Analysis of a solar desalinator (humidification–dehumidification cycle) including a compound system consisting of a solar humidifier and subsurface condenser using DoE

Okati, Vahab; Behzadmehr, A.; Farsad, Saeed

doi:10.1016/j.desal.2016.06.010

Cited by 23 publications

(8 citation statements)

References 19 publications

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“…Applying Equations (19) and Equation (20) in the design matrix (Table 8) main effects are calculated and shown in Table 9. …”

Section: Fractional Factorial Designmentioning

confidence: 99%

“…Fractional factorial designs with the highest available resolution with their defining relations is shown in Table 6. DOE a very suitable tool used for process performance and product quality improvement [18], for solar technologies [19] etc. In this example DOE is applied on injection-molding process with the aim of improving product quality such as excessive flash.…”

Section: Fractional Factorial Designmentioning

confidence: 99%

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Design of experiments application, concepts, examples: State of the art

Duraković

2017

PEN

204

144

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Design of Experiments (DOE) is statistical tool deployed in various types of system, process and product design, development and optimization. It is multipurpose tool that can be used in various situations such as design for comparisons, variable screening, transfer function identification, optimization and robust design. This paper explores historical aspects of DOE and provides state of the art of its application, guides researchers how to conceptualize, plan and conduct experiments, and how to analyze and interpret data including examples. In addition, this paper reveals that in past 20 years application of DOE have been growing rapidly in manufacturing as well as nonmanufacturing industries. It was most popular tool in scientific areas of medicine, engineering, biochemistry, physics, computer science and counts about 50% of its applications compared to all other scientific areas. Keyword:Design of Experiments, full factorial design; fractional factorial design; product design; quality improvement;

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“…Applying Equations (19) and Equation (20) in the design matrix (Table 8) main effects are calculated and shown in Table 9. …”

Section: Fractional Factorial Designmentioning

confidence: 99%

Section: Fractional Factorial Designmentioning

confidence: 99%

Design of experiments application, concepts, examples: State of the art

Duraković

2017

PEN

204

144

View full text Add to dashboard Cite

show abstract

“…The application of DOE models is known to benefit a wide range of industries, such as Aviation (Yondo et al, 2018;Davis et al, 1996), Service (Antony et al, 2020;Setamanit, 2018), Chemical Engineering (Yoo, 2020;Durakovic & Torlak, 2017;Andersson et al, 1996), Engineering (Schlueter & Geyer, 2018), Environment (Okatia et al, 2016;Yang & Tsai, 1998), Food Technology (Yu et al, 2018;Chen, 1996), Manufacturing (Wesling & Emamjomeh, 1994), Materials (Paulo et al, 2017;Bucher & Loos, 1994), Medical (Yip et al, 2020;Mager, 1997), andMicrobiology (Puente-Massaguer et al, 2020). Within the field of engineering and science, DOE's applications are frequently visible in the materials sector (30 %), mechanical engineering (18%), chemical engineering (17 %), and the industrial sector (13 %).…”

Section: What Is Doe?mentioning

confidence: 99%

Critical Evaluation into the practical utility of the Design of Experiments

Sharma

2021

Engineering Management in Production and Services

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The research aims to emphasise the relevance of the Design of Experiments (DOE) technique as a reliable method for ensuring efficient use of statistical methods in routine industrial processes. A case study approach with a deductive strategy was used to assess the effectiveness of different DOE methods to achieve the desired objectives. Screening, mid-resolution and high-resolution DOE methods helped identify, characterise, and optimise an experimental variable against the desired output response. A general framework for effective DOE is provided as part of DOE planning, including defining DOE objectives, selection criteria, noise reduction, and application across industries. Overall, various DOE models proved successful in identifying a complicated relationship between experimental variables and output response. However, when ideal DOE models may not be feasible, reducing test run by choosing lower resolution DOE or fewer replicates can still provide important insights into the experimental variables’ impact on output responses.

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“…Their results indicate the effectiveness of the methodology to verify the process. Okati et al [18] analyzed the sensitivity of a solar desalinator's primary parameters using design of experiment (DoE) method based on response surface method (RSM) in order to obtain optimal conditions. They presented different diagram to assist the designer to choose suitable design parameters based on the operational conditions.…”

Section: Introductionmentioning

confidence: 99%