A New Multi-Criteria Approach for Sustainable Material Selection Problem

Aires, Renan Felinto de Farias; Ferreira, Luciano Vaz

doi:10.3390/su141811191

Cited by 7 publications

(4 citation statements)

References 96 publications

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“…In addition, better quality assessment can also increase efficiency in the frying process, resulting in more consistent and quality products (Ahmad et al, 2021). The implications of this research also include the impact on sustainability, where selecting oil from sustainable sources can reduce the environmental impact of oil production and minimize the waste of raw materials (Aires & Ferreira, 2022). In addition, research in this area supports innovation in the food industry, enabling the development of more innovative and high-quality products to meet increasingly diverse consumer needs.…”

Section: Resultsmentioning

confidence: 95%

Educational Tool for Determining Viscosity Coefficient of Cooking Oil Using Arduino UNO

Hilyana,

Marwoto,

Nugroho

2024

jpppf

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The research aims to determine the quality of cooking oil based on the viscosity coefficient using an Arduino UNO-based viscosity coefficient determining tool. By integrating the Arduino UNO into the viscosity measurement process, this research shows innovation in adapting widely available technology for scientific purposes. The series of tools for determining the value of the viscosity coefficient work if an iron ball enters the fluid and will be detected by magnetic sensors 1 and 2 if it passes through the sensor, which is placed at a predetermined distance. Research was conducted to test the quality of cooking oil by determining the viscosity coefficient. The method research is analyzing recorded videos of the motion of objects falling in oil with Tracker Software. By tracking the video recording of the motion of an object falling in a liquid, data, and graphs of the speed of the falling motion can be obtained. Then from the data obtained, the viscosity value is obtained using the equation. The results of the 5 cooking oils, using the tool, were that oil 1 had a viscosity coefficient of 0.2732 Pa.s; oil 2 with 0.3077 Pa.s; oil 3 with 0.3127 Pa.s; oil 4 with 0.3186; and oil 5 with 0.3218 Pa.s. Meanwhile, the results of the oil viscosity coefficient using manual calculations showed that oil 1 had 0.2733 Pa.s; oil 2 with 0.3089 Pa.s; oil 3 with 0.3136 Pa.s; oil 4 with 0.3188; and oil 5 with 0.3219 Pa.s. The percentage of error that occurs from the tool is 0.17%. The oil with a smaller viscosity coefficient is coconut oil (better quality than palm oil), while the quality of bulk oil is indicated by a larger viscosity coefficient. It could be asserted that the oil's quality improves as the viscosity coefficient decreases.

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Section: Resultsmentioning

confidence: 95%

Educational Tool for Determining Viscosity Coefficient of Cooking Oil Using Arduino UNO

Hilyana,

Marwoto,

Nugroho

2024

jpppf

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“…Mousavi-Nasab and Sotoudeh-Anvari identified some limitations of these algorithms, such as not presenting a solution for the RRP, limiting the assessment of rank reversal cases to the addition/removal of alternatives, and presenting new difficult-to-operationalize methods for practical applications. Moreover, all have a different degree of uncertainty that cannot be estimated because they rely on scores assigned by experts, which are subjective (based on their experience and knowledge)-see the last [31,32]. Unfortunately, none of the above algorithms are more reliable than the statistical approach proposed here, given that the experts have their opinions that cannot be objectively measured.…”

Section: Statistical Comparison Of the Importance Given To The Criter...mentioning

confidence: 99%

A Comparative Analysis of the Criteria for Choosing Sustainable Materials for Façades in Turkey and the European Union

Daskin,

Bărbulescu,

Muntean

et al. 2024

Sustainability

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One of the primary contributors to energy consumption is the construction industry. To address the urgent demand for eco-friendly approaches in this field, this study conducted an investigation on Scopus and Web of Science databases to identify the criteria for selecting sustainable materials for façades. Three groups of criteria were derived after a systematic review: Environmental, Social/economic and Technical. The main goal of the research was to answer the question of whether there are differences in these materials’ selection between Turkey and European Union countries. After applying statistical tests, it was found that there are significant differences in selecting eco-friendly material only from the social/economic perspective. The most important sub-criterion is the economic cost. Comparisons with results from China and US confirm this finding.

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“…The results showed that Polysulfone material was the best choice for solar thermal applications. Aires & Ferreira 84 developed a decision-making framework for selecting the most suitable thermal insulation material for enhancing energy efficiency, by integrating Fuzzy BWM, CRITIC, and Mixed Aggregation by Comprehensive Normalization Technique (MACONT). Among the considered alternatives, Polyisocyanurate was identified as the optimal material based on the defined criteria.…”

Section: Literature Reviewmentioning

confidence: 99%

A decision analysis model for material selection using simple ranking process

Zakeri

Chatterjee

Konstantas

et al. 2023

Sci Rep

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A large number of materials and various criteria fashion material selection problems as complex multi-criteria decision-making (MCDM) problems. This paper proposes a new decision-making method called the simple ranking process (SRP) to solve complex material selection problems. The accuracy of the criteria weights has a direct impact on the outcomes of the new method. In contrast to current MCDM methods, the normalization step has been eliminated from the SRP method as a potential source of producing incorrect results. The application of the method is appropriate for situations with high levels of complexity in material selection because it only considers the ranks of alternatives in each criterion. The first scenario of vital-immaterial mediocre method (VIMM) is used as a tool to derive criteria weights based on expert assessment. The result of SRP is compared with a number of MCDM methods. In order to evaluate the findings of analytical comparison, a novel statistical measure known as compromise decision index (CDI) is proposed in this paper. CDI revealed that the MCDM methods’ outputs for solving the material selection could not be theoretically proven and requires to be evaluated through practice. As a result, the dependency analysis-an additional innovative statistical measure is introduced to demonstrate the reliability of MCDM methods by assessing its dependency on criteria weights. The findings demonstrated that SRP is extremely reliant on criteria weights and its reliability rises with the number of criteria, making it a perfect tool for solving challenging MCDM problems.

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A New Multi-Criteria Approach for Sustainable Material Selection Problem

Cited by 7 publications

References 96 publications

Educational Tool for Determining Viscosity Coefficient of Cooking Oil Using Arduino UNO

Educational Tool for Determining Viscosity Coefficient of Cooking Oil Using Arduino UNO

A Comparative Analysis of the Criteria for Choosing Sustainable Materials for Façades in Turkey and the European Union

A decision analysis model for material selection using simple ranking process

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