Process optimization using sequential design of experiment: A case study

Lv, Shanshan; He, Zhen; Quevedo, A. Valeria; Mirabile, Yiming Zhang; Vining, G. Geoffrey

doi:10.1080/08982112.2018.1539232

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…If there is only one factor affecting the response, the one-way ANOVA and the multiple comparison methods, such as Tukey’ test and least significance difference method, are used to determine an appropriate level of a significant factor based on a desired criterion (maximization, minimization or desired target). Otherwise, the 2 k + center point and ANOVA will be used to investigate whether there is an evidence of curvature in the response over the region of exploration (Montgomery, 2005; Lee, 2019; Lv, 2019). If the curvature does not exist in the model, the experimenter needs to adjust the levels of each factor using the method of steepest ascent or steepest descent for the criterion of maximaization or minimization.…”

Section: Methodsmentioning

confidence: 99%

“…Coleman and Antony (2000) stated that many teachers could not present real case studies in a classroom because of a lack of practical experience with DOE. To overcome this issue, Lv et al (2019) presented a case study of the startup of an ethanol–water distillation column to provide a practical experience of sequential learning strategy in solving complex system with DOE. The practical experience with DOE provided students and engineers guidance and capability of complex problem-solving, enabling an effective use of DOE.…”

Section: Introductionmentioning

confidence: 99%

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How to motivate students to do a course project in design of experiments course from a web-based virtual learning material?

Saikaew

2022

IJLSS

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Purpose The purpose of this study is to develop a practical method for training students how to conduct statistical analysis and do a course project in design of experiments (DOEs) course through the Web-based virtual catapult simulation. Design/methodology/approach A step-by-step sequential DOE process for investigating the effects of controllable factors on quality characteristic responses was presented as a guideline for conducting a DOE course project. Each team was assigned to create an innovative teaching material and work on the term report by following the recommended guidelines for designing experiments through the Web-based virtual catapult simulation. Hypothesis was defined to test whether doing a course project based on this approach would impact students’ learning outcome. Findings The Web-based virtual material was an alternative technique for interactive teaching that could improve students’ understanding and achievement in DOE course projects. There was a significant difference in student learning and understanding before and after doing on the course project through the Web-based virtual catapult simulation. The students had improved communication and teamwork skills after following the recommended procedure for practicing DOEs. Practical implications Most students could effectively conduct designing experiments, carry out designed experiments, analyze data and gain valuable teamwork experience. After learning the DOE approach based on the catapult simulation, they enjoyed working on their course projects deploying to the innovative toys and other real-life situations with real measurements. Originality/value The use of Web-based virtual material, including catapult simulation, was an alternative technique for interactive DOE teaching to improve the students’ understanding and achievement in DOE course projects.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

How to motivate students to do a course project in design of experiments course from a web-based virtual learning material?

Saikaew

2022

IJLSS

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“…The use of PB designs as a screening experiment, followed by the sequential use of Complete, Central Composite or Central Composite Rotational designs, e.g., were successfully employed to develop and evaluate the properties of an oil-based emulsion gel, optimize the production of an enzyme by an actinomycete in submerged fermentation, and to develop a method of sterols and squalene extraction and determination in cyanobacteria (CÂMARA et al, 2020;FAGUNDES et al, 2021;PATEL et al, 2021). The initial use of FF designs, followed by the sequential use of CF and/or Central Composite designs, in turn, was used by Keijok et al (2019) to optimize a method used in the synthesis of metallic nanoparticles, by Gautério et al (2020) to maximize the production of an enzyme by a yeast-like fungus using a by-product of rice grain milling, and by Lv et al (2019) to optimize an ethanol-water distillation column. According to the authors, the results obtained in the initial screening designs were essential to, in an economical number of experiments, identify significant factors that were affecting the system's response.…”

Section: Sequential Experimentationmentioning

confidence: 99%

Fundamental Concepts and Recent Applications of Factorial Statistical Designs

Mainardi

Bidóia

2022

Braz. Jour. Biom.

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Factorial designs have been increasingly used in scientific investigations and technological development. The designs, through the use of matrices with all the treatment combinations, have been capable to effectively characterize the relationships between the variables of multi-factor experiments, assess the experimental variabilities, and derive mathematical functions that represent the behavior of the responses. Factorial designs were fractionalized, which substantially reduced the number of treatments without the loss of relevant information. The addition of central and star points to the factorial arrays has given them the orthogonality and rotatability characteristics, frequently used to fit models with curvature and identify critical regions of interest. Literature reports indicated that factorial designs, also called factorial experiments, were successfully applied in different types of investigations, including in cost evaluations and time-series studies. They were capable to estimate important features of the experiments, like the individual and combined effects of factors, the magnitude of residuals, additionally to express the relationships of the variables in polynomial equations, draw response surface and contour plots, and determine optimal combinations of parameters. In this review, the fundamental aspects of the Complete, Fractional, Central Composite Rotational and Asymmetrical factorial designs were conceptualized, and recent applications of these powerful tools were described.

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“…In many problems, the authors justify their approach to solve the problem, and use two out of three experimental phases, namely, screening/characterization [44] and screening/optimization [45]. A comprehensive example of the sequential learning process in the response surface methodology framework, including the optimization of multiple responses simultaneously, is presented by Lv et al [46].…”

Section: Doe's Principles and Experimentation Strategymentioning

confidence: 99%

Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods

Costa

Fontes

2020

Sustainability

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Some (non)manufacturing industries are becoming more energy efficient, but many of them are losing cost-effective energy-savings opportunities, namely, by lack of knowledge or underestimation of good engineering and management practices as well as guidance on techniques or tools for that purpose. This study points out that Design of Experiments is a tool that cannot be ignored by managers and other technical staff, namely, by those who have the responsibility to eliminate energy waste and promote energy-efficiency improvement in industry, mainly in energy-intensive manufacturing industries. A review on Design of Experiments for physical and simulation experiments, supported on carefully selected references, is provided, since process and product improvement at the design and manufacturing stages increasingly rely on virtual tests and digital simulations. However, the expense of running experiments in complex computer models is still a relevant issue, despite advances in computer hardware and software capabilities. Here, experiments were statistically designed, and several easy-to-implement yet effective data analysis methods were employed for identifying the variables that must be measured with more accurate devices and methods to better estimate the energy efficiency or improve it in a billets reheating furnace. A simulation model of this type of furnace was used to run the experiments and the results analysis shows that variables with practical effect on the furnace’s energy efficiency are the percentage of oxygen in the combustion gases, the fuel flow in the burners, and the combustion air temperature.

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Process optimization using sequential design of experiment: A case study

Cited by 4 publications

References 21 publications

How to motivate students to do a course project in design of experiments course from a web-based virtual learning material?

How to motivate students to do a course project in design of experiments course from a web-based virtual learning material?

Fundamental Concepts and Recent Applications of Factorial Statistical Designs

Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods

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