scholarly journals Drilling Process on CFRP: Multi-Criteria Decision-Making with Entropy Weight Using Grey-TOPSIS Method

2020 ◽  
Vol 10 (20) ◽  
pp. 7207
Author(s):  
Quang-Phuoc Tran ◽  
Van-Nhat Nguyen ◽  
Shyh-Chour Huang
Keyword(s):  
Decision Making ◽  
Surface Roughness ◽  
Feed Rate ◽  
Twist Angle ◽  
Tool Geometry ◽  
Main Body ◽  
Drilling Process ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Machining Parameter

Moisture strongly affects the quality and mechanical specificity of carbon fiber reinforced plastic (CFRP) when using lubrication fluids during machining, and the significant impact of the cutting tool geometry and cryogenic gas cooling on CFRP machining capabilities are observed. The main body of this paper aims at making decisions about the optimum parameter of the drilling process while machining on CFRP base on the grey relational coefficient embed to the technique for order of preference by similarity to an ideal solution (Grey-TOPSIS). The entropy method was used to determine the weight of decision-making for handling a multiple measure decision-making response. The twist angle of the tool drill, lubrication, and feed rate were used as the input variables, and were analyzed while taking into account several multi-response outputs, such as the surface roughness, uncut fiber, and delamination. The result showed that a feed rate of 228 mm/min, the high-helix twist angle, and cryogenic CO2 lubrication leads the calculated value to close the relative value, which minimizes the value of the surface roughness, the uncut fiber, and the delamination. Finally, verification of the valid effect of each parameter process was conducted using analysis of variance. The results indicated that the lubrication was the highest remarkable criterion on the uncut fiber, the delamination, and the surface roughness. By integrating the advantage of grey systems theory, and the technique for order preference by similarity to an ideal solution, to evaluate and optimize the machining parameter, the results indicate that the proposed model is useful to facilitate the multi-criteria decision-making problem under the environment of uncertainty and vagueness. This relatively advanced approach is very effectual in rejecting process variation and a great assistive strategy than other multi-criteria decision-making approaches.

Surface Roughness Analysis of Carbon/Glass Hybrid Polymer Composites in Drilling Process Based on Taguchi and Response Surface Methodology

2015 ◽  
Vol 1119 ◽  
pp. 622-627 ◽  
Author(s):  
Chye Lih Tan ◽  
Azwan Iskandar Azmi ◽  
Noorhafiza Muhammad
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Regression Model ◽  
Response Surface ◽  
Feed Rate ◽  
Hybrid Composite ◽  
Spindle Speed ◽  
Tool Geometry ◽  
Secondary Process ◽  
Drilling Process

Drilling is an essential secondary process for near net-shape of hybrid composite as to achieve the required dimensional tolerances prior to final application. Dimensional tolerance is often influenced by the surface integrity or surface roughness of the workpart. Thus, this paper aims to employ the Taguchi and response surface methodologies in minimizing the surface roughness of drilled carbon-glass hybrid fibre reinforced polymer (CGCG) using tungsten carbide, K20 drill bits. The effects of spindle speed, feed rate and tool geometry on surface roughness were evaluated and optimum cutting conditions for minimizing the aforementioned response was determined. Subsequently, response surface methodology (RSM) was utilised in finding the empirical relationships between experimental parameters and surface roughness based on the Taguchi results. The experimental analyses reveal that surface roughness is greatly influenced by feed rate and tool geometry rather than the spindle speed. This is due to the increment of feed that attributed to the increased strain rate and hence, deteriorated the surface roughness of the hybrid composite. The predicted results (via regression model) and theoretical results (via additivity law) were in good agreement with experiment results. This indicates that the regression model from response surface methodology (RSM) can be used to predict the surface roughness in machining of CGCG hybrid composite.

Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Decision Model ◽  
Business Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Making Model

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

Optimum criterion for lightweight nonlinear confusion component with multi-criteria decision making

2021 ◽  
pp. 1-12
Author(s):  
Nabilah Abughazalah ◽  
Majid Khan ◽  
Noor Munir ◽  
Amna Zafar
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Mathematical Structures ◽  
Substitution Boxes

In this article, we have designed a new scheme for the construction of the nonlinear confusion component. Our mechanism uses the notion of a semigroup, Inverse LA-semigroup, and various other loops. With the help of these mathematical structures, we can easily build our confusion component namely substitution boxes (S-boxes) without having specialized structures. We authenticate our proposed methodology by incorporating the available cryptographic benchmarks. Moreover, we have utilized the technique for order of preference by similarity to ideal solution (TOPSIS) to select the best nonlinear confusion component. With the aid of this multi-criteria decision-making (MCDM), one can easily select the best possible confusion component while selecting among various available nonlinear confusion components.

scholarly journals Effect of Cutting Parameters and Tool Geometry on the Performance Analysis of One-Shot Drilling Process of AA2024-T3

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 854
Author(s):  
Muhammad Aamir ◽  
Khaled Giasin ◽  
Majid Tolouei-Rad ◽  
Israr Ud Din ◽  
Muhammad Imran Hanif ◽  
...  
Keyword(s):  
Feed Rate ◽  
Surface Defects ◽  
Thrust Force ◽  
Cutting Tools ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Machining Process ◽  
Tool Geometry ◽  
Drilling Process

Drilling is an important machining process in various manufacturing industries. High-quality holes are possible with the proper selection of tools and cutting parameters. This study investigates the effect of spindle speed, feed rate, and drill diameter on the generated thrust force, the formation of chips, post-machining tool condition, and hole quality. The hole surface defects and the top and bottom edge conditions were also investigated using scan electron microscopy. The drilling tests were carried out on AA2024-T3 alloy under a dry drilling environment using 6 and 10 mm uncoated carbide tools. Analysis of Variance was employed to further evaluate the influence of the input parameters on the analysed outputs. The results show that the thrust force was highly influenced by feed rate and drill size. The high spindle speed resulted in higher surface roughness, while the increase in the feed rate produced more burrs around the edges of the holes. Additionally, the burrs formed at the exit side of holes were larger than those formed at the entry side. The high drill size resulted in greater chip thickness and an increased built-up edge on the cutting tools.

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

Satisfaction Degree Based Interactive Decision Making under Hesitant Fuzzy Environment with Incomplete Weights

2014 ◽  
Vol 22 (04) ◽  
pp. 553-572 ◽  
Author(s):  
Huchang Liao ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Hesitant Fuzzy Set ◽  
Optimization Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Fuzzy Information ◽  
Satisfaction Degree ◽  
Interactive Decision Making ◽  
New Research ◽  
Topsis Technique

Multi-criteria decision making with hesitant fuzzy information is a new research topic since the hesitant fuzzy set was firstly proposed. This paper investigates a multi-criteria decision making problem where the weight information is partially known. We firstly propose the hesitant fuzzy positive ideal solution and the hesitant fuzzy negative ideal solution. Motivated by the TOPSIS (Technique for Order Preference by Similarity to an ideal Solution) method, we definite the satisfaction degree of an alternative, based on which several optimization models are derived to determinate the weights. Subsequently, in order to make a more reasonable decision, we introduce an interactive method based on some optimization models for multi-criteria decision making problems with hesitant fuzzy information. Finally, a practical example on evaluating the service quality of airlines is provided to illustrate our models and method.

scholarly journals SELECTING THE OPTIMAL RENEWABLE ENERGY USING MULTI CRITERIA DECISION MAKING

2013 ◽  
Vol 14 (5) ◽  
pp. 957-978 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini ◽  
Mohammad Majid Fouladgar ◽  
Edmundas Kazimieras Zavadskas ◽  
S. Hamzeh Haji Moini
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Evaluation Criteria ◽  
Energy Resources ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Proposed Model ◽  
Negative Ideal Solution ◽  
Hierarchy Process ◽  
The Ideal

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.

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