Hybrid MCDM Model of ARAS -TOPSIS - GRA for Materials Selection Problem

Since traditional Multi-Criteria Decision Making (MCDM) approaches have become defunct, academics have shifted their attention to developing hybrid MCDM models, which use a combination of two or more MCDM methods to solve decision-making issues. Using Additive Ratio Assessment (ARAS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Gray Relational Analysis (GRA), the authors of this work aimed to develop unique hybrid MCDM systems. To show how well this hybrid model works, it is applied to a real-world material selection scenario including seven possible materials and seven criteria. Results from this hybrid model are compared to those from other standalone MCDM tools as well as previously published findings based on the same illustrative situation. 3rd Material is the best option, while the 2nd material is the worst option, among these seven choices which are consistent enough to imply such a conclusion. Using many MCDM strategies is recommended since no one strategy can ensure making the best decision. Because of this, the Copeland approach is used to combine the rankings from the 11 methodologies and get a consensus result. The results from the Copeland technique show that the final consensus rank of materials may be different from the rank of the hybrid model and other standalone MCDM tools. As a result, it is crucial to use a multi-pronged approach. Furthermore, the Spearman Correlation Coefficient (SCC) shows that the suggested rankings produced from the different approaches have a significant ranking association with one another

Hybrid MCDM Model of ARAS -TOPSIS - GRA for Materials Selection Problem

Since traditional Multi-Criteria Decision Making (MCDM) approaches have become defunct, academics have shifted their attention to developing hybrid MCDM models, which use a combination of two or more MCDM methods to solve decision-making issues. Using Additive Ratio Assessment (ARAS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Gray Relational Analysis (GRA), the authors of this work aimed to develop unique hybrid MCDM systems. To show how well this hybrid model works, it is applied to a real-world material selection scenario including seven possible materials and seven criteria. Results from this hybrid model are compared to those from other standalone MCDM tools as well as previously published findings based on the same illustrative situation. 3rd Material is the best option, while the 2nd material is the worst option, among these seven choices which are consistent enough to imply such a conclusion. Using many MCDM strategies is recommended since no one strategy can ensure making the best decision. Because of this, the Copeland approach is used to combine the rankings from the 11 methodologies and get a consensus result. The results from the Copeland technique show that the final consensus rank of materials may be different from the rank of the hybrid model and other standalone MCDM tools. As a result, it is crucial to use a multi-pronged approach. Furthermore, the Spearman Correlation Coefficient (SCC) shows that the suggested rankings produced from the different approaches have a significant ranking association with one another

A multi-attribute framework for determining the competitive advantages of products using grey-TOPSIS cum fuzzy-logic approach

Competitive advantage (CA) is a manufacturing business idea that assists organisations to be at benefits over rivals by keeping additional customers and exhibiting superior trade levels. Literature on prioritising measures and resources with respect to their impacts on competitiveness is interesting, important, promising but limited. However, CA decisions are confronted with factors to be prioritised having unequal importance. Additionally, data may be scanty and uncertain but quality decisions must be made. Furthermore, factors employed to judge the CA ability of organisations are disjointed and limited and do not often account for environmentalfriendliness in frameworks. Consequently, a new environmentally set of measures should be included in frameworks containing combined grey-TOPSIS and fuzzylogic. Using the resulting framework, a case study approach, based on expert judgement was adopted to exemplify and articulate the concept embedded in the approach. Study results indicate framework application feasibility and validity in packaging manufacturing. The novelties of the paper are: (i) development of a comprehensive CA method using greenness factors; (ii) addition of a case-based CA method for the Nigerian manufacturing environment; and (iii) application of combined grey-TOPSIS-fuzzy-logic framework for CA. The presented framework may serve as an effective CA implementation too

Performance drivers of green innovation under incomplete information

AbstractThe environmental management practices have been well studied; few studies are presented the firm's green innovation activities. This study is adopted to evaluate the green innovation for environment management, with a particular focus on managerial, process, product and technological aspects. The empirical analysis from Taiwanese printed circuit board manufacturing firm's reveals that such studies does exist and that the effect of focal firm's green innovation activities has been evaluated. This study identified the appropriate green innovation criteria for the case firms and developed the following selection method: (i) evaluate the weights of aspects, criteria and alternatives as described both by linguistic preferences; and (ii) rank alternative suppliers using a grey relational analysis with entropy weight. This study presents theoretical and empirical evidence of green innovation drivers in the domains of environmental management and has interesting implications for operations management research and practices. This knowledge may contribute to better decision-making towards implementing green innovation practices

A research on application of the measurement of alternatives and ranking according to compromise solution method for multi-criteria decision making in the grinding process

The efficiency of cutting methods in general and the grinding method in particular is evaluated through many parameters such as surface roughness, machining productivity, system vibrations, etc. The machining process is considered highly efficient when it meets the set requirements for these parameters such as ensuring the small surface roughness, small vibrations, and high productivity, etc. However, for each specific machining condition, sometimes the set criteria for the output criteria are opposite. In these cases, it is required to solve the Multi-Criteria Decision Making (MCDM) which means making the decision to ensure the harmonization of all criteria. In this study, a study on multi-criteria decision making in the grinding process of 9CrSi steel using CBN grinding wheels is presented. The experimental process was carried out with sixteen experiments according to an orthogonal matrix that designed by the Taguchi method. The workpiece velocity, feed rate, and depth of cut were changed in each experiment. At each experiment, the responses were determined including surface roughness (Ra), the vibration of the grinding wheel shaft in the three directions, corresponding to Ax, Ay, and Az, and material removal yield (Q). Four determination methods of weights for criteria were used. The Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was applied for multi-criteria decision making. The objective of this study is to identify an experiment that simultaneously ensures the small values of Ra, Ax, Ay, and Az and large value

A toolset for complex decision making in analyze phase of Lean Six Sigma Project: A case validation

The analyze phase of Lean Six Sigma (LSS) project is an important phase where the project heads and organizational directors need to select the critical issues for further improvements. The present work is primarily focused on analyze phase of LSS project to prioritized the Critical to Quality (CTQs) in a particular case industry. The CTQs prioritization is being done based on the five evaluation criteria found from the literature. The weights of the criteria are determined through the Modified Digital Logic (MDL) method. The identified CTQs in assembly section of case industry have been ranked through the Grey Relation Analysis (GRA) under fuzzy environment. The results of the study have been validated using fuzzy VIKOR. It is found that the ‘cost’ criterion is the most significant among other criteria with MDL weight of 0.3. Through fuzzy-GRA, out of ten identified CTQs, non availability of rack system is found to be the most critical issue in assembly section of case industry. The perceptions of industrial manager and production head of case industry are strongly in favor of the obtained results and has implemented the suggested solutions.To sustain in the competitive environment and produce quality product at right time, organizations need to control their CTQs as per their criticality. For this, the decision making becomes quite complex to select the most critical factors due to the fascinating nature of various criteria and sub-criteria. The present study is the first attempt that has implemented the multi-criteria decision-making approach in analyze phase of LSS project

Optimization of Friction Stir Welding Parameters of AA5052-H32 Aluminium Alloy using Taguchi and Taguchi-Pareto Methods

It is difficult to improve the quality of friction stir welded joints of AA5052-H32 material because of scarce metrics on its concurrent optimization and prioritization. However, the objective of this article is to obtain optimal parametric values and identify important parameters using the Taguchi-Pareto method during the friction stir welding process of AA5052-H32 material. Then the ranks, delta values and optimal parameters are determined. The critical parameters identified for the friction stir welding process are the tool pin, rotational speed, welding speed and tool angle. When comparing the results of these parameters using the Taguchi method and Taguchi-Pareto method, the rotational speed retained its first position in both methods; the tool tilt angle gained the second position in the Taguchi-Pareto method from its third position when only the Taguchi method was considered. The welding speed became the third position in the Taguchi-Pareto method against the second position that it had in the Taguchi method. However, the tool pin profile retained its last position in both methods. Consequently, the rotational speed is the best parameter while the tool pin profile is the worst parameter. For the Taguchi-Pareto method, the optimal parametric setting is TPP2/TPP4RS1WS4TTA3. This is interpreted as cylindrical tapered or square tapered for the tool profile, 40 rpm of rotational speed, 75 mm/min of welding speed and 1.5° of tool tilt angle. The novelty of this study is the scope of analysis of the AA5052-H32 material that extends beyond the Taguchi method to the Taguchi-Pareto method where the concurrent optimization and prioritization of friction welding parameters are achieved

A state-of-art survey on TQM applications using MCDM techniques

In today’s competitive economy, quality plays an essential role for the success business units and there are considerable efforts made to control and to improve quality characteristics in order to satisfy customers’ requirements. However, improving quality is normally involved with various criteria and we need to use Multi Criteria Decision Making (MCDM) to handle such cases. In this state-of the-art literature survey, 45 articles focused on solving quality problems by MCDM methods are investigated. These articles were published between 1994 and 2013.Seven areas were selected for categorization: (1) AHP, Fuzzy AHP, ANP and Fuzzy ANP, (2) DEMATEL and Fuzzy DEMATEL, (3) GRA, (4) Vikor and Fuzzy Vikor, (5) TOPSIS, Fuzzy TOPSIS and combination of TOPSIS and AHP, (6) Fuzzy and (7) Less frequent and hybrid procedures. According to our survey, Fuzzy based methods were the most popular technique with about 40% usage among procedures. Also AHP and ANP were almost 20% of functional methods. This survey ends with giving recommendation for future researches