A low-carbon evaluation method for manufacturing products based on fuzzy mathematics

Dong, Chaoqun; Bi, Kexin

doi:10.1080/21642583.2020.1734987

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…A further application consists of using the C-means and the Gaussian Mixture model to observe the operations of a machine in real-time: the aim is to define the degradation severity and assess the necessity for a predictive intervention (Dasuki Yusoff et al, 2019). Fuzzy clustering can also be applied to define a low carbon evaluation method for product manufacture and maintenance (Dong & Bi, 2020) or to monitor the oil status to predict machinery failures (Yanchun et al, 2010). Fuzzy k-means and adaptive neuro-fuzzy inference have also been applied to predict a distillation column's remaining useful life in the chemical industry (Daher et al, 2020).…”

Section: Clustering Of Data Using Fuzzy K-meansmentioning

confidence: 99%

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Bellinello,

Antomarioni,

Souza

et al. 2022

Prod.

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Paper aims: This paper aims to develop a proper maintenance policy directly related to defining critical components for ensuring a high level of safety and high-level in-service quality for all hydro generator units.Originality: An innovative integrated tool that contributes to ensuing assertiveness in decision-making to determine the critical components is presented in this study. Specifically, hydro-generator unit type Kaplan belonging to a Brazilian Hydroelectric power plant is used as an application case to highlight the choice of the most suitable maintenance policy in light of the proposed approach. The selection of the case study is based on the fact that hydroelectric power plants are the basis of the Brazilian energy matrix, accounting for 75% of the demand in the country. Therefore, the need to maintain hydroelectric plants' availability and operational reliability is clear not to compromise the continuity and conformity (quality) of the electrical energy supply.Research method: Seven multi-criteria decision-making methods were applied in addition to two methods for deciding weight (Critic Method and Entropy) have been compared to determine the critical components of the hydro-generator. To investigate the robustness of the classification of the applied Multi-Criteria Decision Making approaches, a sensitivity analysis was performed based on the weight change of each decision criterion. Main findings:As a main result, the Entropy-Multi-Attribute Utility Theory model is proposed as the best approach to guarantee the selection of critical components for the Brazilian hydroelectric power plant case study. The validation sensitivity analysis by critical Fuzzy K-means groups guarantees that it is a robust tool for decision-making.Implications for theory and practice: Ensuring the availability and reliability of hydroelectric plants can be achieved by employing appropriate maintenance policies that reduce the likelihood of failure or even eliminate its root causes, preventing failure from occurring. Consequently, a robust tool for decision-making regarding the Kaplan hydro generator's critical components' monitoring was developed.

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Section: Clustering Of Data Using Fuzzy K-meansmentioning

confidence: 99%

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Bellinello,

Antomarioni,

Souza

et al. 2022

Prod.

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show abstract

“…Fuzzy mathematics is a mathematical theory and method for studying and processing fuzzy phenomena (Wang et al., 2020 ). It can quantify unclear or unquantifiable boundaries, and scientifically and comprehensively evaluate the multiple quality indicators of the target (Dong & Bi, 2020 ; Minaev et al., 2020 ). Sensory evaluation is currently the primary method for determining liquor quality, blending, and flavoring.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive evaluation of Luzhou‐flavor liquor quality based on fuzzy mathematics and principal component analysis

Liu

Qiao

Zhao

et al. 2022

Food Science & Nutrition

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Currently, the primary method of identifying high‐ and low‐quality liquors is sensory tasting, which is prone to uncertainty caused by the biases of tasters. To address this problem, this study used color, aroma, taste, and style as four factors affecting the sensory quality of Luzhou‐flavor liquor; determined the weights of each factor; and quantitatively evaluated the sensory quality of five different Luzhou flavor liquor using fuzzy mathematical methods. The volatile aromatic substances in the liquor samples were detected by GC‐MS, and analyzed using principal component analysis. The results obtained from fuzzy mathematics and principal component analysis indicated that the comprehensive evaluation system was scientifically sound and reasonably constructed.

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“…The technological progresses which are needed to develop the low-carbon economy refer to the low-carbon technologies that can decrease the carbon emission level in the production process rather than ordinary technological progresses which can only increase the production efficiency only. Therefore, the innovation and applications of low-carbon technology as important indispensable support to the low-carbon economic development are core impetus needed to develop the lowcarbon economy [9]. As one of important routes to realize the goal of greenhouse gas emission reduction, accelerating lowcarbon technological innovation has been widely accepted in the world [10].…”

mentioning

confidence: 99%

On Innovation Performance of Low-Carbon Technology Breakthrough Innovation Network in Manufacturing Industry Under the Global Value Chain: A Case Study Based on Chinese Manufacturing Industries

Dong

2020

IEEE Access

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The strengthening scientific and reasonable quantitative evaluation of innovation performance of low-carbon technology breakthrough innovation network in manufacturing industry under the background of economic globalization is of important significance, which can enrich relevant theoretical system of low-carbon technology breakthrough and improve the core competitiveness of Chinese manufacturing industries. In this paper, the scientific and reasonable quantitative evaluation of the innovation performance of low-carbon technology breakthrough innovation network is firstly determined as a dynamic (timevarying) evaluation problem, which involves multi-source influencing factors. Note that many evaluation objects in the innovation performance of an innovation network are gray, ambiguous and dynamic variables, which are difficult to be quantified and the collected industrial data has certain discreteness and fluctuation. Hence, a fuzzy clustering analysis on influencing variables of innovation performance of low-carbon technology innovation network is carried out via the sampling data from 28 manufacturing industries during 2011-2016. Moreover, an innovation performance evaluation model for low-carbon technology innovation network is constructed through analytic hierarchy process (AHP), grey theory and fuzzy clustering analysis. Based on this model, the qualitative and quantitative evaluations of innovation performances of the innovation network before and after low-carbon technology breakthrough are realized. The results show that the low-carbon technology breakthrough innovation has a positive effect on improving the development level of manufacturing industry. In addition, the construction performance evaluation model not only decreases the influences of subjective factors by combining qualitative analysis with quantitative analysis, but also applies the grey theory innovatively to determine the membership matrix. It realizes accurate, systematic and scientific evaluation of the innovation performance of the low-carbon technology breakthrough innovation network in the manufacturing industries. Finally, the research conclusions provide the theoretical and practical references to the strategic arrangement of the low-carbon technology breakthrough innovation in Chinese manufacturing industries. INDEX TERMS Low-carbon technology breakthrough innovation; Innovation network; Innovation performance; Chinese manufacturing industries; AHP I. INTRODUCTION With the continuous transition of global technological innovative ability, the innovation-driven development has be

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A low-carbon evaluation method for manufacturing products based on fuzzy mathematics

Cited by 6 publications

References 12 publications

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Entropy-MAUT integrated approach supported by Fuzzy K-means: a robust tool for determining critical components for maintenance monitoring and a case study of Kaplan hydro generator unit

Comprehensive evaluation of Luzhou‐flavor liquor quality based on fuzzy mathematics and principal component analysis

On Innovation Performance of Low-Carbon Technology Breakthrough Innovation Network in Manufacturing Industry Under the Global Value Chain: A Case Study Based on Chinese Manufacturing Industries

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