scholarly journals Thermoplastic Matrix Material Selection Using Multi Criteria Decision Making Method for Hybrid Polymer Composites

2014 ◽  
Vol 564 ◽  
pp. 439-443 ◽  
Author(s):  
Muhd Ridzuan Mansor ◽  
S.M. Sapuan ◽  
Edi Syam Zainudin ◽  
A.A. Nuraini ◽  
Arep Ariff Hambali
Keyword(s):  
Decision Making ◽  
Polymer Composites ◽  
Natural Fiber ◽  
Material Selection ◽  
Selection Process ◽  
Matrix Material ◽  
Final Decision ◽  
Multi Criteria Decision Making ◽  
Hybrid Polymer ◽  
Thermoplastic Matrix

Multi criteria decision making (MDCM) methods are amongst the approaches available in aiding composite designers to make the final decision especially during the material selection process where multiple solutions are present and various requirements are required to be satisfied simultaneously. Thus, in this paper, material selection process of thermoplastic matrix using MDCM methods for hybrid natural fiber/glass fiber polymer composites is presented. The aim is to identify the most suitable type of thermoplastic matrix to be used in the hybrid polymer composites formulation. The Weighted Sum Method (WSM) is applied in the selection process of seven candidate thermoplastic matrix materials based on the product design specifications. The overall analysis highlights that low density polyethylene (LDPE) is the preferred matrix for the intended application based on the highest scores obtained compared to other candidate materials. A signal-to-noise (S/N) ratio analysis was further performed to validate the initial selection results where LDPE once again outperformed other candidate materials with highest S/N ratio score in the non-compensatory approach.

An Improved TOPSIS Method for Material Selection Model

2014 ◽  
Vol 951 ◽  
pp. 120-123
Author(s):  
Wei Fan Huang
Keyword(s):  
Decision Making ◽  
Influencing Factors ◽  
Material Science ◽  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Science Field

Material selection problem becomes an important issue in the material science field. It is important for design for mechanical, electrical, thermal, chemical et al. There are several influencing factors in the material selection process, and thus material selection problem is a multi-criteria decision making (MCDM) problem. Relative entropy measure can depict the closeness of the two systems, and then this paper will use it to develop an improved TOPSIS method for the material selection problem. Finally, a practical example is given to demonstrate that the proposed method is effective and feasible.

Development of a fuzzy-TOPSIS multi-criteria decision-making model for material selection with the integration of safety, health and environment risk assessment

2021 ◽  
pp. 146442072199426
Author(s):  
Aamir AA Rahim ◽  
S Numaya Musa ◽  
S Ramesh ◽  
Ming K Lim
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Material Selection ◽  
Manufacturing Sector ◽  
Selection Process ◽  
Complex Structure ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Automotive Body ◽  
Risks Assessment

This study presents the development of a fuzzy-TOPSIS multi-criteria decision-making (MCDM) model for material selection with integrated safety, health, and environment risk assessment. As safety, health, and environment is very much linked to sustainable design and manufacturing, it is imperative that safety, health, and environment is taken into consideration in ensuring a comprehensive and holistic material selection process. This paper shows the possibility of fuzzy logic utilization in assessing safety, health, and environment risk and proposed a methodology based on fuzzy-TOPSIS MCDM model for material selection suitable for the manufacturing sector. This method has the capability of producing a ranking result with strong reasonings. The proposed method facilitates the designer to select, evaluate, and rank material alternatives based on given attributes from design requirements and weighting given by the decision-makers. Additionally, the other benefits of the proposed methodology are the elimination of a complex structure and/or a black-box algorithm. The fuzzy-TOPSIS approach capable of considering not only the uncertainty related to qualitative judgments but also the uncertainty that may reside in the measurement of quantitative or qualitative parameters that exist within the safety, health, and environment risks assessment. A numerical example of selecting material for automotive body panels using the proposed method has been discussed.

scholarly journals Modelling approach for multi-criteria decision-making selection process for artificial lift systems in crude oil production

2018 ◽  
Vol 8 (1) ◽  
pp. 53-60
Author(s):  
Javier Duran-Serrano
Keyword(s):  
Decision Making ◽  
Crude Oil ◽  
Selection Process ◽  
Oil Production ◽  
Final Decision ◽  
Multi Criteria Decision Making ◽  
Software Application ◽  
Artificial Lift ◽  
Crude Oil Production ◽  
Key Factor

Artificial Lift system selection is a key factor in enhancing energy efficiency, increasing profit and expanding asset life in any oilproducing well. Theoretically, this selection has to consider an extensive number of variables, making hard to select the optimal Artificial Lift System. However, in practice, a limited number of variables and empirical knowledge are used in this selection process. The latter increases system failure probability due to pump – well incompatibility. The multi-criteria decision-making methods present mathematical modelling for selection processes with finite alternatives and high number of criteria. These methodologies make it feasible to reach a final decision considering all variables involved.In this paper, we present a software application based on a sequential mathematical analysis of hierarchies for variables, a numerical validation of input data and, finally, an implementation of Multi-Criteria Decision Making (MCDM) methods (SAW, ELECTRE and VIKOR) to select the most adequate artificial lift system for crude oil production in Colombia. Its novel algorithm is designed to rank seven Artificial Lift Systems, considering diverse variables in order to make the decision. The results are validated with field data in a Casestudy relating to a Colombian oilfield, with the aim of reducing the Artificial Lift Failure Rate.

Application of Recently Developed MCDM Methods for Materials Selection

2015 ◽  
Vol 809-810 ◽  
pp. 1468-1473
Author(s):  
Dušan Petković ◽  
Miloš Madić ◽  
Miroslav Radovanović ◽  
Predrag Janković
Keyword(s):  
Decision Making ◽  
Material Selection ◽  
Selection Process ◽  
Multi Criteria Decision Making ◽  
The Novel ◽  
Materials Selection ◽  
Suitable Material ◽  
Product Assessment ◽  
Designed Materials ◽  
Selection Of

It is well known fact that materials play an important role in engineering design. Nowadays over a hundred thousand available materials can be distinguished with constant tendency for increasing the novel designed materials. Therefore material selection process becomes a complex and time consuming task. Selection of the most suitable material for a given application can be regarded as a multi-criteria decision making (MCDM) problem with conflicting and diverse objectives. New MCDM methods have been developed, and existing methods improved, showing that research in the decision-making is important and still valuable. This paper describes the use of recently developed MCDM methods, i.e. Complex Proportional Assessment (COPRAS) and Weighted Aggregated Sum Product Assessment (WASPAS) for selecting the most suitable hard coating material.

Hybrid Multi-Criteria Decision-Making Optimization Strategy for RP Material Selection

2019 ◽  
pp. 320-334
Author(s):  
Jagadish ◽  
Sumit Bhowmik ◽  
Suresh Gudala
Keyword(s):  
Decision Making ◽  
Computer Aided Design ◽  
Material Selection ◽  
Selection Process ◽  
Real Life ◽  
Multi Criteria Decision Making ◽  
Optimization Strategy ◽  
Rp Process ◽  
Criteria Weights ◽  
Optimal Material

Rapid prototyping (RP) is an advanced manufacturing technique that uses a computer-aided design data for designing a prototype. To design a part, the RP uses many kinds of materials that best suit the application. Due to the existence of a large number of RP materials that make the selection process quite challenging and considered to be a multi-criteria decision-making (MCDM) optimization problem. The chapter proposed a hybrid MCDM optimization strategy for optimal material selection of the RP process. The hybrid strategy consists of modified DEMATEL with TOPSIS where the extraction of criteria weights using modified DEMATEL strategy while ranking of RP alternatives considering the effect of beneficial and non-beneficial using TOPSIS strategy. A real-life case study on RP material selection is demonstrated to validate the proposed strategy.

Thermoplastic Polymer Selection for Optimal Thermal Efficiency of Composite Syrup Vessel

2021 ◽  
Vol 1021 ◽  
pp. 35-44
Author(s):  
Mohaiman J. Sharba ◽  
Mohammed J. Al-Mostaaf
Keyword(s):  
Decision Making ◽  
Natural Fiber ◽  
Mechanical Design ◽  
Material Selection ◽  
Multi Criteria Decision Making ◽  
Thermoplastic Polymer ◽  
Nylon 6,6 ◽  
Material Choice ◽  
Decision Making Model ◽  
Hierarchy Process

Material selection is one of the vital and critical steps in the mechanical design process. In recent times, various tools based on the multi-criteria decision-making process are used successfully to cope with such complexity in material selection. .This work provides appropriate methods and tools to find the optimum thermoplastic polymer reinforced natural fiber composites. The material selection applied using a decision-making model that consists of the „Technique for Order of Preference by Similarity to Ideal Solution“ (TOPSIS) and „Vlsekriterijumska Optimizacija I Kompromisno Resenje“ (VIKOR) methods in order to rank of the materials according to applied criteria. Analytical Hierarchy Process (AHP) method was performed in order to determine the weighting of the material properties or criteria. Rank the materials were gained by using ranking scores as results of the methods use. The results offer that the best polymers were found to be the LDPE and Nylon 6,6. It was proved that the multi-criteria decision-making model is an application for solving complex material choice decision problems. This model can be applied to other engineering applications with any number of alternatives and criteria for material selection.

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