A robust interactive approach to optimize correlated multiple responses

Salmasnia, Ali; Bashiri, Mahdi; Salehi, Mojtaba

doi:10.1007/s00170-012-4619-9

Cited by 16 publications

(8 citation statements)

References 50 publications

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“…Some of the novel approaches simultaneously incorporate dispersion and location effects and/or a correlation between the responses in a unified framework [33,34]. In some papers have suggested the methodologies that combine the quality (goodness) of predictions and/or robustness (non-sensitivity to environmental noise factors) [30,[33][34][35]. In such cases, the traditional overall desirability is redefined through a suitable trade-off between the aforementioned requirements.…”

Section: Overall Desirabilitymentioning

confidence: 99%

A novel desirability function for multi-response optimization and its application in chemical engineering

Marinković

2020

CI&CEQ

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In many aspects of modern engineering (processes, products, and systems) there is a need to optimize multiple responses simultaneously, rather than optimizing one response at a time. The optimization of each individual response may generate as many different results as the responses are considered in the study. Then, it may be impossible to decide whether one solution is better than the other. On the other hand, some improvement in one response can significantly degrade at least one or more responses. There are a number of multiresponse optimization techniques available. Among the these multi-response optimization techniques, the desirability-based approaches take a prominent place because they are less sophisticated, easy to understand and implement, and more flexible with respect to other existing approaches, due to which they are very popular among researchers and practitioners. There are many different formulations of the desirability function. Unfortunately, most desirability functions known in the literature are piecewise, non-differentiable functions. In this paper, a novel desirability function is proposed, which is continuous and differentiable in its domain. This function is more suitable for applying some of the efficient gradient-based optimization methods. The efficiency and accuracy of the proposed method were analyzed on two chemical processes that were studied extensively in the literature.

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Section: Overall Desirabilitymentioning

confidence: 99%

A novel desirability function for multi-response optimization and its application in chemical engineering

Marinković

2020

CI&CEQ

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“…To earn the buyer and manufacturer satisfaction simultaneously, a desirability function approach is used. This model utilizes the desirability function that presented in [32].…”

Section: Optionmentioning

confidence: 99%

Bi-objective optimization of non-periodic preventive maintenance strategy by considering time value of money

et al. 2019

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Recently, design of preventive maintenance (PM) policies during the warranty period has attracted the attention of researchers. The methods mainly design warranty servicing strategies in a way that reduce the cost imposed on the manufacturer without considering the impact of customer dissatisfaction. While dissatisfaction with a product is an important issue which may result in the loss of potential buyers and switching existing buyers to competitors.Therefore, this study develops a bi-objective model which simultaneously minimizes the manufacturer and the buyer cost under a Non-homogeneous Poisson Process framework. Also, a non-periodic preventive maintenance strategy is presented in which PM actions are performed at discrete time instants in a way that the expected number of failures remains a constant value over all PM intervals. Furthermore, it is a known fact that the value of money reduces over time due to different reasons and has a significant impact on long-term contracts. Since PMs and repairs are conducted at different times, the time value of money is considered to estimate the cost more accurately. A comparative study is conducted to support this claim that the presented nonperiodic reliability-based PM policy has a better performance in comparison with a periodic PM policy.

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“…Under such condition, the multi-response model must be able to consider the correlation among quality characteristic. A number of recent studies which have been attended variance-covariance framework of responses are Cheng et al (2013), Rathod et al (2013), Romano et al (2004) and Salmasnia et al (2013).…”

Section: Multi-objective Robust Optimizationmentioning

confidence: 99%

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

Parnianifard¹,

Azfanizam²,

Ariffin³

et al. 2018

10.5267/j.ijiec

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Nowadays, process optimization has been an interest in engineering design for improving the performance and reducing cost. In practice, in addition to uncertainty or noise parameters, a comprehensive optimization model must be able to attend other circumstances which might be imposed in problems under real operational conditions such as dynamic objectives, multiresponses, various probabilistic distribution, discrete and continuous data, physical constraints to design parameters, performance cost, computational complexity and multi-process environment. The main goal of this paper is to give a general overview on topics with brief systematic review and concise discussions about the recent development on comprehensive robust design optimization methods under hybrid aforesaid circumstances. Both optimization methods of mathematical programming based on Taguchi approach and robust optimization based on scenario sets are briefly described. Metamodels hybrid robust design is discussed as an appropriate methodology to decrease computational complexity in problems under uncertainty. In this context, the authors' policy is to choose important topics for giving a systematic picture to those who wish to be more familiar with recent studies about robust design optimization hybrid metamodels, also by attending real circumstances in practice. In particular, production and project management are considered as two important methodologies that could be improved by applications of advanced robust design combining with metamodel methods.

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A robust interactive approach to optimize correlated multiple responses

Cited by 16 publications

References 50 publications

A novel desirability function for multi-response optimization and its application in chemical engineering

A novel desirability function for multi-response optimization and its application in chemical engineering

Bi-objective optimization of non-periodic preventive maintenance strategy by considering time value of money

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

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