Optimization of E-jet Based Micro Manufacturing Process Using Grey Relation Analysis

Das, Raju; Ball, Amit Kumar; Roy, Shibendu Shekhar

doi:10.1016/j.matpr.2017.11.072

Cited by 8 publications

(5 citation statements)

References 15 publications

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“…Currently, the more commonly used comprehensive evaluation methods include the Grey Correlation Method, Artificial Neural Network Method, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) Method, and Fuzzy Comprehensive Evaluation Method. The Grey Correlation Method is applicable to a large number of evaluation indicators, and some indicators have the characteristics of correlation or repetition [33,34]. The Artificial Neural Network Method is more suitable for the case of a large amount of data [35].…”

Section: Methodsmentioning

confidence: 99%

The Framework of Technical Evaluation Indicators for Constructing Low-Carbon Communities in China

et al. 2021

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In recent years, in order to promote the construction of low-carbon communities (LCCs) in China, many scholars have proposed an evaluation indicator system of LCC. The existing indicator systems are mostly established from the macro perspective of environmental impact and resource conservation, but few are from the micro technical perspective. Thus, the aim of this study is to construct a micro technical evaluation indicator system for LCCs. Firstly, the index system was divided into three categories: low-carbon building, low-carbon transportation, and low-carbon environment. Then, the technical indicators were selected through empirical analysis. The indicator weights were assigned by the improved analytic hierarchy process (AHP) and the multi-level fuzzy comprehensive evaluation method was used as the evaluation method of the indicators. Finally, in order to examine the practicality of the indicator system, two typical communities in Tianjin and Shanghai were selected as case studies. The results showed that the indicator system gave a reasonable low-carbon level for the two communities, which was in line with the actual low-carbon construction status of each community. In addition, the evaluation results pointed out that the low-carbon community (LCC) in Tianjin needs to further strengthen the construction of the low-carbon environment, including community compactness, rainwater collection and utilization, and waste recycling. For the LCC in Shanghai, it was pointed out that the construction of the low-carbon building and low-carbon transportation needs to be strengthened. The indicator system can be used as a tool for urban planning and construction personnel to evaluate the construction progress and low-carbon degree of LCC.

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Section: Methodsmentioning

confidence: 99%

The Framework of Technical Evaluation Indicators for Constructing Low-Carbon Communities in China

et al. 2021

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“…Assuming that there is a total of q evaluation levels for the improvement of the knowledge innovation ability, the classical domain corresponding to the h-th evaluation level of the evaluation index (ci) is uh(ci) = [ua h(ci), ub h(ci)]. Based on the grey correlation theory [21][22][23][24], the grey correlation coefficient ζk-h(ci) between the evaluation index ci and the h-th evaluation level for the evaluation object k is given as:…”

Section: 4mentioning

confidence: 99%

Influence of Teacher-Student Matching on Knowledge Innovation of College Students

Zhang

2021

Int. J. Emerg. Technol. Learn.

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The relationship between teacher-student matching and knowledge innovation of college students is constrained by multiple factors. Considering the multiple constraints, this paper explores deep into the influence of teacher-student matching on knowledge innovation of college students. Firstly, the internal correlation between the two factors was identified through analysis. Next, the detailed contents of the two factors were examined, and used to set up an analysis model to improve knowledge innovation of college students based on teacher-student matching. Grey system theory and analytic hierarchy process (AHP) were implemented in the modeling process. Finally, several strategies were put forward to promote knowledge innovation among college students, from the perspective of teacher-student matching. The research results provide a strong support to knowledge innovation in colleges.

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“…. , n } is a set of grey related elements [12]. At a certain moment, the grey correlation degree of two sets of series can be expressed by grey correlation coefficient r(x 0 (k), x i (k)), which is defined as below:…”

Section: Gra-fuzzy Logic Modelmentioning

confidence: 99%

Research on Optimized Product Image Design Integrated Decision System Based on Kansei Engineering

Lei

Zhang³

2020

Applied Sciences

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In order to facilitate the development of product image design, the research proposes the optimized product image design integrated decision system based on Kansei Engineering experiment. The system consists of two sub-models, namely product image design qualitative decision model and quantitative decision model. Firstly, using the product image design qualitative decision model, the influential design elements for the product image are identified based on Quantification Theory Type I. Secondly, the quantitative decision model is utilized to predict the product total image. Grey Relation Analysis (GRA)–Fuzzy logic sub-models of influential design elements are built up separately. After that, utility optimization model is applied to obtain the multi-objective product image. Finally, the product image design integrated decision system is completed to optimize the product image design in the process of product design. A case study of train seat design is given to demonstrate the analysis results. The train seat image design integrated decision system is constructed to determine the product image. This shows the proposed system is effective and for predicting and evaluating the product image. The results provide meaningful improvement for product image design decision.

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Optimization of E-jet Based Micro Manufacturing Process Using Grey Relation Analysis

Cited by 8 publications

References 15 publications

The Framework of Technical Evaluation Indicators for Constructing Low-Carbon Communities in China

The Framework of Technical Evaluation Indicators for Constructing Low-Carbon Communities in China

Influence of Teacher-Student Matching on Knowledge Innovation of College Students

Research on Optimized Product Image Design Integrated Decision System Based on Kansei Engineering

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