Based on Approximation Model

The consistency problem caused by the uncertainties in manufacturing process is a significant factor influencing the quality of electromagnetic device (EMD). The foundation of quality analysis and consistency optimization is the substantial calculation for the input-output characteristics of the product. As for EMD, the interaction of electricity, magnetism (permanent magnetism), and dynamics make the calculation quite complicated. At present, finite-element method (FEM) is a common method for calculating the output characteristics of EMD. However, FEM takes too much time for calculating, it is difficult to be applied for the quality analysis and consistency design of EMD that requires substantial calculation. In this paper, a new approach for the quality analysis and consistency design of EMD based on the approximate model has been proposed. First, the approximate model for calculating the EMD output characteristics is established on the basis of FEM simulation results. Second, using the approximate model, the quality analysis of batch products is conducted with Monte Carlo method. Finally, the optimal design for consistency is carried out with robust tolerance design method. The effectiveness of the method proposed in this paper is verified by the case study of a certain type of electromagnetic relay with permanent magnet.

Optimal Tolerance Design and Optimization for a Pharmaceutical Quality Characteristic

A number of pharmaceutical quality characteristics are destructive or too costly to inspect. However, most quality improvement tools developed in the pharmaceutical research community typically assume that quality characteristics are nondestructive. This paper proposes a new design system for quality improvement by incorporating the concept of surrogate variables with the concepts of robust design (RD) and tolerance design (TD). The proposed robust-tolerance design paradigm determines the optimal factor setting and specification limits simultaneously, thereby improving quality of pharmaceutical products. In addition, the proposed methodology can provide the optimal tolerance as a mathematical closed-form solution. Finally, a numerical example and its associated sensitivity analysis for a pharmaceutical case are conducted for verification purposes. Based on the numerical example results, the proposed approach could provide robust factor settings with significant tradeoffs between quality and cost.

Simultaneous Optimization of Robust Parameter and Tolerance Design Based on Generalized Linear Models

Robust parameter design (RPD) and tolerance design (TD) are two important stages in design process for quality improvement. Simultaneous optimization of RPD and TD is well established on the basis of linear models with constant variance assumption. However, little attention has been paid to RPD and TD with non‐constant variance of residuals or non‐normal responses. In order to obtain further quality improvement and cost reduction, a hybrid approach for simultaneous optimization of RPD and TD with non‐constant variance or non‐normal responses is proposed from generalized linear models (GLMs). First, the mathematical relationship among the process mean, process variance and control factors, noise factors and tolerances is derived from a dual‐response approach based on GLMs, and the quality loss function integrating with tolerance is developed. Second, the total cost model for RPD‐TD concurrent optimization based on GLMs is proposed to determine the best control factors settings and the optimal tolerance values synchronously, which is solved by genetic algorithm in detail. Finally, the proposed approach is applied into an example of electronic circuit design with non‐constant variance, and the results show that the proposed approach performs better on quality improvement and cost reduction. Copyright © 2012 John Wiley & Sons, Ltd.

A new joint process optimisation methodology for pharmaceutical destructive characteristics: a statistical approach

In current pharmaceutical research and development, not many robust design (RD) and tolerance design (TD) approaches have been applied, although many researchers and practitioners have realised the importance of process design concepts. Pharmaceutical characteristics often involve different types of destructive measurements, such as hardness, friability, and disintegration in drug development and manufacturing processes. The primary objective of this paper is to develop an integrated robust-tolerance design methodology for handling destructive quality characteristics on pharmaceutical study. A statistical TD optimisation method, which incorporates consumer and producer risk, is proposed that uses a surrogate variable that is strongly correlated with the destructive quality characteristic. Finally, a pharmaceutical case study is performed for verification purposes. In the case study, a comparison between two RD optimisation models (i.e., dual-response and mean squares error models) is also conducted.

Feasible Robust Tolerance Design for Fixture System in Two-dimensional Multi-station Assembly Processes Based on Variation Propagation

Based on variation propagation,a method of feasible robust design tolerance is developed for fixture system in two-dimensional multi-station assembly processes.The relationship of dimensional variation propagation for two-dimensional multi-station assembly processes is analyzed,and the state space model of variations stream is built,in which the fixture locating variations are caused by the tolerances of pin and part hole/slot.By means of number-theoretical net method,the tolerances sample of pin and part hole/slot is presented which is used to substitute into the variations model of fixture locating to obtain the sample space of fixture locating variations.Based on state space model,taking fixture locating variations for input vectors,an evaluation method of assembly yield is proposed for two-dimensional multi-station assembly processes.Furthermore,Taguchi orthogonal experiment method is adopted to analyze the main factors that influence the assembly yield and the design of regression-orthogonal combination is applied to fit the response surface model of assembly yield.With the objective to satisfy the lowest manufacturing cost of pin and part hole/slot,taking the assembly yield for constraint,the model of feasible robust tolerance design for fixture system in two-dimensional multi-station assembly processes is established.Automotive body floor assembly process with three-station is given as an example to build the model which is calculated and analyzed.The results show that the robustness of tolerance design is improved significantly with robust constraint while assembly cost increases slightly.It provides a new way of feasible robust tolerance design for fixture system in two-dimensional multi-station assembly processes.

Development of a sequential robust–tolerance design model for a destructive quality characteristic

Robust design (RD) and tolerance design (TD) have received much attention from researchers and practitioners for more than two decades, and a number of methodologies for modeling and optimizing the RD and TD processes have been studied. However, there is ample room for improvement. Because most existing research considers RD and TD as separate research fields, the primary objective of this paper is to develop a sequential robust–tolerance design method to jointly determine the best factor settings and the closed-form solutions for the optimal specification limits. We then apply the proposed method to a destructive quality characteristic. Finally, a case study and sensitivity analyses are performed for verification purposes, and further studies are discussed.

Robust Tolerance Design of Automotive Body Product with Game Theory

Robust tolerance design is an effective way to reduce the production risk. Traditionally, manufacturing cost and product quality are considered to be the optimization objectives. Designers often adopt the single-objective optimization or establish a comprehensive evaluating function combining several optimization objectives with different weights. It may not be desirable as it is difficult to identify the weights and balance the conflicting demands reasonably. This paper presents a kind of game approach to solve the robust tolerance design problem for automotive body products. Instead of designing specific objective functions, some measuring data in the manufacturing process are collected, and a robust game model considering the cost and the quality demand is established by transforming the part and the product information into relevant game components. The Nash bargaining method (NBM) of game theory is adopted to attain a balanced solution. It calls on two players in a game to start negotiation from a reference vector and achieve a trade-off vector as far as possible from the worse situation. Finally, an example of vehicle fender demonstrates the application and the performance of this method.

Robust tolerance design for function generation mechanisms with joint clearances

This paper presents a method for robust tolerance design of function generation mechanisms with joint clearances. Based on previous studies made by other researchers, we develop a model to quantify the effects of uncertain factors on the accuracy of function generation mechanisms. An improved Taguchi method is applied to determine the optimal tolerances for individual components so that the total assembly cost is minimized while satisfying the accuracy requirements of the mechanism. Unlike the traditional Taguchi method which uses orthogonal arrays to arrange experiments, the uniform design table is selected to represent noise factors in this paper. Sensitivity maps are plotted to provide an insight to the effects of parameter variances on the performance of function generation mechanisms. An illustrative example is given to demonstrate the practicality and efficiency of the proposed method.

Integrated robust parameter design and tolerance design

Robust design has been gaining plenty of attention in both academia and industry over the past two and half decades. However, there is still some room for improvement. In this dissertation, several drawbacks of the existing robust design methods were identified and analysed. An integrated robust design framework was proposed to help achieve robustness against both external and internal noises. A Steepest Descent Driven Parameter Design method was developed to enhance robust design. Also developed was an improved loss function for robust tolerance design. The proposed methodology was applied using computer simulation experiments to optimise the design of a state-of-the-art injector in a high pressure common rail injection system in a diesel engine. It was demonstrated that the injector performance was significantly improved with the proposed method.

Development of a sequential optimization procedure for robust design and tolerance design within a bi-objective paradigm

Many practitioners and researchers have implemented robust design and tolerance design as quality improvement and process optimization tools for more than two decades. Robust design is an enhanced process/product design methodology for determining the best settings of control factors while minimizing process bias and variability. Tolerance design is aimed at determining the best tolerance limits for minimizing the total cost incurred by both the customer and manufacturer by balancing quality loss due to variations in product performance and the cost of controlling these variations. Although robust design and tolerance design have received much attention from researchers and practitioners, there is ample room for improvement. First, most researchers consider robust design and tolerance design as separate research fields. Second, most research work is based on a single quality characteristic. The primary goal of this paper is to integrate a sequential robust design–tolerance design optimization procedure within a bi-objective paradigm, which, the authors believe, is the first attempt in the robust design and tolerance design literature. Models are proposed and numerical examples along with sensitivity analysis are performed for verification purposes.

Manufacturing environment-oriented robust tolerance optimization method

Tolerance design has a great impact on the cost and quality of a product. Previous research focused on process tolerances or robust tolerance design with little consideration on real manufacturing context. This paper presents a nonlinear method for robust tolerance design based on the real manufacturing context in three stages. The objective function to be minimized is the total manufacturing cost. The constraint equations for the optimization model are also deduced, which select suitable manufacturing processes based on the manufacturing environment. Simulation annealing (SA) is used for the nonlinear optimization. The approach is finally illustrated by a practical example. The results of the comparison with different models indicate that the proposed approach is more effective with the manufacturing resource. The robust and reliable tolerance can be obtained.