Application Of Multi-attribute Decision-making Method Research Articles

Application of multi-attribute decision-making method based on fuzzy influence diagram in green supplier selection

The external business environment exhibits many uncertainties with the continuing changes in technological progress, political environment, and consumption behavior. This has made companies recognize the significance of addressing environmental issues to remain competitive in the modern global market. Thus, much attention is given to the supply chain to ensure environmental factors are considered during supplier selection. However, the process of selecting the right suppliers to enable green supply chain management is proving difficult. This paper presents a novel approach using fuzzy influence diagrams to identify key green supplier selection criteria, combined with multi-criteria decision making to evaluate alternatives. The fuzzy influence diagram derives priority supplier capabilities by modeling interrelationships and uncertainties. The multi-criteria technique then ranks suppliers based on prospect values. A case study of furniture manufacturer supplier selection validates the proposed method. Compared to existing models, this integrated approach reduces subjective weight bias and improves handling of complex criteria dependencies and uncertainties. The results demonstrate state-of-the-art performance in identifying ideal green suppliers. This technique can enhance sustainability efforts across supply chains.

Application of MADM methods in Industry 4.0: A literature review

Industry 4.0 has received inordinate attention from the business as well as research communities. Along with the development of Industry 4.0 applications and the diversity of potential alternatives, Multi-Attribute Decision Making (MADM) techniques have been employed by researchers as systematic approaches to support the decision-making processes. However, as the adoption of Industry 4.0 technologies requires considerable capital, and as it is relatively difficult to identify the suitable MADM method for the decision-making process in certain conditions, it becomes necessary to determine which components of Industry 4.0 are most commonly in demand of MADM applications of decision making, and which MADM techniques are mostly preferred by researchers and businesses for varied directions of Industry 4.0. Therefore, this study aims to provide a comprehensive review of MADM methods and their applications for different components of Industry 4.0. A methodology, including a review framework, is provided for the related analyses. The proposed framework includes analyses concerning methods, subtopics, and bibliometry along with the related exploratory tables and figures. Finally, the trends and research gaps are clearly stated to shed light on the further research areas taking into consideration different challenges that can be encountered by researchers, along with a set of propositions to potentially overcome them.

Application of multi-attribute decision-making methods for the selection of conveyor

In the present time of innovation, conveyor is an exceptionally indispensable part and has huge significance for material handling in various process and manufacturing industries. It is made with precisions, and the expenses are relatively high and should work with better productivity. The selection of the best conveyor is a crucial task, and the designers need to recognize different attributes that will influence the functionalities of the conveyor system to limit bottlenecks in the system. Researchers have worked on strategies for finding the best optimum solution for various selection problems, but conveyor selection using selected methods is not reported. Therefore, the present work aims to the selection process of the best option for conveyor by using four selected decision-making methods such as analytical hierarchy process, technique of order preference by similarity to ideal solution, compromise ranking method and Deng’s similarity-based method. The selection is done among four alternatives based on six attributes, viz. fixed cost each hour, variable cost each hour, conveyor speed, product width, product weight and flexibility. The analytical hierarchy process is used to determine weights of the attributes based on relative importance of each attribute. It is observed that A3 conveyor is best suitable conveyor. Hence, the proposed strategies help manufacturers to examine and choose the best conveyor.

Application of multi-attribute decision-making methods based on normal random variables in supply chain risk management

Abstract For the multi-criteria group decision-making problem where the criterion value is a normal interval number and the weight information is incomplete, the normal interval number and its compromise expected value, compromise mean square error, algorithm, weighted arithmetic average of normal interval number (ININWAA) Operator, the ordered weighted average (ININOWA) operator of normal interval numbers and the mixed weighted average (ININHA) operator of normal interval numbers, and a multi-criteria group with incomplete information based on normal interval numbers is proposed. Decision-making methods. This method uses ININWAA operator and INNHA operator to integrate criterion values, uses the compromise mean square error of criterion values, establishes an optimisation model to solve the optimal criterion weights and uses the expectation variance criterion to determine the order of the schemes. The case analysis shows the effectiveness and feasibility of this method.

Optimization of machining parameters under MQL turning of Ti-6Al-4V alloy with textured tool using multi-attribute decision-making methods

PurposeThis paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.Design/methodology/approachThe experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.FindingsThe results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speedVc= 80 m/min, feed ratef = 0.05 mm/rev. and depth of cutap= 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.Originality/valueThe research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

Application of multi-attribute decision-making methods in SWOT analysis of mine waste management (case study: Sirjan's Golgohar iron mine, Iran)

Mines provide essential materials for life and human progress; however, on the other hand, the possibility of life and having healthy environment is adversely affected by increasing pollution. Mine waste (tailing) is one of the pollutants generated by mines that should be properly managed. Nowadays, strategic management by using appropriate tools and technology is essential for the proper management of waste everywhere, including the urban, rural, medical, industrial, and mining environments. This study aims to identify strengths, weaknesses, opportunities, and threats (SWOT), and strategies for waste management in iron mines and provide a quantitative basis to analytically determine the ranking of the factors in SWOT analysis via conventional multi-criteria decision-making methods: Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).The AHP method was used to calculate the weights of evaluation criteria and the TOPSIS method was preferred because of its capability to use both negative and positive criteria among the SWOT factors. The results of the evaluation matrix of internal and external factors showed that overall, the strengths overcame the weaknesses. However, if the opportunities are used well and correctly, threats can be overcome and weaknesses can be eliminated. Therefore, strategies based on weaknesses–opportunities (WO) are first priority. Sixteen strategies that are presented based on the SWOTs and prioritized based on TOPSIS could be useful for Sirjan's Golgohar iron ore to develop and promote its future mine waste management at the strategic level.

Application of multiattribute decision-making methods for the determination of relative significance factor of impact categories.

A relative significance factor (f(i)) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f(i). Multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f(i). Thus, all three methods can be applied to the determination of f(i). The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f(i) because it is easier and simpler to use compared to the AHP and the fuzzy method.