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Article
Publication date: 15 November 2011

Min Li and David A. Lowther

Robust design is very important for manufacturers to ensure the quality of the finished product. Therefore, a robustness measure is needed for the topological design of…

Abstract

Purpose

Robust design is very important for manufacturers to ensure the quality of the finished product. Therefore, a robustness measure is needed for the topological design of electromagnetic problems which may be sensitive to parameter variations. The purpose of this paper is to propose a robust objective function for topological design problems.

Design/methodology/approach

In this paper, a robust objective function for topology optimization is defined on an uncertainty set using the worst case analysis. The robustness of a topological design is defined as the worst response due to the variations of the location of the topology change. The approach is based on the definition of a topological gradient.

Findings

The robust topology optimization (RTO) was applied to eddy current crack reconstruction problems. The numerical applications showed that this method can provide more reliable results for the reconstruction in the presence of significant noise in the measured signal.

Research limitations/implications

The RTO may be applied to some more complicated design problems; however large computational costs may result.

Originality/value

This paper has defined a robustness metric for topology design and a robust design model is proposed for topology optimization problems.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 30 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 7 July 2023

Vinayambika S. Bhat, Thirunavukkarasu Indiran, Shanmuga Priya Selvanathan and Shreeranga Bhat

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates…

92

Abstract

Purpose

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Design/methodology/approach

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Findings

Research indicates that integral control parameters (Ki) affect outputs substantially more than proportional control parameters (Kp). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

Originality/value

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 4 October 2019

Seyed Jafar Sadjadi, Zahra Ziaei and Mir Saman Pishvaee

This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability…

Abstract

Purpose

This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability of vaccines, wastages in storage, limited capacity and different priorities for demands.

Design/methodology/approach

This study presents a mixed-integer linear programming (MILP) model and using a robust counterpart approach for coping with uncertainties of model.

Findings

The presented robust model in comparison with the deterministic model has a better performance and is more reliable for network design of vaccine supply chain.

Originality/value

This study considers uncertainty in the network design of vaccine supply chain for the first time in the vaccine context It presents an MILP model where strategic decisions for each echelon and tactical decisions among different echelons of supply chain are determined. Further, it models the difference between high- and low-priority demands for vaccine.

Article
Publication date: 18 January 2023

Zhao Dong, Ziqiang Sheng, Yadong Zhao and Pengpeng Zhi

Mechanical products usually require deterministic finite element analysis in the design phase to determine whether their structures meet the requirements. However, deterministic…

Abstract

Purpose

Mechanical products usually require deterministic finite element analysis in the design phase to determine whether their structures meet the requirements. However, deterministic design ignores the influence of uncertainties in the design and manufacturing process of mechanical products, leading to the problem of a lack of design safety or excessive redundancy in the design. In order to improve the accuracy and rationality of the design results, a robust design method for structural reliability based on an active-learning marine predator algorithm (MPA)–backpropagation (BP) neural network is proposed.

Design/methodology/approach

The MPA was used to obtain the optimal weights and thresholds of a BP neural network, and an active-learning function applicable to neural networks was proposed to efficiently improve the prediction performance of the BP neural network. On this basis, a robust optimization design method for mechanical product reliability based on the active-learning MPA-BP model was proposed. Random moving quadrilateral sampling was used to obtain the sample points required for training and testing of the neural network, and the reliability sensitivity corresponding to each sample point was calculated by subset simulated significant sampling (SSIS). The total mass of the mechanical product and the structural reliability sensitivity of the trained active-learning MPA-BP model output were taken as the optimization objectives, and a multi-objective reliability-robust optimization design model was constructed, which was solved by the second-generation non-dominated ranking genetic algorithm (NSGA-II). Then, the dominance function was used in the obtained Pareto solution set to make a dominance-seeking decision to obtain the final reliability-robust optimization design solution. The feasibility of the proposed method was verified by a reliability-robust optimization design example of the bogie frame.

Findings

The prediction error of the active-learning MPA-BP neural network was smaller than those of the particle swarm optimization (PSO)-BP, marine predator algorithm (MPA)-BP and genetic algorithm (GA)-BP neural networks under the same basic parameter settings of the algorithm, which indicated that the improvement strategy proposed in this paper improved the prediction accuracy of the BP neural network. To ensure the reliability of the bogie frame, the reliability sensitivity and total mass of the bogie frame were reduced, which not only realized the lightweight design of the bogie frame, but also improved the reliability and robustness of the bogie.

Originality/value

The MPA algorithm with a higher optimization efficiency was introduced to find the weights and thresholds of the BP neural network. A new active-learning function was proposed to improve the prediction accuracy of the MPA-BP neural network.

Details

International Journal of Structural Integrity, vol. 14 no. 2
Type: Research Article
ISSN: 1757-9864

Keywords

Article
Publication date: 5 October 2021

Yonghua Li, Hao Yin and Qing Xia

This study aims to research the influence of non-probabilistic design variables on interval robust optimization of electric multiple units (EMU) brake module, therefore obtain the…

Abstract

Purpose

This study aims to research the influence of non-probabilistic design variables on interval robust optimization of electric multiple units (EMU) brake module, therefore obtain the reasonable of design variables of the EMU brake module.

Design/methodology/approach

A robust optimization model of the EMU brake module based on interval analysis is established. This model also considers the dimension tolerance of design variables, and it uses symmetric tolerance to describe the uncertainty of design variables. The interval order relation and possibility degree of interval number are employed to deal with the uncertainty of objective function and constraint condition, respectively. On this basis, a multiobjective robust optimization model in view of interval analysis is established and applied to the robust optimization of the EMU brake module.

Findings

Compared with the traditional method and the method proposed in the reference, the maximum stress fluctuation of the EMU brake module structure is smaller after using the method proposed in this paper, which indicates that the robustness of the maximum stress of the structure has been improved. In addition, the weight and strength of the structure meet the design requirements. It shows that this method and model introduced in this research have certain feasibility.

Originality/value

This study is the first attempt to apply the robust optimization model based on interval analysis to the optimization of EMU structure and obtain the optimal solution set that meets the design requirements. Therefore, this study provides an idea for nonprobabilistic robust optimization of the EMU structure.

Details

Multidiscipline Modeling in Materials and Structures, vol. 17 no. 6
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 2 October 2017

Aalya Banu and Asan G.A. Muthalif

This paper aims to develop a robust controller to control vibration of a thin plate attached with two piezoelectric patches in the presence of uncertainties in the mass of the…

Abstract

Purpose

This paper aims to develop a robust controller to control vibration of a thin plate attached with two piezoelectric patches in the presence of uncertainties in the mass of the plate. The main goal of this study is to tackle dynamic perturbation that could lead to modelling error in flexible structures. The controller is designed to suppress first and second modal vibrations.

Design/methodology/approach

Out of various robust control strategies, μ-synthesis controller design algorithm has been used for active vibration control of a simply supported thin place excited and actuated using two piezoelectric patches. Parametric uncertainty in the system is taken into account so that the robust system will be achieved by maximizing the complex stability radius of the closed-loop system. Effectiveness of the designed controller is validated through robust stability and performance analysis.

Findings

Results obtained from numerical simulation indicate that implementation of the designed controller can effectively suppress the vibration of the system at the first and second modal frequencies by 98.5 and 88.4 per cent, respectively, despite the presence of structural uncertainties. The designed controller has also shown satisfactory results in terms of robustness and performance.

Originality/value

Although vibration control in designing any structural system has been an active topic for decades, Ordinary fixed controllers designed based on nominal parameters do not take into account the uncertainties present in and around the system and hence lose their effectiveness when subjected to uncertainties. This paper fulfills an identified need to design a robust control system that accommodates uncertainties.

Details

World Journal of Engineering, vol. 14 no. 5
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 29 March 2021

Nigar Ahmed, Abid Raza and Rameez Khan

The aim of this paper is to design a nonlinear disturbance observer-based control (DOBC) method obtained by patching a control method developed using a robust adaptive technique…

Abstract

Purpose

The aim of this paper is to design a nonlinear disturbance observer-based control (DOBC) method obtained by patching a control method developed using a robust adaptive technique and a DO.

Design/methodology/approach

For designing a DOBC, initially a class of nonlinear system is considered with an external disturbance. First, a DO is designed to estimate the external disturbances. This estimate is combined with the controller to reject the disturbances and obtain the desired control objective. For designing a controller, the robust sliding mode control theory is used. Furthermore, instead of using a constant switching gain, an adaptive gain tuning criterion is designed using Lyapunov candidate function. To investigate the stability and effectiveness of the developed DOBC, stability analysis and simulation study are presented.

Findings

The major findings of this paper include the criteria of designing the robust adaptive control parameters and investigating the disturbance rejection when robust adaptive control based DOBC is developed.

Practical implications

In practice, the flight of quadrotor is affected by different kind of external disturbances, thus leading to the change in dynamics. Hence, it is necessary to design DOBCs based on robust adaptive controllers such that the quadrotor model adapts to the change in dynamics, as well as nullify the effect of disturbances.

Originality/value

Designing DOBCs based on robust control method is a common practice; however, the robust adaptive control method is rarely developed. This paper contributes in the domain of DOBC based on robust adaptive control methods such that the behavior of controller varies with the change in dynamics occurring due to external disturbances.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 4
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 16 November 2021

Saeid Jafarzadeh Ghoushchi, Iman Hushyar and Kamyar Sabri-Laghaie

A circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should…

435

Abstract

Purpose

A circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.

Design/methodology/approach

In this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.

Findings

The proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.

Practical implications

This study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.

Originality/value

The main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 25 September 2009

Humberto Hijar‐Rivera and Victor Garcia‐Castellanos

The purpose of this paper is to present computer‐generated combined arrays as efficient alternatives to Taguchi's crossed arrays to solve robust parameter problems.

Abstract

Purpose

The purpose of this paper is to present computer‐generated combined arrays as efficient alternatives to Taguchi's crossed arrays to solve robust parameter problems.

Design/methodology/approach

The alternative combined array designs were developed for the cases including six to twelve variables where CMR designs are not smaller than Taguchi's designs. The efficiency to estimate the effects of interest was calculated and compared to the efficiency of the corresponding CMR designs.

Findings

For all the cases investigated at least one computer generated combined array design was found with the same size as the CMR design and with higher efficiency.

Practical implications

Robust parameter design identifies appropriate levels of controllable variables in a process for the manufacturing of a product. The designed experiments involve the controllable variables along with the uncontrollable or noise variables to design a product or process that will be robust to changes in these noise variables. Response surface methodology estimates the actual relationship between the response and the input variables with an empirical model based on the designed experiment. Once the empirical model is fitted, the surface described by the model can be used to describe the behavior of the response over the experimental region. The higher efficiency of the computer generated combined array designs proposed in this research produces lower variances for the parameter estimates and lower variance of prediction for the model. As a result, the response will be described in a more realistic form.

Originality/value

The paper shows that using a computer‐generated design to solve a robust parameter problem will result in a better approximation to the true response of the process. Consequently, optimizing the fitted model will produce settings for the parameters closer to the real optimal settings.

Details

Journal of Quality in Maintenance Engineering, vol. 15 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 17 April 2009

Jami Kovach, Byung Rae Cho and Jiju Antony

Robust design is a well‐known quality improvement method that focuses on building quality into the design of products and services. Yet, most well established robust design models…

Abstract

Purpose

Robust design is a well‐known quality improvement method that focuses on building quality into the design of products and services. Yet, most well established robust design models only consider a single performance measure and their prioritization schemes do not always address the inherent goal of robust design. This paper aims to propose a new robust design method for multiple quality characteristics where the goal is to first reduce the variability of the system under investigation and then attempt to locate the mean at the desired target value.

Design/methodology/approach

The paper investigates the use of a response surface approach and a sequential optimization strategy to create a flexible and structured method for modeling multiresponse problems in the context of robust design. Nonlinear programming is used as an optimization tool.

Findings

The proposed methodology is demonstrated through a numerical example. The results obtained from this example are compared to that of the traditional robust design method. For comparison purposes, the traditional robust design optimization models are reformulated within the nonlinear programming framework developed here. The proposed methodology provides enhanced optimal robust design solutions consistently.

Originality/value

This paper is perhaps the first study on the prioritized response robust design with the consideration of multiple quality characteristics. The findings and key observations of this paper will be of significant value to the quality and reliability engineering/management community.

Details

International Journal of Quality & Reliability Management, vol. 26 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

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